Proceedings of I4SDG Workshop 2023: IFToMM for Sustainable Development Goals 3031324382, 9783031324383

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Mechanisms and Machine Science

134

Series Editor Marco Ceccarelli , Department of Industrial Engineering, University of Rome Tor Vergata, Roma, Italy

Advisory Editors Sunil K. Agrawal, Department of Mechanical Engineering, Columbia University, New York, NY, USA Burkhard Corves, RWTH Aachen University, Aachen, Germany Victor Glazunov, Mechanical Engineering Research Institute, Moscow, Russia Alfonso Hernández, University of the Basque Country, Bilbao, Spain Tian Huang, Tianjin University, Tianjin, China Juan Carlos Jauregui Correa , Universidad Autonoma de Queretaro, Queretaro, Mexico Yukio Takeda, Tokyo Institute of Technology, Tokyo, Japan

This book series establishes a well-defined forum for monographs, edited Books, and proceedings on mechanical engineering with particular emphasis on MMS (Mechanism and Machine Science). The final goal is the publication of research that shows the development of mechanical engineering and particularly MMS in all technical aspects, even in very recent assessments. Published works share an approach by which technical details and formulation are discussed, and discuss modern formalisms with the aim to circulate research and technical achievements for use in professional, research, academic, and teaching activities. This technical approach is an essential characteristic of the series. By discussing technical details and formulations in terms of modern formalisms, the possibility is created not only to show technical developments but also to explain achievements for technical teaching and research activity today and for the future. The book series is intended to collect technical views on developments of the broad field of MMS in a unique frame that can be seen in its totality as an Encyclopaedia of MMS but with the additional purpose of archiving and teaching MMS achievements. Therefore, the book series will be of use not only for researchers and teachers in Mechanical Engineering but also for professionals and students for their formation and future work. The series is promoted under the auspices of International Federation for the Promotion of Mechanism and Machine Science (IFToMM). Prospective authors and editors can contact Mr. Pierpaolo Riva (publishing editor, Springer) at: [email protected] Indexed by SCOPUS and Google Scholar.

Victor Petuya · Giuseppe Quaglia · Tigran Parikyan · Giuseppe Carbone Editors

Proceedings of I4SDG Workshop 2023 IFToMM for Sustainable Development Goals

Editors Victor Petuya Department of Mechanical Engineering University of the Basque Country Bilbao, Spain

Giuseppe Quaglia DIMEAS Politecnico di Torino Turin, Italy

Tigran Parikyan Advanced Simulation Technologies AVL List GmbH Graz, Austria

Giuseppe Carbone DIMEG University of Calabria Rende, Italy

ISSN 2211-0984 ISSN 2211-0992 (electronic) Mechanisms and Machine Science ISBN 978-3-031-32438-3 ISBN 978-3-031-32439-0 (eBook) https://doi.org/10.1007/978-3-031-32439-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

According to the definition adopted by the United Nations in 1987, “Sustainable Development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” Fully embracing this thought, IFToMM, the International Federation for the Promotion of Mechanism and Machine Science, started the Cross-Disciplinary Group 1 (CDG1) “Securing our Future Environment—Air, Water, Energy” and IFToMM for Sustainable Development Goals Workshop (I4SDG), in 2021. CDG1 aims at increasing the awareness related to global Sustainable Development Goals within the IFToMM scientific community, to generate a network of active researchers with specific interest on the effects of the new technologies for a sustainable world, to promote new research and solutions consistent with the United Nations 2030 Sustainable Development Agenda, and to foster the dialogue between technologists and humanists. I4SDG workshop is a tool to achieve these purposes. The first I4SDG edition was held online, due to the COVID-19 pandemic, in November 2021. This book collects all the papers presented in the second edition of the I4SDG workshop, organized by IFToMM Italy and the CompMech Research Group of the University of the Basque Country, and held in Bilbao on June 22–23, 2023. Every day it becomes clearer that sustainability, in the wide sense expressed by the UN Sustainable Development Goals (SDGs), is at the heart of tomorrow’s technical challenges. The 17 goals, adopted by all member states of the United Nations in 2015 as a part of the 2030 Agenda for Sustainable Development, represent a road map which can also address and inspire the research within typical areas of mechanism and machine science. The Sustainable Development Goals (SDGs) are a universal call to action to end poverty, protect the planet, and ensure that all people enjoy peace and prosperity. Founded in the post-Second World War era, IFToMM’s mission has always been to bring the people from different nationalities and systems together for scientific exchange and strengthening of international ties in the general area of Mechanism and Machine Science. Such solid weaving of peoples is more important than ever, and IFToMM is continuing this mission with a strongly growing network of its constituting member organizations. In recent years, the presence of global organizations such as IFToMM, which recognize the centrality of the human being and which build networks of international collaboration, is becoming increasingly important. Indeed, these networks are a formidable tool for reaching Goal 16, about promoting peaceful and inclusive societies, providing access to justice for all and building effective, accountable, and inclusive institutions at all levels. These recent years are highlighting not only the impacts of climate change, but also all health-related issues, and scientific communities such as IFToMM are called to engage in the search for solutions. Some, non-exhaustive, examples of the connection between IFToMM’s technical areas and SDGs can be summarized as follows: • Research on biomechanical engineering is correlated to SDG 3, Good Health, and Well-being.

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Preface

• Studies on sustainable energy systems are addressed to SDG 7, Affordable, and Clean Energy. • All the topics covered by IFToMM Technical Committees can be related to SDG 8, Decent Work and Economic Growth; SDG 9, Industry, Innovation, and Infrastructure; and SDG 12, Responsible Consumption and Production. • Decarbonization of vehicles and power plants to reduce the global footprint in the area of mobility, transportation, and power generation is related to SDG 13, Climate Action. • Humanitarian engineering and appropriate technologies are linked to SDG 10, Reduced Inequalities, and SDG 11, Sustainable Cities and Communities. I4SDG 2023 has been strongly supported by the following IFToMM Technical Committees, Permanent Commissions (PC), and Member organizations: Sustainable Energy Systems; Robotics and Mechatronics; Tribology; Linkages and Mechanical Controls; Biomechanical Engineering; Rotordynamics; Multibody Dynamics; Micromachines; Engines and Powertrains; Gearing and Transmissions; Computational Kinematics; Transportation Machinery; PC for the History of Mechanism and Machine Science; PC for Education; together IFToMM Italy and IFToMM Spain. I4SDG workshop is an example of collaboration and participation of the whole IFToMM world community, and without the help of IFToMM constitutional bodies, of all the organizers, and of all the authors, it would have been impossible to get so many significant contributions. A special acknowledgment is due to the IFToMM president, to all the TC/PC Chairs, to IFToMM Italy, to the CompMech Research Group, to the members of the Scientific and Organizing Committee, and to all the reviewers who gave their valuable feedback to realize this initiative. This book collects 56 scientific papers and is divided into eight chapters reflecting the technical sessions of the conference. All papers have been selected through a rigorous peer review process that considered their relevance, novelty, and clarity, guaranteeing the high-quality level of this work. Each paper is related to one or more SDGs and to one TC/PC topic. To clearly identify the relation between SDGs and the presented research, it was requested to include the most relevant SDG as the first keyword. The conference also had three special sessions: • Service Systems for Sustainability (coordinated by Maria Cristina Valigi) • Educational Experiences in Mechatronics (coordinated by Alberto Borboni) • Engines and Powertrains (coordinated by Tigran Parikyan). We are confident that any researcher who is interested in shaping his/her research activity considering its impact on building an inclusive, sustainable, and resilient future for people and the planet will find this book an exceptional and timely window on the latest findings in this area. Giuseppe Quaglia Victor Petuya Tigran Parikyan Giuseppe Carbone

Organization

Program Committee Chairs Carbone, Giuseppe Parikyan, Tigran Petuya, Victor Quaglia, Giuseppe

University of Calabria, DIMEG, Rende, CS, Italy AVL List GmbH, Advanced Simulation Technologies, Graz, Austria University of the Basque Country, Department of Mechanical Engineering, Bilbao, Spain Politecnico di Torino, Department of Mechanical and Aerospace Engineering, Torino, Italy

Contents

Sustainable Energy Systems Experimental Investigation to Enhance Performances of MRE in Energy Harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Renato Brancati, Giandomenico Di Massa, and Andrea Genovese Dynamic Motion Evaluation of a Novel Hybrid Wind and Wave Integrated Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ermando Petracca, Emilio Faraggiana, Massimo Sirigu, Giuseppe Giorgi, and Giovanni Bracco Model and Control Analysis for a Point Absorber Wave Energy Converter in Lebu, Chile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fabián G. Pierart, Claudio Villegas, Cristian Basoalto, Mathias Hüsing, and Burkhard Corves Novel Pseudo 3D Design of Solar Thermal Facades with Triangle and Trapeze Solar Thermal Collectors for Increased Architectural Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Denisa Rusea, Macedon Moldovan, and Ion Visa Fast Frequency-Domain Based Tool for FOWT Platforms Preliminary Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . María Alonso-Reig, Iñigo Mendikoa, and Victor Petuya

3

11

19

27

37

Robotics and Mechatronics A Framework for Improving the Energy Efficiency and Sustainability of Collaborative Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paolo Boscariol, Enrico Clochiatti, Lorenzo Scalera, and Alessandro Gasparetto Modeling and Parametric Analysis of Quasi-Translational Parallel Continuum Manipulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Luigi Tagliavini, Oscar Altuzarra, Giuseppe Quaglia, and Víctor Petuya Energy Efficiency of a SCARA-Like Manipulator with Elastic Balancing . . . . . . Luca Bruzzone, Shahab E. Nodehi, G. Berselli, and Pietro Fanghella

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55

65

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Contents

Deep Learning Technique to Identify Abrupt Movements in Human-Robot Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michele Polito, Elisa Digo, Stefano Pastorelli, and Laura Gastaldi

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Planning Real-Time Energy Efficient Trajectories for a Two Degrees of Freedom Balanced Serial Manipulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Domenico Dona’, Basilio Lenzo, and Giulio Rosati

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Reducing Energy Consumption and Driving Torque in an Underactuated Robotic Arm Through Natural Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jason Bettega, Dario Richiedei, Iacopo Tamellin, and Alberto Trevisani

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Online vs Offline Calibration of 5 DOFs Robotic Manipulators . . . . . . . . . . . . . . . Francesco Cosco, Michele Perrelli, Rocco Adduci, Arnaldo Michele Cerminara, Giuseppe Carbone, and Domenico Mundo

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Task-Specific Synthesis and Design of a Mobile Six-DoF Hexa Parallel Robot for Weed Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Tim Sterneck, Jannik Fettin, and Moritz Schappler Optimization of the Design Parameters of a 6-DOF Mobility Platform . . . . . . . . 115 L. A. Rybak, A. V. Khurtasenko, V. S. Perevuznik, K. V. Chuev, and D. I. Malyshev Biomechanical and Medical Systems Identification of Surgical Forceps Using YOLACT++ . . . . . . . . . . . . . . . . . . . . . . . 127 Shoko Memida and Satoshi Miura RehaWrist.q - Development of a 3 DoF Cable-Driven End-Effector Wearable Robot for Rehabilitation of the Wrist Joint . . . . . . . . . . . . . . . . . . . . . . . . 136 Giuseppe Quaglia, Andrea Botta, Giovanni Colucci, and Yukio Takeda Lifting Assist Device for Transfer in Cooperation with Caregivers . . . . . . . . . . . . 146 Mari Kurata, Ming Jiang, Kotaro Hoshiba, Yusuke Sugahara, Takahiro Uehara, Masato Kawabata, Ken Harada, and Yukio Takeda Design and Prototyping of a Semi-wearable Robotic Leg for Sit-to-Stand Motion Assistance of Hemiplegic Patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 Micah J. P. Alampay, Ming Jiang, Yusuke Sugahara, and Yukio Takeda Comprehensive Control Strategy Design for a Wheelchair Power-Assist Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Valerio Cornagliotto, Michele Polito, Laura Gastaldi, and Stefano Pastorelli

Contents

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Analytical Synthesis of the Seven-Bar Linkage 7-RR(RRRR)RR Used for Medical Disinfection Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Elida-Gabriela Tulcan, Alexandru Oarcea, and Erwin-Christian Lovasz Design of a Novel Medical Rolling Walker for Use in Hospital Environment . . . 181 Ángela Alonso Ortuzar and Saioa Herrero Villalibre Linkages, Gearing, Transmissions and Actuators Influence of Design Parameters in Energy Lost for Eccentric Cam Mechanisms with Translational Roller Follower . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 P. Català, L. Jordi, and J. M. Veciana Friction Models for a Sustainable Design: Friction Coefficient in Lubricated Conformal Pairs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Enrico Ciulli Evolution of Gear Machining Technology in a Japanese Manufacturer – Realization of Skiving Method as an Application of 5-Axes Machining Center - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Daisuke Matsuura and Tsune Kobayashi A Vibration Exciter for Dynamic Testing of Large Structures . . . . . . . . . . . . . . . . 217 Renato Brancati, Domenico De Falco, Giandomenico Di Massa, Stefano Pagano, and Ernesto Rocca Low Cost 3D Printed Pneumatic Linear Actuator . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 Daniela Maffiodo, Terenziano Raparelli, and Walter Incardona Development of Orientation Modules with Linear Actuation . . . . . . . . . . . . . . . . . 233 Florin Florescu, Radu Sebastian Zaharia, Ioan-Emil Popescu, Alexandru Oarcea, and Erwin-Christian Lovasz Analytical Synthesis of Five-Bar Linkage 5-RPRPR . . . . . . . . . . . . . . . . . . . . . . . . 241 Demjen Tivadar, Alexandru Oarcea, Carmen Sticlaru, Marco Ceccarelli, and Erwin-Christian Lovasz Technical Developments for Sustainable Engineering An Automatic Measurement System for Shape Memory Alloys’ Wire Resistivity Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253 Marco Siciliano, Francesco Lamonaca, Domenico Luca Carnì, Stefano Rodinò, Elio Matteo Curcio, Giuseppe Carbone, Domenico Mundo, and Carmine Maletta

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Contents

Fault Detection in Induction Machines of Air Handling Units . . . . . . . . . . . . . . . . 262 Christian Saab and Bechara Nehme Development of a Remote-Controlled Scaled Multi-actuated Vehicle . . . . . . . . . . 270 Stefano Lovato, Giovanni Righetti, Alice Canton, Basilio Lenzo, and Matteo Massaro Functional Design and Prototyping of a Novel Soft Fingertip with Variable Stiffness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 Giovanni Colucci, Carmen Visconte, and Giuseppe Quaglia Machine-Learning Based Energy Estimation on a High-Speed Transportation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290 Paolo Boscariol, Dario Richiedei, Iacopo Tamellin, and Alberto Trevisani Overturning Stability for the SNAP Cargo Family of Pedal-Assisted Ultralight Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 Francesco Passarella, Giacomo Mantriota, and Giulio Reina Gas Bearings Applications in Automotive Fuel Cell Technology . . . . . . . . . . . . . 307 Federico Colombo, Luigi Lentini, Terenziano Raparelli, and Andrea Trivella Numerical Simulation of Cylindrical Lithium-ion Cells Impact . . . . . . . . . . . . . . . 315 Miguel Antonio Cardoso Palomares, Juan Carlos Paredes Rojas, Adolfo Angel Cazares Duran, and Christopher René Torres San Miguel Conceptual Design and Numerical Analysis of a Photobioreactor to Cultivate Arthrospira . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324 A. A. Casarez-Duran, C. R. Torres-SanMiguel, J. C. Paredes-Rojas, M. A. Cardoso-Palomares, and G. M. Urriolagoitia-Calderón Movement Smoothness Metrics in Human-Machine Interaction . . . . . . . . . . . . . . 333 Mattia Antonelli, Elena Caselli, Laura Gastaldi, Luc Janssens, Stefano Pastorelli, Anna Bjerkefors, and Yves Vanlandewijck Education for Sustainabililty and Special Session: Educational Experiences in Mechatronics (Coordinated by Alberto Borboni) Humanitarian Techniques in the Teaching of Technical Sciences . . . . . . . . . . . . . 343 G. V. Tikhomirov, O. V. Egorova, G. A. Bazanchuk, and S. V. Kurakov

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Teaching Appropriate Technologies with the Applied Mechanics Approach to Sensitize Students to Their Future Role in Environmental Sustainability and Social Justice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 Walter Franco Machine Learning Algorithm for Robotic Inverse Kinematic Problem . . . . . . . . . 359 Alberto Borboni and Nataliya Shakhovska Robot Motion Planning in ROS Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 Alberto Borboni, Cinzia Amici, Ivan Archetti, Leonardo Archetti, and Rodolfo Faglia Intersubjective Dynamics in Cooperative Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Lorenzo Romagnoli A Code of Ethics for Social Cooperative Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . 382 Elena Guerra Special Session: Engines and Powertrains (Coordinated by Tigran Parikyan) Crankshaft Balancing Design Platform: A Practical Application . . . . . . . . . . . . . . 393 Eugenio Brusa, Alberto Dagna, Cristiana Delprete, and Chiara Gastaldi A Drop-In Phase Change Material-Based Augmented Cooling System for Track Capable Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403 Neeraj Shidore, Justin Skorski, Satish Ketkar, Jacob Wright, and Madhu Raghavan Decarbonizing Marine Sector: The Drop – In Solution of Marine Sustainable Fuels Following Their Lubricity Performance . . . . . . . . . . . . . . . . . . . 411 Thomas Vernados, Ioannis Stathopoulos, and Stamatis Kalligeros On the Influence of the Actual Load Sharing Factor in Increasing the Power Density in Gearboxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 420 Carlo Rosso and Fabio Bruzzone Driveability Constrained Models for Optimal Control of Hybrid Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 430 Federico Miretti and Daniela Misul Torsional Dynamic Performance of a Transmission Test Bench: An Investigation on the Effect of Motors Controllers Parameters . . . . . . . . . . . . . 441 Enrico Galvagno, Mauro Velardocchia, Antonio Tota, Luca Zerbato, and Angelo Domenico Vella

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Contents

Special Session: Service Systems for Sustainability (coordinated by Maria Cristina Valigi) Sustainable Design of Machine Guards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 Luca Landi, Silvia Logozzo, and Maria Cristina Valigi Robotic System for Hand Rehabilitation Based on Mirror Therapy . . . . . . . . . . . . 459 Monica Tiboni, Amici Cinzia, and Bussola Roberto Development of Energy Optimization Strategies for Catenary-Free Tramways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 468 Alessio Cascino, Gabriele Ciappi, Enrico Meli, and Andrea Rindi Multibody Simulation of an Underactuated Gripper for Sustainable Waste Sorting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 Gabriele Maria Achilli, Silvia Logozzo, and Monica Malvezzi Preliminary Study on a Handle with Haptic Devices for Collaborative Robotics in a Remote Maintenance Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Gabriele Maria Achilli, Francesco Chinello, Cheng Fang, Pedro Gomez Hernandez, Silvia Logozzo, and Maria Cristina Valigi Joint Stiffness Analysis and Regulation for Underactuated Soft Grippers Based on Monolithic Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 Mihai Dragusanu, Danilo Troisi, Domenico Prattichizzo, and Monica Malvezzi Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501

Sustainable Energy Systems

Experimental Investigation to Enhance Performances of MRE in Energy Harvesting Renato Brancati(B) , Giandomenico Di Massa , and Andrea Genovese University of Naples Federico II, Department of Industrial Engineering, Via Claudio 21, Naples, Italy [email protected] http://www.unina.it Abstract. The so-called “Smart Systems” are increasingly wide-spread impacting extremely different fields, that range from production systems to transport systems up to instrumented dress. For the correct functioning of these systems, it is necessary to use sensors that must be powered. When, for environmental or technical reasons it is not possible to employ cables or batteries, the sensors must be self-powered. The set of technologies used to transform energy dispersed in the environment into electrical energy useful for powering the sensors is called Energy Harvesting (EH). In this paper is investigated the use of Magnetorheological elastomers (MREs) as transducer for the conversion of mechanical vibration energy in electrical energy. The energy conversion, based on the “Villari Effect”, is obtained from the strain of a MRE pad immersed in a magnetic field. The device must also include a magnetic circuit and a coil. The behaviour of two types of specimens is investigated: the first made only with rubber while the second composed by rubber and thin iron sheets. The study made by means of an experimental test rig showed a noticeable increase of output voltage when the iron discs are also used. The paper represents a contribution to researches in the field of Sustainable Development Goals number seven: Affordable and Clean Energy. Keywords: SDG7 · Energy Harvesting Elastomer · Villari Effect

1

· Magnetorheological

Introduction

Energy Harvesting is a technology used for all those applications that involve self-powering devices such as, wearable devices, remote sensors or sensor nodes. The usage of sensor nodes is becoming increasingly widespread in a range of applications i.e. industrial processes, structures, vehicles, environment, traffic. They normally need cables for power supply but there are several applications, i.e. in remote or hostile environments, where the wiring with cables is unavailable [1]. The most common sources of energy adopted for EH are: solar, wind, thermal, mechanical. The proposed paper deals with the EH from mechanical c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 3–10, 2023. https://doi.org/10.1007/978-3-031-32439-0_1

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R. Brancati et al.

sources, in this case the energy transduction is based on three main physical principles: piezoelectric, electromagnetic and electrostatic [2]. In this study the possibility to use the magnetorheological elastomers as transduction mechanism is investigated. Magnetorheological elastomers consist of magnetic particles dispersed within a non-magnetic polymeric matrix. The presence of a magnetic field is able to condition the mechanical and the rheological properties of MREs, altering them quickly but in a reversible and controllable way. This phenomenon is commonly known as the MR effect. The MR effect is influenced by several factors, including the material of the matrix, the concentration and distribution of magnetic particles, the use of additives and the strength of the magnetic field. Most of the works present in the literature investigate the mechanical properties of the MREs and their applications [3–5]. Vibration isolators are devices in which the MREs are used to suitably adjust the stiffness according to external excitation [6–8]. The authors propose an “inverse” use of MREs, that is, the exploitation of the elastomer strain to induce a variation of a magnetic field and so inducing an electrical current inside a coil [9–11]. This paper reports some interesting results obtained from a purpose-built experimental test rig. In particular a strategy to enhance the efficiency of the Villari effect was investigated. In the first part of the paper the Villari effect for the MREs is explained. Then the experimental test rig, properly set up for this study, and the testing procedure are presented. Finally the experimental results are presented, showing that, when iron sheets are used together with the rubber elastomer, the voltage generation significantly increase.

2

Villari Effect

There is the phenomenon of magnetostriction when an object changes its shape if it is immersed in a magnetic field. In Fig. 1(a) a rod of magnetostrictive material is shown inserted in a winding. When the electric circuit is supplied with a current i, a magnetic field H is generated and the rod lengthens by an amount ΔL. The ratio ΔL L is called magnetostriction. Fig. 1(b) shows the qualitative trend of magnetostriction as the magnetic field varies. The inverse phenomenon to magnetostriction is called the Villari effect (magnetomechanical effect) [12]. Suppose to apply a variable force to a rod of magnetostrictive material inserted inside a coil and so immersed in a magnetic field of module H0 . The force F (t) causes a deformation of the rod, and a potential difference v(t) is generated at the ends of the winding. (Fig. 2) Indeed the following equation subsists: B(t) = d∗ σ(, H) + μ(, H)H0

(1)

where F indicates the applied force, σ is the ratio between F and the section surface,  the deformation, d∗ is the magneto-mechanical coupling coefficient [m/A] and μ is the magnetic permeability of the rod. The variation of magnetic induction B(t) is due to two contributions: the variation of stress σ and the variation of permeability μ.

Experimental Investigation to Enhance Performances of MRE

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Fig. 1. Magnetostriction effect

Fig. 2. Villari Effect

The variable voltage is then generated: v(t) = Ns A

dB dt

(2)

with Ns number of turns of the winding. Figure 3 shows the experimental set-up proposed for the evaluation of the MREs transduction mechanism. It is worth noting that the necessary magnetic field can be obviously generated by a permanent magnet. In order to easily change the magnetic field magnitude during the experimental campaign a coil is used. In the other coil, search coil, there is the inducted electrical voltage v(t). The MRE samples are deformed by means of an electromagnetic shaker. Respect to the piezoelectric material or the magnetostrictive material, the magnetorheological rubber has three great advantages: it can suffer hight amplitude strains, it has lower costs, it can be recycled the rubber that must be disposal.

6

R. Brancati et al.

Fig. 3. Experimental set-up Scheme

Fig. 4. Test rig photo

3

Test Rig

Fig. 4 shows a photo of the test rig whose main components are: the magnetic circuit, the MRE specimens, the devices for impose the motion and the measurement instruments. 3.1

Magnetic Circuit

The magnetic circuit is composed by following elements: • Cylindrical “Excitation Coil” with 1000 turns winding (25 mm height, 60 mm inner diameter, 113 mm external diameter); • Cylindrical “Search Coil” with 5000 turns winding (25 mm height, 60 mm inner diameter, 113 mm external diameter); • Two 9 mm height MRE specimens; • Two iron plates and four iron columns. The supply current of the excitation coil, that varies between 0 and 3 A, is provided by a laboratory power-supply.

Experimental Investigation to Enhance Performances of MRE

7

Fig. 5. Specimens

Fig. 6. Measured Motion

3.2

MRE Pads

Magneto-rheological elastomers (MRE), which belong to the magnetorheological material family, are composite materials with magnetically polarized suspended particles or arranged particles, dispersed in an elastomer matrix. MRE compounds may be isotropic if the particles are randomly dispersed or anisotropic if the particles are arranged in columns. The mixture used for the MRE pads employed in the experimental tests is composed by low stiffness silicone rubber (Prochima GLS-10) and iron-carbonyl powder. The volume percentage of powder is 25%, in the curing phase a magnetic field is applied to the MRE mixture in order to align the powder particles on columns. Each pad has a cylindrical shape with 30 mm of radius and 3 mm of height. Two specimen types were tested: the first type consists of three pads overlapped while the second one consists of three MRE pads among which they are inserted thin iron disks. Fig. 5 shows the two specimen types used.

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Fig. 7. Output Voltage

3.3

Motion Excitation System

A shaker, Bruel & Kjaer 4808, provides the motion to impose to the MRE specimens. A signal generator give the desired electrical tension waveform, by means of an amplifier the shaker is supplied with the desired waveform. The desired excitation motion is so obtained. 3.4

Measurement Devices

The voltage across the search coil winding is measured directly with Yokogawa data acquisition device. The displacement is measured with the laser sensor OptoNCDT 1420 and the applied force is measured with the load cell Dytran 6210 s.s. The magnetic field magnitude inside the specimen and near the plate is measured with the magnetometer “Hirst Magnetics GM08”.

4

Results

A 0.8 mm amplitude sinusoidal motion is imposed. The frequency of motion 3 Hz. Figure 6 shows the measured specimen motion. The measured output voltage is sinusoidal with a frequency 6 Hz but is noisy and it was filtered with a moving average filter. Figure 7 shows a measured output voltage and the filtered one. The supply current of excitation coil was varied between 0 and 3 A and in the Table 1 is reported the correspondence between excitation coil supply current and magnetic field magnitude inside MRE. The Fig. 8 shows the output voltage amplitude versus supply excitation coil current for the two specimen types. It can be observed that as the current varies, the output voltage first increases but then decreases, reaching a maximum between 2.5 and 2 A or for a magnetic field between 220 and 320 mT. This behaviour has already been highlighted in previous studies ([9,10]). The novelty concerns the significant increase in tension that is obtained by inserting the thin iron discs between the pads.

Experimental Investigation to Enhance Performances of MRE

9

Table 1. Current - Magnetic Field Correspondence Current (A) Magnetic Field only MRE (mT)

Magnetic Field MRE + Iron Sheet (mT)

0

28

27

0.5

95

89

1

174

162

1.5

246

229

2.0

320

293

2.5

381

354

3.0

440

413

Fig. 8. Output Voltage Amplitude

5

Conclusion

In this work an energy harvester based on Villari Effect is proposed. The harvester consists of magnetorheological rubber elements and a magnetic circuit. It has been made two types of MRE specimen and one magnetic circuit. The experimental rig is completed by an electrodynamic shaker, some sensors and an acquisition device. The experimental tests were designed to evaluate the output voltage varying the magnetic field that is the current at the excitation coils. The measures in addition to confirming that the Villari Effect is maximized when the magnetic field is between 200 and 250 mT, they show that the presence of iron discs significantly improves the transformation of energy.

References 1. D´ıez, P.L., Gabilondo, I., Alarc´ on, E., Moll, F.: Mechanical energy harvesting taxonomy for industrial environments: application to the railway industry. IEEE Trans. Intell. Transp. Syst. 21(7), 2696–2706 (2019)

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2. Wei, C., Jing, X.: A comprehensive review on vibration energy harvesting: modelling and realization. Renew. Sustain. Energy Rev. 74, 1–18 (2017) 3. Brancati, R., Di Massa, G., Pagano, S.: Investigation on the mechanical properties of MRE compounds. Machines 7(2), 36 (2019) 4. Sapouna, K., Xiong, Y.P., Shenoi, R.A.: Dynamic mechanical properties of isotropic/anisotropic silicon magnetorheological elastomer composites. Smart Mater. Struct. 26(11), 115010 (2017) 5. Yu, Y., Li, Y., Li, J., Gu, X.: A hysteresis model for dynamic behaviour of magnetorheological elastomer base isolator. Smart Mater. Struct. 25(5), 055029 (2016) 6. Behrooz, M., Wang, X., Gordaninejad, F.: Performance of a new magnetorheological elastomer isolation system. Smart Mater. Struct. 23(4), 045014 (2014) 7. Brancati, R., Massa, G.D., Pagano, S., Petrillo, A., Santini, S.: A combined neural network and model predictive control approach for ball transfer unitmagnetorheological elastomer-based vibration isolation of lightweight structures. J. Vib. Control 26(19–20), 1668–1682 (2020) 8. Leng, D., Feng, W., Ning, D., Liu, G.: Analysis and design of a semi-active xstructured vibration isolator with magnetorheological elastomers. Mech. Syst. Signal Process. 181, 109492 (2022) 9. Brancati, R., Di Massa, G., Genovese, A.: Electromagnetic-mechanical coupling in the magneto-rheological elastomers elastomers: an experimental overview. Int. J. Mech. Control 22(2), 27–33 (2021) 10. Diguet, G., Sebald, G., Nakano, M., Lallart, M., Cavaill´e, J.Y.: Optimization of magneto-rheological elastomers for energy harvesting applications. Smart Mater. Struct. 29(7), 075017 (2020) 11. Sebald, G., Nakano, M., Lallart, M., Tian, T., Diguet, G., Cavaille, J.Y.: Energy conversion in magneto-rheological elastomers. Sci. Technol. Adv. Mater. 18(1), 766–778 (2017) 12. Zhao, X., Lord, D.G.: Application of the Villari effect to electric power harvesting. J. Appl. Phys. 99(8), 08M703 (2006)

Dynamic Motion Evaluation of a Novel Hybrid Wind and Wave Integrated Platform Ermando Petracca(B)

, Emilio Faraggiana, Massimo Sirigu , Giuseppe Giorgi , and Giovanni Bracco

Marine Offshore Renewable Energy Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy [email protected]

Abstract. Hybrid wind and wave platforms are among the most promising technologies to foster access to untapped renewable energy in deep seas. This technology aims to leverage synergies between wave and wind conversion systems by sharing costs, such as mooring and electrical connection, and combining their power production. The platform is usually a floating offshore wind turbine (FOWT) integrated with one or more wave energy converter (WEC) devices. WECs, compared to FOWT, are less mature technologies as there is a general lack of design convergence nor a standard layout. This paper investigates the capabilities of a new hybrid concept developed at Politecnico di Torino, which integrates a FOWT with three point absorber WECs, such WECs are integrated into the floating structure and are fundamental to obtaining the desired hydrostatic and dynamic stability. The in-house hydrostatic stability tool and the time domain model MOST are used to analyse the hybrid system motions performances with two modes: WEC activated or blocked; in this way, this paper purports to critically discuss differences and advantages of the hybrid WEC-activated solution with respect to rigid floating substructures. The WEC-activated scenario outperforms the blocked configuration, with a 12% reduction of the nacelle acceleration. Keywords: SGD 7 SDG 13 · SDG 11 · Floating offshore wind · Wind energy · Wave energy · Hybrid platforms · Renewable Energy · Multi-body systems

1 Introduction Nowadays, climate change and the sustainable energy scenario are the most relevant issues. Some of the UN Sustainable Development Goals (SDGs) focus on the capability of the energy sector to provide clean and sustainable energy from renewable sources; in particular, SDG 7 aims to ensure access to affordable, reliable, sustainable energy for all; SDG 11 purports to make cities inclusive, safe, resilient, and sustainable; SDG 13 focuses on actions to fight climate change. Globally the theoretical resource potential of ocean energy is 80’000 TWh of electricity generation per year, representing almost 400% of the global demand [1]. Within this scenario, the European Green Deal supports the energy transition towards decarbonization of the supply chain and includes a strategy © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 11–18, 2023. https://doi.org/10.1007/978-3-031-32439-0_2

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for offshore renewable energy technologies [2, 3]. The main target is to achieve 300 GW and 40 GW from offshore wind and ocean energy, respectively, in Europe by 2050. Although offshore wind and wave energy converters are often developed separately, as done respectively in [4] and [5] there are significant synergies that can be exploited between such technologies, including cost-sharing and power production variability compensation. There are several examples of scientific work analysing hybrid energy solutions. For example, a novel concept combining the Nautilus platform and four-point absorbers was investigated by [6], where the hybrid concept leads to a 10% reduction in the Levelized Cost Of Energy (LCOE) and improved hydrodynamic stability, compared to a floating wind turbine alone. Combining the Fincantieri Sea Flower Floater with the ISWEC gyroscopic device, [7] demonstrates an improvement of the stability of the floater and a reduction of hull pitch motions up to 37%. Hybrid solutions for offshore wind and wave energy have been attracting industrial interest, trying to achieve more competitive devices than offshore wind alone. W2Power is one of the most successful examples of a floating hybrid wind device [8], combining two wind turbines in the front corners and multiple point absorber WECs on the same semi-submersible platform. Another example of a floating hybrid platform is the Poseidon P37 platform, developed by Floating Power Plant Ltd [9]: the wave absorbers consist of a front pivot hinged absorber (float) that can absorb both the push and lift of the wave into one mechanical movement, which aliments the Power take-off (PTO) chain. The PTO system is an oil-based multi-cylinder hydraulic system connected directly to the hinge axis of the absorbers. Within this context, this paper aims to investigate the novel and patented floating hybrid platform [10]. The hybrid system comprises the NREL 5 MW wind turbine [11] and three hinged WECs. The wind turbine is a three-bladed, horizontal-axis wind turbine mounted above the floating platform. The hybrid floating platform is made of a central cylinder with ballast in the lower part (Fig. 1). The cylinder has reduced dimensions (height) to support the installation in shallow water (at least 60 m deep). The WEC is connected to the central cylinder by arms. The floating platform stability is achieved almost entirely thanks to the presence of the WECs. Note that state-of-the-art floating offshore wind turbines achieve stability by longer spars of larger fixed structures [12]. The WECs generate electrical energy by rotating the WEC arms around the hinges arranged around the central cylinder. Each WEC arm is connected to a hydraulic PTO (Fig. 2), which converts the arms’ mechanical rotational energy into hydraulic and electrical energy. A hydraulic PTO (HPTO) is considered the most effective PTO for pointabsorber-based WECs due to its high efficiency (almost 90% [13], high controllability, well-adapted to the high-power density of ocean waves at low frequency (Table 1). After an introductory section, this paper is structured into two parts: Sect. 2 proposes the methodology to design the platform, including considerations on applicable regulations and performs dynamic simulation; then, the theory to analyse static and dynamic features of the hybrid energy system is elaborated and applied. Finally, results are reported in Sect. 3, while some concluding remarks are presented in Sect. 4.

Dynamic Motion Evaluation of a Novel Hybrid Wind and Wave

Fig. 1. Top view of novel patented hybrid wind and wave floating platform

Fig. 2. Side view of novel patented hybrid wind and wave floating platform [10]

13

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E. Petracca et al. Table 1. The main geometric and mass features

Page

Value

Unit

H

5

m

D

15.0

m

Larm

40

m

2 Methods The analysis of the hybrid device is carried out in MATLAB environment, connecting different pieces of software, either open-source or in-house codes [14]. First it is assessed the hydrostatic stability extracting the metacentric height and verifying the maximum pitch static angles of the platform. Then, the dynamic motion of the system is assessed. The hydrodynamic coefficients are calculated using the linear potential flow solver Nemoh, based on the meshes provided by the Salome software and the computed centre of gravity (CoG). Finally, the dynamic simulation of the floating platform is computed using the in-house code MOST [14]. The dynamic simulation is performed to evaluate the dynamic stability of the platform and to compute the power generated by the WECs. 2.1 Hydrostatic Stability The stability tool calculates the static pitch angle, the metacentric height and the righting moment curve and is compared with DNV recommended values [15]. The DNV standard recommends a metacentric height of larger than one. At the same time, the area under the righting moment curve until the second intercept should be equal to or greater than 130% of the area under the wind heeling moment. The metacentric height can be expressed as a function of the metacentric height (GM)) GM = KB +

I + KG V

where K is the origin of the vertical coordinates, I is the moment of inertia of the waterplane about the axis of inclination, G and B are the centers of buoyancy and gravity, while V represent the volume of displacement. The angle of the static equilibrium in the pitch direction is computed as αsp =

MW ih

where the MW is the heeling moment on the wind turbine and ih is hydrostatic stiffness. The wind heeling moment is estimated from the heeling moments due to the tower and the rotor:   1 2 2 cos(αh ) C v(h) D(h)hdh + c V A h MW = MWt + MWr = ρair ∫hmax Dt Tmax r r r hmin 2

Dynamic Motion Evaluation of a Novel Hybrid Wind and Wave

15

where ρair is the air density, CDt is the drag coefficient of the tower, v(h) is wind speed, D(h) is the diameter of the tower for each height, hmin and hmax are the distances between the center of buoyancy (COB) and the bottom and top position of the tower, cTmax and Vr are the maximum thrust coefficient and the wind speed associated, Ar is the swept area, hr is the rotor height relative to the COB and αh is the heeling angle. 2.2 Time Domain Model The hydrodynamic time-dependent loads are extracted from the hydrodynamic frequency coefficients calculated for the four hydrodynamic bodies using the open-source Nemoh [16]. Nemoh is based on linear potential flow theory, which assumes an inviscid, irrotational and incompressible flow. A fluid potential φ is defined as a function of displacement x, y, z and time domain t to represent the velocity field of the fluid. The equation for the conservation of mass and momentum under the given assumption is reduced to Laplace’s equation ( ∇φ 2 = 0). φ = φI + φD + φR where φD is the diffraction potential, φR is the radiation potential, and φI is the incident wave potential. The hydrodynamic force computed by integrate the hydrodynamic pressure on the floating body surface. Beneath this consideration, the motion of a floating body in the frequency domain can be expressed by the following equation (m + A∞ )X¨ (t) + C X˙ (t) + KX (t) = F(t) where A∞ is the infinite added mass matrix. The external force is F(t) in time domain, and the radiation and excitation forces (Frad (t), Fexc (t)) for each hydrodynamic body (WECs and central cylinder) have been calculated respectively as Frad (t) = −A∞ X¨ − ∫t0 Kr (t − τ )X˙ (τ )d τ and

⎛ Fexc (t) = Re⎝

N 

Fexc (ωj , θ ei(ωj t+ϕj )



⎞  2S ωj d ωj ⎠

j=1

where, Kr is the radiation impulse response function, ω and ϕ are the wave and phase frequencies, S(ω) is the wave spectrum. The aerodynamic loads are calculated using Blade Element Momentum Theory (BEMT) with Prandtl’s Tip Loss and Glauert corrections. The mooring is modelled using a quasi-static approach which computes the catenary equation for each single line [17].

3 Results This section analyses the difference between the configuration of the hybrid platform, considering the three WECs either with an active operational PTO or a blocked PTO

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scenario: the former case is a coupled multi-body system, while the latter represents an equivalent only-wind platform, i.e. no wave energy conversion and no influence on the overall dynamics. Figure 3 describes the response amplitude operator (RAO) in the main response directions (Heave, Surge, and Pitch) of each WEC and of the entire floating platform. The simulation is performed with a regular wave with an elevation of 1 m and a fixed wind velocity equal to 11 m/s. Table 2 resumes the main static and dynamic statistical results of the simulations, with an irregular wave (significant wave height (Hs ) of 4 m, and peak period (TP ) of 10 s) and wind velocity equal to 11 m/s.

Fig. 3. RAO platforms values at heave, surge and pitch directions of the blocked scenario (blue line) and activated WEC scenario (red line)

Table 2. Results of static and dynamic performances comparison between two scenarios for a wave period of 10 s and elevation of 6 m Parameter

Activated PTO

Blocked PTO

Value

Unit

Value

Unit

Root mean square (RMS) Nacelle acceleration

0.443

m/s2

0.5061

m/s2

Pitch max

8.1

Deg

1.6

Deg

The novel hybrid wind and wave energy systems is stable in both configurations, since a steady harmonic response is obtained to harmonic wave input; as shown in Fig. 3,

Dynamic Motion Evaluation of a Novel Hybrid Wind and Wave

17

concerning both scenarios studied. The activated WEC scenario shows the peak of the RAO within a range of wave periods typical of the North Sea (14–18 s) [6]. Instead, looking at the blocked scenario, the RAO pitch natural period shifts to around the typical Mediterranean wave period (6–10 s) [18]. This suggests that the presence of the WECs can significantly modify the dynamics of the systems, to such an extent to make it fit for different Sea basins; in particular, since the WEC-activated hybrid system has the (undesired) highest pitching response away from the typical Mediterranean wave periods, it is particularly suitable for installation such a closed sea. In Table 2 we can observe that, in the activated WEC scenario, the nacelle acceleration root mean square value is 12% lower than the blocked configuration, confirming the dramatic role of the WEC as a counterbalance into system dynamics. On the other hand, the maximum inclination performed for WEC-activated is higher (8.1°) than compared to the blocked WEC scenario result (1.6°). This difference is based on the nature of the coupling of platform motion and the WEC point absorber. The two WECs on the sides of the platform compress the respective piston and allow the structure to tilt over more than the tilt results for the configuration when these remain blocked. Meanwhile the blocked configuration, performs a greater resistance to the heeling moment, which is fundamental when a failure occurs, and the system shut down to prevent further damage.

4 Conclusions Within this context, the present dynamic assessment of the novel hybrid system confirms its significant impact on the hydrostatic and dynamic response. Furthermore, the system has the potential to be more suited for deployment in the Mediterranean Sea site, due to the reduction of the pitching response and nacelle acceleration in most recurrent sea states. This promising feature can be leveraged in a feedback design loop, where the characteristics of both the supporting floating structure and the attached WECs is optimized in terms of dynamic response for a given installation site, as well as productivity and structural fatigue.

References 1. Bhuyan, G.S.: World-wide status for harnessing ocean renewable resources. In: IEEE PES General Meeting, vol. 2010 (2010).https://doi.org/10.1109/PES.2010.5589292 2. Szpilko, D., Ejdys, J.: European green deal—research directions. a systematic literature review. In: Ekonomia (2022) 3. Vargiu, A., Novo, R., Moscoloni, C., Giglio, E., Giorgi, Mattiazzo, G.: An energy cost assessment of future energy scenarios: a case study on san Pietro Island. Energies 15(13), 4535 (2022). https://doi.org/10.3390/en15134535 4. Cottura, L., Caradonna, R., Novo, R., Ghigo, A., Bracco, G., Mattiazzo, G.: Effect of pitching motion on production in a OFWT. J. Ocean Eng. Mar. Energy 8(3), 319–330 (2022). https:// doi.org/10.1007/s40722-022-00227-0 5. Rava, M., et al.: Low-cost heaving single-buoy wave-energy point absorber optimization for Sardinia west coast. J. Mar. Sci. Eng. 10(3), 397 (2022). https://doi.org/10.3390/jmse10 030397

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6. Petracca, E., Faraggiana, E., Ghigo, A., Sirigu, M., Bracco, G., Mattiazzo, G.: Design and techno-economic analysis of a novel hybrid offshore wind and wave energy system. Energies 15(8), 2739 (2022). https://doi.org/10.3390/en15082739 7. Fenu, B., et al.: Analysis of a gyroscopic-stabilized floating offshore hybrid wind-wave platform. J. Mar. Sci. Eng. 8(6), 439 (2020) 8. Legaz, M.J., Mayorga, P., Coronil, D., Fernández, J.: Study of a Hybrid Renewable Energy Platform: W2POWER (2018). http://asmedigitalcollection.asme.org/OMAE/procee dings-pdf/OMAE2018/51326/V11AT12A040/2537022/v11at12a040-omae2018-77690.pdf 9. McTiernan, K.L., Sharman, K.T.: Review of hybrid offshore wind and wave energy systems. In: Journal of Physics: Conference Series, vol. 1452(1) (2020). https://doi.org/10.1088/17426596/1452/1/01201 10. Faraggiana, E., et al.: Piattaforma Ibrida Per L’estrazione di Energia Eolica ed Ondosa (2022). (Patent No. 102022000024684) 11. Jonkman, J.M.: Dynamics of offshore floating wind turbines-model develop-ment and verification. Wind Energy 12(5), 459–492 (2009). https://doi.org/10.1002/we.347 12. Faraggiana, E., Giorgi, G., Sirigu, M., Ghigo, A., Bracco, G., Mattiazzo, G.: A review of numerical modelling and optimisation of the floating support structure for offshore wind turbines. In: Journal of Ocean Engineering and Marine Energy, (Vol. 8, Issue 3, pp. 433–456). Springer Science and Business Media Deutschland GmbH, Berlin (2022). https://doi.org/10. 1007/s40722-022-00241-2 13. Jusoh, M.A., Ibrahim, M.Z., Daud, M.Z., Albani, A., Yusop, Z.M.: Hydraulic power take-off concepts for wave energy conver-sion system: a review. In: Energies (Vol. 12, Issue 23). MDPI AG (2019). https://doi.org/10.3390/en12234510 14. Faraggiana, E., Sirigu, M., Ghigo, A., Bracco, G., Mattiazzo, G.: An efficient optimisation tool for floating offshore wind support struc-tures. Energy Rep. 8, 9104–9118 (2022). https:// doi.org/10.1016/j.egyr.2022.07.036 15. DNV-GL, Floating wind turbine structures (2018) 16. Soulard, T., Babarit, A.: Numerical Assessment of the Mean Power Production of a Combined Wind and Wave Energy PlatforM (2012). http://asmedigitalcollection.asme.org/OMAE/pro ceedings-pdf/OMAE2012/44946/413/4429150/413_1.pdf 17. Masciola, M.: MAP++ Documentation Release 1.15 (2018) 18. Ruzzo, C., Saha, N., Arena, F.: Wave spectral analysis for design of a spar floating wind turbine in Mediterranean Sea. Ocean Eng. 184, 255–272 (2019). https://doi.org/10.1016/j. oceaneng.2019.05.027

Model and Control Analysis for a Point Absorber Wave Energy Converter in Lebu, Chile Fabi´ an G. Pierart1(B) , Claudio Villegas1 , Cristian Basoalto1 , Mathias H¨ using2 , and Burkhard Corves2 1

2

Department of Mechanical Engineering, College of Engineering, Universidad del B´ıo-B´ıo, 4051381 Collao Avenue, Concepci´ on 1202, Chile {fpierart,cvillegas,cbasoalto}@ubiobio.cl Institute of Mechanism Theory, Machine Dynamics and Robotic (IGMR), RWTH Aachen University, Eilfschornsteinstr. 18, 52062 Aachen, Germany {huesing,corves}@igmr.rwth-aachen.de Abstract. Wave energy has enormous potential and many good qualities, such as its predictability, energy density and low variability. Nevertheless, this type of energy still needs to be competitive against other types of renewable energy, like wind or solar ones. This is mainly due to its high cost. One solution to reduce the cost of wave energy is the use of control strategies. In this work, a simple point absorber based on the dimensions of an ongoing project, named Lafkenewen, is modeled with linear potential theory and the software Ansys-AQWA. Three different control strategies, reactive control, latching control and resistive control, are compared for a regular wave that represents the mean sea state of the project site location. Results show that the reactive control can achieve up to 18 kW but for unrealistic conditions. Latching control allows converting up to 4 kW showing better performance than the resistive control, which only allows up to 0.8 kW average.

Keywords: SDG7 Conversion

1

· Renewable Energy · Control Design · Sea Energy

Introduction

Nowadays, there is an increasing global need for energy. Yet, our worldwide capability for generating it has descended from 0.8% annual increase between 2010 and 2018 to 0.5% annual increase between 2018 and 2020 [2]. This increase should be accelerated to 0.9% if we are to reach Sustainable Development Goal 7 (SDG7) and achieve global energy access by 2030. To accelerate the rate of energy development, many energy forms can be considered. A group of them are renewable energies. Amongst them, we can find the most common ones: hydraulic energy, solar energy and wind energy. Still, in development, ocean renewable energy, and particularly wave energy, shows a big raw potential. The c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 19–26, 2023. https://doi.org/10.1007/978-3-031-32439-0_3

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available power in coastal grid zones where the power per meter of the wavefront is greater than 5 kW/m reaches 2.99 TW globally, which can increase if we consider offshore grids [3]. This value is roughly equivalent to the mean power consumption in the world in 2021 [4]. Most of this raw power is located near southern and northern countries, for example, Denmark, Scotland, Australia or Chile [5]. Amongst ocean energies, wave energy is at the top in terms of mean raw power per year. Moreover, its predictability makes it attractive for its use in power grids [6]. In order to harvest such power, an wave energy conversion device (WEC) is required. In this context, many WECs have been developed to harvest energy from sea waves. Some of them are the Wavestar [7], Pelamis [8] and Wave Dragon [9], to mention a few. These devices are typically categorized depending on how they interact with the waves. Many categorization methods and improvements to WECs have been developed over the years. Nonetheless, there is no clear consensus in the field about a standard type of them, as it exists for other kinds of energies. An example of this fact is that the current number of wave devices almost reaches 1000, and only 200 are in the test phase [6]. Therefore, technology convergence is needed. For this, a collaboration between scientists, developers and politicians is especially required. Furthermore, identifying the best WECs candidates, increasing the total efficiency of the energy conversion, and improving the technologies are required nowadays to reach low emissions [11]. Apart from the conversion efficiency, the operation and maintenance of these devices play an important role in the costs of these technologies. It varies from device to device. These costs could be reduced if WECs share the infrastructure of existing devices, for example, offshore wind parks [11] or breakwaters [10]. Moreover, the costs of installation, foundation and mooring are also reduced by sharing the structure. Costs are also reduced with progress in technology and increase in efficiency. It is predicted a cost reduction of about 22% for PTOs, 18% for installation, 17% for operation and maintenance, 6% for foundation and mooring as well as 5% for grid connection [12]. To improve costs as well as survivality and efficiency, a major emphasis is put on numerical models and simulation of WEC prototypes. These models require information about the location, depth of the sea and historical wave data to enhance the lifespan and efficiency of the PTO [12]. Moreover, this information highly influences the possible extracted power, for example, depending on whether the eigenfrequency of the system can be reached by the wave oscillation. Furthermore, the oscillation of waves in South-American Pacific ocean typically have longer periods. Therefore, control techniques have to be carefully evaluated there. On these waters, particularly at Lebu, Chile, a point-absorber prototype is being built. It is called Lafkenewen [10]. The contribution of this work is to analyze the theoretical extracted power of this particular prototype under its own sea conditions using different control techniques. This analysis is based on fundamental concepts of Wave Energy Conversion. First, the equations of motions of this point absorber are presented and linearized. Then, the average power is obtained based on the hydrodynamic parameters obtained with Ansys-AQWA software. Afterwards, three different control strategies are implemented based on the mathematical model. Finally, results are compared based on the power, the velocity and the position of the WEC.

Model and Control Analysis for a Point Absorber

2 2.1

21

Background Study Case

The main dimensions of the WEC and the characteristics of the sea state are based on the project named “Wave energy converter Lafkenewen” to be deployed in 2024 at Lebu, in the south of Chile [10]. Based on on-site measurements, it was found that the predominant period of the waves is 12 s and their average amplitude is ca. 30 cm. A schematic representation of the WEC is shown in Fig. 1.

Fig. 1. Representation of the Lafkenewen WEC connected to the PTO.

The buoy is attached to a vertical shaft restricted to heave motion by two axial bearings. The power-take-off (PTO) system consists in a direct mechanical drive system using a rack and pinion connected to a electrical generator. 2.2

Mathematical Model

The most common approach to represent the dynamics of a floating body in the time domain was derived in 1962 by Cummins [1]. For a body of mass M with no forward speed and considering an ideal fluid, Cummins equation can be written as shown in (1).  t ˆW EC (t) + h(t − τ )zˆ˙W EC (t)dτ + Gˆ zW EC (t) = Fexc (t), (1) (M + μ ¯add∞ )z¨ 0

where μ ¯add∞ is the infinite frequency added mass, h is the radiation impedance impulse response, G is the hydrostatic stiffness, fext is the excitation force and

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zˆW EC is the amplitude of motion of the system. The different effects of the PTO and generator are included as external damping and stiffness named DP T O and cP T O . Another common form of (1) is the frequency domain representation as shown in (2), − Ω 2 [M + μ ¯add (Ω)]ˆ zW EC (Ω) + jΩ [DP T O + γ¯r (Ω)] zˆW EC + [G + cP T O (Ω)] zˆW EC = Fˆexc (Ω),

(2)

where Ω is the wave frequency, μ ¯add is the added mass of water in the function of the wave frequency and γ¯r is the radiation damping. As can be seen many parameters depends on the wave frequency and in order to simplify this study only a regular wave with constant frequency is studied. Solving the equation of motion (2), the amplitude of motion zWˆEC for harmonic excitation results in zˆW EC =

[−Ω 2 (M

Fˆexc . +μ ¯add ) + G + cP T O ] + jΩ(¯ γr + DP T O )

(3)

If we think in a resistive control with its force and velocity always in phase, then the harvested power by the PTO PP T O can be written as PP T O =

DP T O Ω 2 |Fˆexc |2 1 . 2 [−Ω 2 (M + μ ¯add ) + G + cP T O ]2 − Ω 2 (¯ γr + DP T O )2

(4)

The hydrodynamic parameters of the WEC depicted in Fig. 1 are obtained with the software Ansys-AQWA (TM) for a wave period of 12 s determined above (See Table 1). Table 1. Lafkenewen WEC prototype properties. Parameter Definition

3

Value

μ ¯add

Added mass

11307.41 kg

Ω

Wave frequency

0.53 rad/s

γ¯r

Radiation damping 3086.11 Ns/m

M

WEC mass

G

hydrostatic stiffness 70979.06 N/m

4467.93 kg

Control Strategies

Control technology can impact many aspects of wave energy converters (WECs), including device sizing and configuration, maximizing energy extraction and optimizing energy conversion in the PTO system. The use of control engineering to optimize wave energy conversion was first proposed in the mid-1970s by

Model and Control Analysis for a Point Absorber

23

Budal and independently by Salter [13,14]. Numerous other control strategies have been implemented, being the most popular: optimal, phase, latching and predictive control. A comprehensive review of the different types of controllers can be found in [15]. In our study, a comparison of resistive, reactive and latching control is made for the wave energy converter named Lafkenewen considering its particular location. 3.1

Resisitive Control

In resistive damping control, excitation force and WEC velocity are kept proportional with the use of a constant controllable damping. The resistance of the PTO is obtained as FP T O = DP T O zˆ˙W EC .

(5)

The optimal damping DP T O−OP T can be obtained by maximizing (4) with respect to DP T O , resulting in    G 2 ¯add ) − DP T O−OP T = γ¯r + ω0 (M + μ . (6) ω0 In (4) it is assumed that cP T O = cmoor = 0. 3.2

Reactive Control

This control strategy is an extension of resistive control, where not only the damping is adjusted, but also the stiffness of the PTO. The PTO force is now obtained by (7) FP T O = DP T O zˆ˙W EC + cP T O zˆW EC . In this case the optimal damping and stiffness of the PTO are defined as: DP T O−OP T = γ¯r cP T O−OP T = 3.3

ω02 (M

+μ ¯add )

(8) (9)

Latching Control

Latching is a switching control, first proposed by Budal and Falnes [13] to enhance wave energy absorption by shifting the movement of the point absorber. It consists of locking the point absorber when the velocity goes to zero and unlocking it after a period of time TL , forcing the velocity to be in phase with the excitation force. This method can be applied by means of a mechanical brake or a valve (on a hydraulic PTO). The optimal latching time TL is calculated as follows Tw Tn − √ , (10) 2 2 1−ξ where Tw is the frequency of the wave, Tn and ξ are the natural frequency and the damping coeficient of the point absorber. TL =

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Results

Based on the parameters shown in Table 1 and Eq. (4), the average power is calculated for different values of the PTO damping. Results are compared in Fig. 2 for resistive control, latching control and reactive control. Additionally, the theoretical optimal power is depicted.

Fig. 2. Effect of PTO damping in different control strategies.

For the resistive control cP T O = 0, it can be seen that the optimal damping is effective DP T O−OP T as defined in (6). For reactive control, cP T O is defined according to (9), and it can be seen that the maximum power is found at the optimal damping defined in (8), which matches the theoretical optimal power. It is important to highlight that the optimal damping for latching control is close to the optimal damping for reactive control but not the same. This is due to the fact that latching control is a suboptimal control that tries to find resonance, but it is not able to do it completely. For reactive control, force and velocity are in phase. For latching control, these parameters are artificially in phase with the latching periods. For resistive control, there is always a delay between force and velocity. This is easily seen in Fig. 3, where the excitation force is shown in the same graph as the velocity of the WEC. In our work, the maximum power is highest for reactive control (18 kW) using a negative stiffness. In spite of that, it is difficult to add a negative stiffness to the PTO in practice. Moreover, a good model as well as a prediction of the future state of the waves are needed to adapt the PTO stiffness in real environments. Another important point is the displacement of the response of the system. It is 3 m from the equilibrium position, as shown in Fig. 4. This value is not realistic for the constraints of prototype Lafkenewen. On the other hand, Fig. 4 shows that the amplitude response fo latching control and resistive control are both below 1 m. Such amplitude is acceptable from our design point of view. If we compare the maximum average power of

Model and Control Analysis for a Point Absorber

25

Fig. 3. Force-velocity phase comparison for the three control strategies.

Fig. 4. WEC position vs time for the three control strategies.

both methods, 4 kW and 0.8 kW, respectively, we can see that latching control shows superior performance. Hence, it is the best option between the control strategies analyzed.

5

Conclusion

This work presents the classical linear modeling of a point absorber applied to a specific case. The parameters were obtained from the BEM model software Ansys-AQWA, and three different control strategies were studied from this model. The results show that reactive control can achieve the maximum average power of 18 kW but using a negative PTO stiffness and achieved displacement of ±3 m from the equilibrium. Latching control allows to achieve 4 kW of average

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power for a damping close but higher than the optimal found for reactive control (3086 Ns/m). However, displacements of the WEC are around ±1 m from the equilibrium position. Finally, resistive control allows 0.8 kW of average power using an optimal damping of 127340 Ns/m, which is 41 times the optimal damping for reactive control. In the future, a more detailed analysis can be made in order to include other design parameters, for example, the maximum PTO force, the type of PTO to be used and the structural analysis of the system to study, for example, maximum stresses or a fatigue analysis.

References 1. Cummins, W.: The impulse response function and ship motions. 9, 101–109 (1962) 2. United Nations Ensure access to affordable, reliable, sustainable and modern energy. https://www.un.org/sustainabledevelopment/energy/. Accessed 22 Dec 2022 3. Mork, G., Barstow, S., Kabuth, A.: Assessing the global wave energy potential. In: 29th International Conference on Ocean, Offshore and Arctic Engineering, ASMEDC, vol. 3, pp. 447–454 4. United States Energy Information Administration Electricity net consumption. https://www.eia.gov/international/data/world/electricity/electricity-consu mption. Accessed 22 Dec 2022 5. Shadman, M., Roldan-Carvajal, M., Pierart, F., et al.: A review of offshore renewable energy in South America: current status and future perspectives. Sustainability 15(2), 1740 (2023) 6. Hu, H., Xue, W., Jiang, P., Li, Y.: Bibliometric analysis for ocean renewable energy: an comprehensive review for hotspots, frontiers, and emerging trends. Renew. Sustain. Energy Rev. 167, 1–18 (2022) 7. Hansen, R., Kramer, M., Vidal, E.: Discrete displacement hydraulic power take-off system for the wavestar wave energy converter. Energy 6(8), 4001–4044 (2013) 8. Dalton, G.J., Alcorn, R., Lewis, T.: Case study feasibility analysis of the Pelamis wave energy convertor in Ireland. Port. N. Am. Renew. Energy 35(2), 443–455 (2010) 9. Kofoed, J.P., Frigaard, P., Friis-Madsen, E., Sorensen, H.C.: Prototype testing of the wave energy converter wave dragon. Renew. Energy 31(2), 181–189 (2006) 10. Pierart, F.G., Basoalto, C., Avila, M., Vega, M.: Dise˜ no y control de sistema de extracci´ on de potencia para generador undimotriz Lafkenewen. In: XX Jornadas de Mec´ anica Computacional, Valdivia, Chile 11. Wimalaratna, Y., Hassan, A., Afrouzi, H., Mehranzamir, K., et al.: Comprehensive review on the feasibility of developing wave energy as a renewable energy resource in Australia. Clean. Energy Syst. 3, 1–18 (2022) 12. Ahamed, R., McKee, K., Howard, I.: Advancements of wave energy converters based on power take off (PTO) systems: a review. Ocean Eng. 204, 107248 (2020) 13. Budal, K., Falnes, J.: Optimum operation of improved wave-power converter. Optimum operation of improved wave-power converter. Mar. Sci. Commun. 3, 133–150 (1977) 14. Salter, D.J., Taylor, J.: The architecture of nodding duck wave power generators. Nav. Archit. 21–24 (1976) 15. Ozkop, E., Altas, I.H.: Control, power and electrical components in wave energy conversion systems: a review of the technologies. Renew. Sustain. Energy Rev. 67, 106–115 (2017)

Novel Pseudo 3D Design of Solar Thermal Facades with Triangle and Trapeze Solar Thermal Collectors for Increased Architectural Acceptance Denisa Rusea , Macedon Moldovan(B)

, and Ion Visa

Renewable Energy Systems and Recycling Research Center, Transilvania University of Brasov, Brasov, Romania [email protected]

Abstract. A novel pseudo 3D design of solar thermal facades is presented in the paper based on triangle- and trapeze- solar thermal collectors developed in the Renewable Energy Systems and Recycling R&D Centre of the Transylvania University of Brasov, Romania aiming to improve their architectural acceptance and to provide affordable and clean energy, according to the SDG7 objective. Based on these two types of solar thermal collectors, all the subassemblies with two collectors of the same or different type having a common edge are identified in the paper, which become subsystems in the development of solar thermal facades. Combined with an enlarged range of colours (green, purple, brown, red, orange, yellow etc.) the subassemblies are used to develop pseudo 3D patterns to increase the attractiveness of these solar thermal facades. These subassemblies can be also used for the stylized representation of various images. Keywords: SDG7 · Sustainable Energy Systems · Triangle Solar Thermal Collector · Trapeze Solar Thermal Collector · Solar Thermal Façade · Architectural Acceptance

1 Introduction The renewable energy has begun to be used more and more in the last years as people starts to understand what Nearly Zero Energy Building means [1]. The 2010/31/EU Directive, mandatory from beginning of 2021 for all new buildings, imposes to use renewable energy in an efficient way [2]. Rapid advancing in the field of renewable energy is based on the important research findings as reviewed in [3] for renewable energy sources (RES) assessments, for systems and technologies exploiting RES to provide carbon-neutral energy in this energy transition period. This transition requires a multi-faceted focus, overcoming the research barriers and including research topics ranging from technology development via systems analyses to ownership and acceptance [4]. Solar thermal systems represent a viable solution especially when integrated in the building envelope [5]. Innovative solutions exist to compensate the variability of solar © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 27–36, 2023. https://doi.org/10.1007/978-3-031-32439-0_4

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energy based on active [6] and passive [7] thermal energy storage systems. The technologies exploiting renewable energy sources significantly contribute to the sustainable development of solar thermal and photovoltaic systems for individual and multifamily residential buildings [8]. When using solar energy to contribute to its thermal energy demand, the built environment faces a new challenge: the integration of the solar thermal system in the building envelope in such a way that it can achieve and even increase the architectural acceptance. Usually, the solar thermal collectors are implemented on the roof of the buildings or in its surrounding available spaces, to produce thermal energy for domestic hot water preparation and for space heating. The acceptance of solar systems integrated in the building envelope has many limitations in terms of aesthetic characteristic [9]. The major issues of regular solar thermal collectors’ integration in the built environment are related to their size, shape and dark colour (black or dark shades of blue). Developing new solar thermal collectors gives the possibility to implement them also in building facades, resulting solar thermal facades. Innovative solar thermal facades are currently investigated for water [10] and air [11] heating. To increase architectural acceptance, there were developed different shapes and colours of flat plate solar thermal collectors in the Renewable Energy Systems and Recycling Research Center of the Transylvania University of Brasov, Romania [12]. The triangle and trapeze shape of the solar thermal collectors and their small size give the possibility to create larger assemblies that architects can integrate in the building facades. By integrating the non-traditional solar thermal collectors on the southern facade of the buildings, the space heating energy demand may be reduced when the thickness of the building thermal insulation is increased with the thermal insulation of the solar thermal collectors [13]. The challenge to create harmonious design that fits the built environment remains. The advantages of the non-traditional shaped of reduced size solar thermal collectors compared to the regular solar thermal collectors having an absorber surface of about 2m2 are presented in [14] for trapeze solar thermal collectors with an absorber surface of 0.67 m2 and in [15] and [16] for triangle solar thermal collectors with an absorber surface of 0.06 m2 . Also, beside the small size, there is a variety of shapes that can be created by assembling small units [14]. Until now, there was studied only the interconnection between units of the same shape, but another challenge is to find various connections between parts of different shapes and to create an assembly: as example it was showed that three equilateral triangles form one isosceles trapeze [12]. A major advantage can be obtained when the non-traditionally shaped collectors are used to create subassemblies with different meanings or artistic effects. The highest ratings for Building Integrated Solar Thermal Systems (BISTS) were received when the solar thermal collectors also have a decorative role and fit to the appearance of the building [17]. An important fact is not just to match the shape with the building but also the colours and appearance of the glazing surface. For an aesthetic composition, the colour of the absorber plays an important role when assemblies are developed. The base colours (red, green and blue) are not enough to find the best combination of design for a large assembly. The colours were studied by both artistic and engineering point of view, and every colour has a different meaning by visual perception. While 80% of visual information is about the colours, it can lead

Novel Pseudo 3D Design of Solar Thermal Facades

29

to boredom, irritation or it can give a quiet or too dynamic sense, full of live. There can be created different textures only by using the correct colour combinations [18]. The light and the shades of a colour are elementary parts to create the illusion of depth and dimensionality, which at the end is just an illusion that does not happens accidentally [19]. The artistic way of combining the colours such that the final image is an illusion of a three-dimensional (3D) element can be applied also in BISTS, ant this will be the challenge of this paper. When such variety of colours and size of units can be developed in terms of solar thermal collectors, architectural integration and building of solar thermal facades become an attractive choice. If designers match the shapes and colours in order to create a harmonious combination then the architectural acceptance will no longer be a problem. This paper focuses on increasing architectural acceptance by creating combinations of shapes and colours of the new solar thermal collectors developed in R&D Centre of the Transylvania University of Brasov. The study takes in consideration the BISTS recommendations that have been established by architects and engineers from different European regions referring to: the solar thermal collectors should be considered as construction elements; the physical characteristics of the solar thermal collector fields like position/dimension/shape should be considered as an assembly, or as a whole; the colours of the solar thermal collectors should match the colours of the building; the size and the shapes should be also related to the building composition grids [20]. Nowadays, different artist give life to old buildings by painting them using different design and people show positive reactions regarding the murals. This mural art can be transposed by using novel types of coloured solar thermal collectors. The coloured solar thermal collectors have different efficiency depending of the colour of the absorber. As example, for triangle solar thermal collector the highest efficiency was obtained for black absorber (55.19%) followed by green (42.75%) and orange (35%) absorbers [15].

2 The Concept 2.1 Basic Subassemblies There are many possibilities to create solar thermal facades by using only triangle (t) or only trapeze (T) solar thermal collectors (Fig. 1), but such a design does not leave too much for interpretation. To increase the artistic effect, different subassemblies of these types of solar thermal collectors must be investigated. Further on, the sides of the triangle solar thermal collector are denoted with “s”, and in the case of trapeze solar thermal collector “S” is used for non-parallel sides, “B” for the long base and “b” for the short base (Fig. 1). To identify the possible subassemblies of triangle- and trapeze- solar thermal collectors the following combination are further investigated: two triangles (tt), two trapezes (TT) and one triangle combined with one trapeze (tT). To reduce the number of possible combinations, only the subassemblies with a common edge are considered. From these, the similar, rotated and mirrored subassemblies are excluded. In the case of two triangle solar thermal collectors (t1 and t2) arranged to have a common edge, a single option to create a subassembly exists as shown in Fig. 2a. There are many possible options to create subassemblies using two trapezes with a common edge, which is why the matrix shown in Fig. 2b was created to show the algorithm of

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Fig. 1. Solar thermal collectors of triangle and trapeze type.

choice. Thus, the first trapeze (T1) and the second trapeze (T2) may be arranged in nine possible positions, depending on the considered common edges. The codes included in Fig. 2b denote the common edges (e.g. bB means that the short base (b) of the first trapeze is common with the long base (B) of the second trapeze). These codes are further referred as concepts.

Edge of T1

TT

a)

b B S

Edge of T2 B S bB bS BB BS SB SS

b bb Bb Sb b)

Fig. 2. a) Subassembly “tt” of two triangle solar thermal collectors with a common edge; b) matrix of subassemblies of two trapeze solar thermal collectors with a common edge.

Based on the 9 possible concepts defined in Fig. 2b, 12 configurations can be obtained as shown in Fig. 3. Among these, similar pairs are found: bB and Bb, bS and Sb, BS and SB. Therefore, only eight unique arrangements of two trapezes with a common edge are further considered. Using the same algorithm, the subassemblies of one triangle and one trapeze with a common edge were designed by connecting a edge of the triangle (t) to each of the 3 edges of the trapeze (T) as shown in Fig. 4. 2.2 Pseudo Three-Dimensional Images According to Vukovic [21], people decide whether or not they like a product in 90 s or less and 90% of that decision is based only on colour. There are three primary colours: red, yellow, and blue which mixed create secondary colours. There are also two noncolours, black and white, that help to obtain shades (by adding black), tints (by adding white) or tones (by adding grey). Each colour involves a message, an emotion, suggests a feeling and influences the perception of the human eyes. The colour should also integrate in architecture; traditional solar thermal collectors have blue or dark colours that give a high contrast with white or grey colours usually used in the built environment. If there will be used different shapes of solar thermal collectors that can create different designs similar with a mural painting on facades, then colours are needed. The big contrast is given by complementary colours, they make the image pop, but their

Novel Pseudo 3D Design of Solar Thermal Facades

Edge of T1

TT

Edge of T2 B

b

31

S

b

bb similar with bB

bB

Bb

BB

bS

B BS1

BS2

similar with BS1, BS2

SS1

similar with bS S

Sb

SB1

SS2

SB2

Fig. 3. Subassemblies of two trapeze solar thermal collectors with a common edge.

Edge of t

tT

b

Edge of T B

S

s sb

sB

sS

Fig. 4. Solar thermal collectors of triangle and trapeze type.

repeatedly use can lead to tiring aspect. For a big impact, the pallet of colours used for solar thermal collectors must be enlarged. To this end, the effect of three-dimensional (3D) image can be created from simple two-dimensional (2D) images by using groups of solar thermal collectors of different shape and colours. To create a 3D image, lights and shadows should be added to the perspective design. The light should be placed where the designer wants to emphasize a contour from his design, and the opposite of the light should be the shadow. If this contrast is used correctly, the illusion of a 3D design can

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be visible from a simple 2D sketch. Not only the lines and the shapes are important in creating illusion of depth, but the colour also: warm colours (red, yellow etc.) create the illusion of closer object while cold colours (blue and its derived colours) give the impression of distance [22]. As example, if the faces of the white cube presented in Fig. 5a are coloured with different shades of the same colour (Fig. 5b), or with different colours for a higher contrast, like yellow vs blue and purple (Fig. 5c, 5d and 5e), the illusion of depth space is created. The highlighted face is the one that is closer to the imaginary source of light. For the cube in Fig. 5c the source of light is in front of the cube while in Fig. 5d the source of light is on top of the box and on right side in Fig. 5e. The depth illusion can be very simply created by using a light/warm colour near a darker/cold one. Usually the highest contrasts are formed by joining two complementary colours: red- green, yellow-purple and blue-orange. White or black can be added to create a more depth impression.

a)

b)

c)

d)

e)

Fig. 5. Depth illusion created by using shades and contrasted colours.

This concept can be integrated in the design of solar thermal facades, and some examples are presented in the following pictures. Figure 6a is showing an empty box, where the lightest color was used on the side walls made with yellow absorber, the terminator is black, and for the different shadow shades burgundy and green were used. In the same manner was created a 3D effect in Fig. 6b, where the illusion of 3D bricks is more visible. Here, the light was chosen on the upper side, the way that light and shadow is added on walls is changing the perspective of the design. But it should be remembered that here is not a 3D object, triangle and trapeze solar thermal collectors are combined in different subassemblies. This combination of lines and colours gives the illusion of a 3D object, but it only is a 2D design that can be easily integrated on a building. In Fig. 6c, contrasting colours orange and green were used on the sides of the empty rhombus to create a 3D illusion of an open window into a building wall. Figure 6d represents a column lighted from the left. A three floors pyramid is presented in Fig. 6e lighted from right top. The geometry helps in obtaining the 3D effect, the linear perspective means geometrical sets direct proportional that represent corners, edges, or surfaces of the designed object. The projection systems use one, two or three vanishing-points, depending on how the edges converge to one, two or three points. The proposed solar thermal collectors and their subassemblies make possible the creation of perspective using 2 vanishing points. Also the angles and dimensions support the 3D design, making the edges and the angles symmetrical. With a traditional solar thermal collector this illusion cannot be created.

Novel Pseudo 3D Design of Solar Thermal Facades

a)

c)

33

b)

d)

e)

Fig. 6. Pseudo 3D design based on subassemblies of triangle and trapeze collectors.

3 Applications The concept presented in Sect. 2 can be applied on different applications. As example, in the paper are included traditional design elements implemented in solar thermal facades and pseudo 3D solar thermal facades. 3.1 Traditional Design Elements Implemented in Solar Thermal Facades Traditional design elements exist and are a source of inspiration for exterior designers and architects; also they give people impression of welcome by feeling like grandmother house having traditional models painted on the walls. The models can be replicated with solar thermal collectors. Some concepts inspired from traditional models, using subassemblies described in previous section, are further presented. A traditional Spanish model (Fig. 7a) has been transposed using “sb” subassemblies and triangles presented in Fig. 7b in the solar thermal façade shown in Fig. 7c. An Italian traditional model (Fig. 8a) has been transposed using the subassemblies presented in Fig. 8b in the solar thermal façade shown in Fig. 8c. The traditional Romanian model (Fig. 9a) can be stylized combining “sb” (green outlined) and “ss” (blue outlined) subassemblies with one independent triangle- and two trapezes- and solar thermal collectors (Fig. 9b) as a solar thermal façade (Fig. 9c).

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a)

b)

c)

Fig. 7. Traditional Spanish model (a), subassemblies (b) and design transposed in solar thermal facades for buildings (c).

a)

b)

c)

Fig. 8. Traditional Italian model (a), subassembly (b) and design transposed in solar thermal facades for buildings (c).

a)

b)

c)

Fig. 9. Traditional Romanian model (a), subassemblies (b) and design transposed in solar thermal facades for buildings (c).

3.2 Pseudo 3D Solar Thermal Facades Implemented in Buildings To demonstrate the increased architectural acceptance of the proposed pseudo 3D design, a case study is presented for two commercial solar thermal collectors with a total surface of 4 m2 installed on the building facade to cover the thermal energy demand for domestic hot water (Fig. 10a). To supply the required amount of thermal energy, an increased surface of the novel solar thermal collectors is necessary due to their reduced efficiency caused by their lighter colours. As example, a pseudo 3D design based on triangle- and

Novel Pseudo 3D Design of Solar Thermal Facades

35

trapeze- solar thermal collectors is presented in Fig. 10b using “sb”, “sS” and “ss” subassemblies with a total surface of 7.6 m2 . These subassemblies will be preassembled in the factory to simplify the installation phases without limiting the artistic and architectural possibilities. Thus, even in the case of a thermal efficiency of the solar thermal collectors reduced by 50%, the thermal energy demand is covered and, additionally, the architectural acceptance is significantly increased.

a)

b)

Fig. 10. Regular (a) and pseudo 3D (b) solar thermal collectors on the building’s façade.

4 Conclusions The paper addresses the issue of the low architectural acceptance of the commercial solar thermal collectors implemented in the built environment. The main barriers are represented by the large size, rectangular shape and dark color. Novel triangle- and trapezesolar thermal collectors having small surfaces and various colours are considered. Based on the novel shapes (triangle and trapeze) of the solar thermal collectors considered as units, subassemblies are developed consisting of two collectors of the same type (two triangles, two trapeze) or different ones (a triangle and a trapeze) having a common edge. Only one subassembly was identified with two triangles, eight subassemblies with two trapeze and three subassemblies with a triangle and a trapeze. The use of these subassemblies, with different colours, in various combinations, creates the image of three-dimensional structures, with an essential effect on increasing the architectural acceptance. Examples of images formed with these subassemblies (parallelepiped, pyramid, box, columns and brick) are presented in the paper. Based on these subassemblies, configurations inspired from nature or from traditional symbols can be developed. Two applications are detailed in the paper. It is necessary to further model, simulate and experimentally validate the functional behaviour (fluid flow and thermal conversion efficiency) of the developed subassemblies. Acknowledgments. The infrastructure required for this work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation CNCS/CCCDI-UEFISCDI, project no. PN.III.P-2.2.1-PED-2016–0338, within PNCDI III.

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References 1. Attia, S., et al.: Overview and future challenges of nearly zero-energy building (nZEB) design in Eastern Europe. Energy Build. 267, 112165 (2022) 2. Parliament, E.: Directive 2010/31/EU of the European parliament and of the council of 19 May 2010 on the energy performance of buildings. Off. J. Eur. Union 53, 1 (2010) 3. Østergaard, P.A., Duic, N., Noorollahi, Y., Kalogirou, S.: Recent advances in renewable energy technology for the energy transition. Renew. Energy 179, 877–884 (2021) 4. Østergaard, P.A., Duic, N., Noorollahi, Y., Kalogirou, S.: Latest progress in sustainable development using renewable energy technology. Renew. Energy 162, 1554–1562 (2020) 5. Lamnatou, C., Chemisana, D., Mateus, R., Almeida, M.G., Silva, S.M.: Review and perspectives on Life Cycle Analysis of solar technologies with emphasis on building-integrated solar thermal systems. Renew. Energy 75, 833–846 (2015) 6. Navarro L., et al.: Thermal energy storage in building integrated thermal systems: a review. Part 1: Act. Storage Syst. Renew. Energy 88, 526–547 (2016) 7. Navarro L., et al.: Thermal energy storage in building integrated thermal systems: a review. Part 2. Integr. Passive Syst. Renew. Energy 85, 1334–1356 (2016) 8. Østergaard, P.A., Duic, N., Noorollahi, Y., Mikulcic, H., Kalogirou, S.: Sustainable development using renewable energy technology. Renew. Energy 146, 2430–2437 (2020) 9. Schüler, A., Roecker, C., Boudaden, J., Oelhafen, P., Scartezzini, J.L.: Coatings for colored glazed thermal solar collectors and solar active glass facades. In: CISBAT (2003) 10. Buonomano, A., Forzano, C., Kalogirou, S.A., Palombo, A.: Building-façade integrated solar thermal collectors: energy-economic performance and indoor comfort simulation model of a water based prototype for heating, cooling, and DHW production. Renew. Energy 137, 20–36 (2019) 11. Agathokleous, R., Barone, G., Buonomano, A., Forzano, C., Kalogirou, S.A., Palombo, A.: Building façade integrated solar thermal collectors for air heating: experimentation, modelling and applications. Appl. Energy 239, 658–679 (2019) 12. Visa, I., Comsit, M., Duta, A.: Urban acceptance of facade integrated novel solar thermal collectors. Energy Procedia 48, 1429–1435 (2014) 13. Moldovan, M., Visa, I., Rusea, I.D.: The influence of the solar thermal collectors integrated into the building facade on the building thermal energy demand across Europe. J. Sci. Art 1(50), 203–214 (2020) 14. Visa, I., Moldovan, M., Comsit, M., Neagoe, M., Duta, A.: Facades integrated solar-thermal collectors – challenges and solutions. Energy Procedia 112, 176–185 (2017) 15. Visa, I., Moldovan, M., Duta, A.: Novel triangle flat plate solar thermal collector for facades integration. Renew. Energy 143, 252–262 (2019) 16. Moldovan, M., Rusea, I., Visa, I.: Optimising the thickness of the water layer in a triangle solar thermal collector. Renew. Energy 173, 381–388 (2021) 17. Munari Probst, M.C., Roecker, C.: Towards an improved architectural quality of building integrated solar thermal systems (BIST). Sol. Energy 81, 1104–1116 (2007) 18. Barbur, J.L., Spang, K.: Colour constancy and conscious perception of changes of illuminant. Neuropsychologia 46, 853–863 (2008) 19. Jackman, J.: Lighting for Digital Video and Television (Third Edition). In: Chapter 6 - Basic Lighting Techniques, pp. 91–107 (2010) 20. Kalogirou, S.: Building Integrated Solar Thermal Systems, BISTS – Design and Applications Handbook. COST Action TU1205 (2017) 21. Vukovic, P.: The fundamentals of understanding color theory (2012) 22. Wenham, M.: Understanding Art: A Guide for Teachers. SAGE, California (2003)

Fast Frequency-Domain Based Tool for FOWT Platforms Preliminary Design Mar´ıa Alonso-Reig1,2(B) , I˜ nigo Mendikoa1 , and Victor Petuya2 1

Tecnalia Basque Research and Technology Alliance (BRTA), Derio, Spain [email protected] 2 University of the Basque Country (UVP/EHU), Bilbao, Spain

Abstract. An efficient frequency-domain numerical tool for the preliminary design of the floating offshore wind substructures is developed and validated against a time-domain state-of-the-art method. The tool is based on an existing simplified frequency-domain response model that has been improved through the coupling of two developed modules that perform an efficient hydrodynamic analysis compared to the radiationdiffraction analysis. The first module estimates the linear hydrodynamic coefficients by means of interpolation functions and the second module calculates the second-order hydrodynamic loads based on the Morison and Rainey force models. Both modules have been validated with radiation-diffraction analysis. The proposed tool enables a fast comparative analysis between many floater designs for a given wind turbine and identifies 1000 times faster than the state-of-the-art methods those that meet the predefined requirements. Keywords: Affordable and Clean Energy · Climate Action · Floating offshore wind · Semi-submersible Platform · Preliminary Design · Hydrodynamic Loads

1

Introduction

Since the last years, there is a worldwide commitment to climate change mitigation through the reduction of the greenhouse gas emissions. This can be achieved by means of increasing the deployment of renewable energy technologies [9]. Among the renewables, Floating Offshore Wind (FOW) is showing significant interest due to its numerous advantages such as easier installation process and the wider site availability. The FOW industry is currently at an early stage and there is already a large diversity of floating concepts, which hampers the achievement of high technology readiness levels [6]. Consequently, the floating foundations are yet the cost drivers of the FOW structures, thus technology optimisation is one of the keys to achieve its cost reduction. In the pre-design stages, many platform designs are analysed and, therefore, a large number of simulations need to be performed. This process can be very time consuming and as an alternative to the high computational cost demanded c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 37–44, 2023. https://doi.org/10.1007/978-3-031-32439-0_5

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by the time-domain (TD) analyses, usually frequency-domain (FD) numerical approaches are used to evaluate the FOW structures response. However, many inputs on the FD methods are obtained by means of other software that require high computational effort, and thus, make the whole design process less efficient [2,5,8]. For this reason, we have identify the potential improvements of these FD methods and developed the required modules to make the pre-design process more cost-effective in computational terms. Since the present work is focused on the FOW substructures design, we have developed two standalone modules that estimate the first and second-order hydrodynamic coefficients with significantly lower computational effort than the required in radiation-diffraction analysis. The two units coupled with the FD response model enable the acceleration of the pre-design process and, thus, makes it feasible to analyse a great number of platform designs. For the validation of the design tool the OpenFAST numerical method has been used [4].

2

Fast Design Tool

The present design tool for FOW substructures is composed of a simplified FD response model that accounts for the coupled wind turbine, floating platform and station keeping system sub-models. The aerodynamic sub-model is generated using OpenFAST [4] and the mooring system is represented by a matrix. The hydrodynamic sub-model is one of the novelties presented in this work and are described in detail in Sect. 2.2 and Sect. 2.3. 2.1

Simplified Response Model

The equation of motion in FD for a single degree of freedom (DOF) system is given in (1). ˆ ξ(ω) =

−ω 2

Fˆ (ω) , m + iωb + c

(1)

ˆ where ξ(ω) is the response, Fˆ (ω) is the excitation force, ω is the angular frequency, m is the system mass, and b and c are the damping and restoring coefficients, respectively. The response model used was developed by A. Pegalajar-Jurado et al. [2], it is known as QuLAF and consists of a 4 DOF planar model (see red arrows in Fig. 1), considering the surge (ξ1 ), heave (ξ3 ) and pitch (ξ5 ) motions and the first tower fore-aft (FA) mode shape deflection (δ) (see Fig. 1). The platform is considered a rigid body, the rotor and nacelle assembly a concentrated mass, the tower is flexible and the mooring system is represented by a stiffness matrix.

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Fig. 1. Simplified FOWT model. Figure from [2].

The system is subjected to aligned wave and wind, thus the total force in (1) would be the sum of the aerodynamic loads and the first- and second-order hydrodynamic loads. (1) (2) Fˆ (ω) = Fˆaero (ω) + Fˆhydro (ω) + Fˆhydro (ω)

(2)

The system mass is the sum of the structural mass and the hydrodynamic added mass. The restoring matrix accounts for the structural stiffness, hydrostatic stiffness and mooring stiffness. The damping matrix of the system is composed of the structural damping of the tower, the radiation and viscous damping of the platform and the aerodynamic damping. A more detailed description can be found in [2]. 2.2

Linear Hydrodynamic Coefficient Estimation Methodology

Herein, the first module that has been developed in order to efficiently obtain the linear hydrodynamic coefficients is described. The usual way to calculate the linear hydrodynamic coefficients is through radiation-diffraction analysis by means of a panel code. However, these software often require license and a high computational effort for large structures. The frequency-dependant radiation coefficients are the added mass, A(ω), and the radiation damping, Brad (ω), matrices. The diffraction excitation load, X(ω), is composed of an amplitude and a phase for each frequency value and is defined by the load per unit of wave amplitude. The proposed methodology is based on the estimation of the hydrodynamic coefficients of simple geometries through interpolation and scaling. The interpolation is performed using the data from a small data-based previously built from radiation-diffraction analyses. The computational effort required to set the data-base compensates the numerous designs that can be analysed using the

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stocked data afterwards. The semi-submersible floater is split into simple members, such as columns and horizontal prisms, and the hydrodynamic coefficients of each member is predicted separately. Then, superposition is applied, referring the phases and moments to the point of flotation of the structure. 2.3

Accelerated Method for the Second-Order Hydrodynamic Load Calculation

In this section the module for the calculation of the second-order hydrodynamic loads at linear cost is explained. It was originally developed and validated by H. Bredmose and A. Pegalajar for the surge force and pitch moment on a monopile and a spar in [3] and [7], respectively. This method is based on the Morison and Rainey force models, assuming slender-body theory. We have extended the method to implement it to a full semi-submersible floater [1]. To this end, the platform is split into simple geometries that can be, to some extent, considered slender. Then, the second-order loads for each of the members are predicted and superposition is applied afterwards. This can be done provided the interaction between the members has negligible effect. The loads are validated against the radiation-diffraction results. The second-order hydrodynamic loads are expressed through the Morison and Rainey force models, which are based on the slender-body approach. F (2) = (Cm + 1)i

N N   m

ˆm B ˆn ei((ωm +ωn )t−(km +kn )x) F , B

(3)

n

ˆ is the wave amplitude, ω the where N is the size of the frequency array, B angular wave frequency, k the wave number, and F is the QTF derived from the Morison and Rainey force model. This QTF is symmetric and real, thus it can be decomposed in eigenvalues, λj , and eigenvectors, Vj , where j corresponds to each mode. The equation above then can be rewritten as in (4). ⎡ F (2) = i

2N  j

=i

2N  q=1

.. .

⎤

⎢ ⎥   ˆ i(ωn t−kn x) ⎥ , ˆm ei(ωm t−km x) · · · Vj λj Vj ⎢B ··· B ⎣ ne ⎦ .. . λq

  N

ˆm ei(ωm t−km x) Vqm B

(4)

2 .

(5)

m=−N

This matrix product results in the product of two identical pseudo time series and (5) results in the core equation of the accelerated method presented in this work, where q corresponds to each of the mode shapes.

Fast Frequency-Domain Based Tool for FOWT Platforms

41

In Fig. 2 the scheme of the design tool with each of the modules is shown.

Fig. 2. Scheme of the fast Design Tool and its modules.

3

Case Study

(a)

(b)

Fig. 3. (a) LIFES50+ floating offshore wind turbine. Figure from [10]. (b) Submerged section of the platform split into simple members.

The FOWT used as the basis is the DTU 10 MW WT with the Nautilus semisubmersible floater from LIFES50+ project [10]. The Nautilus floater has served as a reference platform where some parameters have been modified in order to

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make the comparative analysis of several designs. The parameters that have been modified are the column diameters, D, the distance between the column vertical axis, s, and the draft of the floater, d. The pontoon width is set to the column diameter size and also the pontoon length is defined by the distance between the columnns and the diameter. Ten different platform designs have been compared. In Table 1 the dimensions corresponding to each of them are given. The steel mass, M , of the platform is also given (Table 1).

Table 1. Case study platforms parameters. D1

D2

D3

D4

D5

D6

D7

D8

D9

D10

D (m)

10

10

10

10

13

13

13

15

15

15

s (m)

50

55

60

70

40

50

60

50

60

70

d (m)

15.33 15.53 15.73 16.12 11.13 11.43 11.74 11.14 11.40 11.67

Mass (tn) 2.36

2.44

2.51

2.65

3.15

3.34

3.53

4.94

5.16

5.38

The case studies have been subjected to several combinations of sea states and wind speed, covering a wide range of environmental conditions. The results shown in Sect. 4 correspond to the most critical case with 22 m/s mean wind speed at hub height and irregular wave of Hs = 6.2 m and Tp = 12.5 s.

4

Results and Discussion

In this section the results obtained for the different platform designs are discussed. The disagreements expected in the results of the present tool are related partly due to the differences with respect to radiation-diffraction analysis; and partly to the differences with the time-domain simulations. For this reason, in Fig. 4 three signals are compared: the response obtained with the present design tool (F Dnew ), the response obtained through the response model in Sect. 2.1 feed with the hydrodynamic data from radiation-diffraction analysis (F Drad/dif f ), and the response from the OpenFAST numerical tool. The pitch angle shows generally very good agreement between F Dnew and F Drad/dif f , and slightly more differences with OpenF AST . This means that the developed modules provide a maximum pitch angle similar to that using the radiation-diffraction analysis coefficients. The under-prediction of both signals from FD methods could be expected, since the FD doesn’t account for transitory leading to possible underestimation of peaks. The designs D1 and D5 are discarded in this preliminary design phase by both methods. There is only one of the designs that using the TD one should discard it, whereas both FD tool accepts it. In view of these results, one can set more conservative threshold values for the analyses with FD tools in order to avoid taking to the next design stages platform designs that the TD methods would have discarded.

Fast Frequency-Domain Based Tool for FOWT Platforms

43

(a)

(b)

Fig. 4. Maximum response for the different designs. (a) Platform pitch displacement (deg). (b) Nacelle acceleration (m/s2 ).

As for the nacelle acceleration, FD generally under-predicts the response but this time some more differences can be found among both FD signals, which are related to the accuracy on the estimation of the phases of the hydrodynamic excitation loads. The acceleration is the second derivative of the nacelle deflection and, thus, it is reasonable to have more noticeable differences between both FD signals. Despite this fact, the design tool still enables to identify most of the designs that overpass the threshold, especially those with the highest acceleration values which could be the most critical ones. Nevertheless, D4 and D8 are discarded by F Drad/dif f and TD but our design tool would accept them. Taking into account both the pitch angle and the nacelle acceleration, the designs that best behave are the D3 and D6, meeting the two design requirements. Among these two designs, the most cost-effective one is the D3 with a platform steel mass of 2.51 tn. This conclusion is the same using the FD tool or the TD tool, therefore, the proposed modules allow to efficiently estimate the

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response of the FOWT and identify the most cost-effective designs that best behave under different metocean conditions. The great advantage of this method is the low computational cost required. The comparative analysis performed for this study was performed 1000 times faster than the conventional methods. Although some accuracy is lost, it has shown to agree reasonably well for a preliminary design phase.

5

Conclusions

In this research, a new efficient frequency-domain based method has been carried out that, with the main focus on the floating offshore wind substructures’ design, consists of the coupling of the response model and two novel methods that predict the hydrodynamic radiation coefficients and first- and second-order hydrodynamic loads with lower computational cost than the conventional radiationdiffraction analyses. The tool enables a fast comparative analysis of different platform designs, discard the ones that don’t meet some predefined thresholds and identify the most cost-effective ones, achieving the same conclusions as if the state-of-the-art numerical methods were used. The tool is validated with the NREL open source code OpenFAST and has shown to be 1000 times faster. The results obtained through the present efficient design tool has shown to agree very well with the time-domain analysis.

References 1. Alonso-Reig, M., Pegalajar-Jurado, A., Mendikoa, I., Petuya, V., Bredmose, H.: Accelerated second-order hydrodynamic load calculation on semi-submersible floaters. Mar. Struct. (2023) 2. Bredmose, H., Pegalajar-Jurado, A.: An efficient frequency-domain model for quick load analysis of floating offshore wind turbines 3(2), 693–712 (2018) 3. Bredmose, H., Pegalajar-Jurado, A.: Second-order monopile wave loads at linear cost 170, 103952 (2021) 4. Jonkman, J.M.S.: OpenFAST: an open source wind turbine simulation tool. NREL 5. Karimi, M., Buckham, B., Crawford, C.: A fully coupled frequency domain model for floating offshore wind turbines. J. Ocean Eng. Mar. Energy 5(2), 135–158 (2019). https://doi.org/10.1007/s40722-019-00134-x 6. Leimeister, M., Kolios, A., Collu, M.: Critical review of floating support structures for offshore wind farm deployment. In: Journal of Physics: Conference Series, vol. 1104, p. 012007. IOP Publishing (2018) 7. Pegalajar-Jurado, A., Bredmose, H.: Accelerated hydrodynamic analysis for spar buoys with second-order wave excitation. In: International Conference on Offshore Mechanics and Arctic Engineering, vol. 84416, p. V009T09A067 (2020) 8. Riste, K.B.: Development of a Frequency-domain Model for Dynamic Analysis of the Floating Wind Turbine Concept-WindFloat. Master’s thesis, NTNU (2016) 9. WindEurope: Getting fit for 55 and set for 2050 (2021) 10. Yu, W., et al.: Public definition of the two lifes50+ 10mw floater concepts. LIFES50+ Deliver. 4 (2017)

Robotics and Mechatronics

A Framework for Improving the Energy Efficiency and Sustainability of Collaborative Robots Paolo Boscariol1 , Enrico Clochiatti2 , Lorenzo Scalera2(B) , and Alessandro Gasparetto2 1

DTG, Universit` a degli Studi di Padova, Vicenza, Italy DPIA, Universit` a degli Studi di Udine, Udine, Italy [email protected]

2

Abstract. On a worldwide scale, industry is responsible for a large part for the overall use of energy and resources: reducing this use is included in the targets of SDG9, one of the Sustainable Development Goals drawn by the United Nations. This work aims to create a framework for better understanding, modelling, and optimizing the energy consumption of industrial robots, with specific reference to the collaborative robot UR5e. The framework comprises a real robot and its electro-dynamic model, the latter being developed on the basis of experimental tests and of data supplied by the manufacturer. The paper presents the main features of the framework, and the future work aimed at improving the accuracy of the proposed energy model. Keywords: SDG9 · SDG12 collaborative robot · UR5e

1

· energy efficiency · model identification ·

Introduction

The operation of industrial robots has been traditionally aimed at maximizing productivity, hence by reducing the time needed to complete a work cycle. This practice, however, does not take into account the energy consumption per cycle, whose optimization brings potential economic saving, as well as a clear reduction of the energy efficiency of the production facility. The impact of power consumption of industrial robots and automatic machines is not to be underestimated, as it has been shown that electric motors are responsible for up to 70% of the total energy consumed in industry [1,2]. The importance of improving the energy efficiency in industry is clearly outlined in the SDG9 and SDG12, two of the Sustainable Development Goals formulated in 2015 by the United Nations General Assembly. In particular, the SDG9 at target 4 reads as: “By 2030, upgrade infrastructure and retrofit industries to c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 47–54, 2023. https://doi.org/10.1007/978-3-031-32439-0_6

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make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies and industrial processes, with all countries taking action in accordance with their respective capabilities”. In most cases, industrial robots are programmed to execute mainly motion tasks, hence their performances are largely dictated by the strategy used to plan their trajectories. Therefore, motion planning has largely been investigated as one of the most effective way of boosting the capabilities of robotic systems, leading to an extensive literature [3]. Traditionally, the literature on trajectory planning has focused on the minimization of execution times [4,5], on vibration reduction for improved motion accuracy [6,7], and only more recently, on energy saving [8–10]. Using motion planning as a tool to enhance energy efficiency is indeed a very sound option in industry, as it does not require any hardware modification to an existing infrastructure, as in [11], being obtainable just by altering the software that handles the robotic operation. Modifying the motion profile of an existing robotic cell is not only ‘simple’, but also potentially rewarding, as energy efficiency improvements up to 33% are cited, as in [12]. This paper is aimed at presenting the current and the future development of an hardware/software framework that is a tool to investigate, model and optimize the energy consumption of industrial robots. In particular, the investigation is targeted on the robot UR5 e-Series, produced by Universal Robots [13]. The choice of this robot is motivated by several factors: first of all, it is a device of large use in industry, as well as in education and in research facilities. Moreover, the architecture of the UR5e robot is shared not only with other manipulators produced by the same manufacturers, but with other robot fabricators. Indeed, many collaborative robots are designed, like the UR5e, to be lightweight, to carry small to medium payloads, to use brushless motor of reduced size and strain wave gear reduction. In the next sections, the dynamic and electric model are outlined, showing the first implementation of the setup used to validate and test the simulator that allows to predict the energy absorption during the execution of a motion task.

2

Energy Modelling of a Collaborative Robot

The estimation of the electric energy consumption of a robot can be conducted through the detailed analysis and use of its dynamic model, which should take into account both a mechanical dynamic model and an electric model. Let us first investigate the mechanical model, which can be formulated, according to the most common procedure, by using the Lagrange formalism as: ˙ q˙ + Ff + g(q) = τ − JT (q)h q + C(q, q) M(q)¨

(1)

Equation (1) includes the position-dependant mass matrix M, which is a func˙ accounts for the tion of the vector of the joint coordinates q. Matrix C(q, q) centrifugal and Coriolis effects, whereas g(q) accounts for the effects of gravity on the manipulator. τ is the vector of the joint torques, and h collects the forces

A Framework for Energy Efficiency of Robots

49

and moments acting on the end-effector, which are weighted by the robot Jacobian matrix J. Finally, the dissipative action due to friction is included in the friction torque vector Ff . Friction torques are included in the formulation of Eq. (1) by means of a general expression, with the specific aim of implementing one of the many friction models that have been developed for describing harmonic drives, which are the main source of friction dissipation in the setup under consideration [14]. As a preliminary result, the experimental data gathered for this work has shown that a rather good approximation of Ff can be obtained by setting Coulomb friction forces as the dominant source of friction torque in the reducers, while friction in motors is modeled also according to a viscous friction effect. In both cases, the discontinuity of the theoretical Coulomb model is avoided by the hyperbolic tangent smoothing approach [15]. This model has been motivated in the work [16], through the analysis of the manufacturers’ technical sheets. The estimated friction parameters are reported in Table 1: Coulomb friction torque is identified by TC , with the superscript m indicating the motor and the superscript r indicating the reducer, whereas the viscous friction coefficient acting on the motor shaft is represented by fvm . Table 1. Estimated friction parameters from [16]. Joint k fvm [N ms/rad] TCm [N m] TCr [N m] 1:3 4:6

6.6 · 10−5

7.4 · 10−2 0.069

−5

3.4 · 10−2 0.029

3.4 · 10

Equation (1) is of paramount importance for the estimation of the energy consumption of a manipulator, as it can be used as an inverse dynamic model to estimate the joint torques to be generated to exert the required speeds and accelerations, as well as to balance eventual external forces and gravity. By applying Eq. (1) to the whole time frame that records the robot performing a task, it is possible to estimate both the instantaneous mechanical power required by the task, as well as the mechanical energy expenditure associated with the task, after time integration. However, the energy dissipation operated by friction forces is not the only one to be accounted for when computing an energy balance of the robot, as also the electric energy dissipation in the actuators significantly concurs in estimating the overall energy losses. As such, the mechanical model of Eq. (1) must be complemented by an electric model, which relates the speed and torque generation with the electric power absorption for each electric motor of the robot. Brushless motors can effectively be modeled using the Clarke-Park transform as equivalent DC motors, which use the torque constant kt , the back-emf constant kb and the winding resistance R to relate current i, voltage drop V , speed ωm , and torque τm as:

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τm (t) = kt i(t) V (t) = R i(t) + kb ωm (t)

(2)

The coefficients kt , kb and R can either be measured, gathered form technical sheets [16], or from experimental data [17], according to the available information. The two approaches have been combined to estimate the parameters used in the robot simulator: a detailed description of the developed procedure is here omitted to comply with the space limitations of the manuscript. Equation (2) provides both the current and the voltage drop across the motor leads: their product describes the instantaneous power absorption Wm (t) = V (t) i(t), which, through time integration, provides an estimation of the energy consumption associated with the execution of a task. Thus, it is possible to relate to it an energy figure, which can then be the subject of additional analysis and improvement through thoughtful motion planning. In the next section, the main features of the setup used to tune and preliminary validate the energy model of the UR5e robot are described.

3

Experimental Results

The experimental setup, which has been used to guide the development of the energy model of the UR5e robot, is based on a minimal hardware configuration. The hardware setup requires just the robot (Fig. 1) and a computer that interfaces with the robot controller to define the robot motion and to log the experimental data during the robot operation. The control of the robot, as well

Fig. 1. The experimental setup.

A Framework for Energy Efficiency of Robots

51

as the data logging, is performed through ROS Melodic Morenia and Python 3.6. The communication between the robot and the PC running ROS is performed through a TCP/IP connection. The setup does not include any additional sensors or devices other than the bare minimum: the data used to drive the model identification and to validate the model has to rely only on data made available by the robot controller. The latter supports the so-called Real-Time Data Exchange (RTDE) interface, which can be used to establish a real-time two-directional communication between the robot and the supervisor/datalogger computer over a bus at 500 Hz. Actual and reference joint position, velocities, accelerations, as well as reference torques and actual motor currents can be retrieved from the robot controller. The kinematic state of the robot can be fed to the energy model defined in Sect. 2 to estimate actual joint torques, motor current and voltages, from which the electric power absorption by each motor can be assessed and the overall energy expenditure associated with the execution of a task can be evaluated. The first part of the model to be tuned is the mechanical model of Eq. (1), for which the inertial parameters have yet to be discussed. The analysis of the data collected by executing several motion tasks have shown that the inertial parameters provided by the robot manufacturer, which are also reported in Table 2, provide a sufficiently accurate description of the robot dynamics. The latter can be improved even more by including also the moments of inertia of the motors and of the reducers, again according to the data presented in [16]. 100

40

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20

0

0

-50 -20

0

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1

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-2 0

-4 -6

-20 0

1

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0

0

-2

0

1

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-2

Fig. 2. Dynamic model validation: measured vs. computed joint torques.

52

P. Boscariol et al. Table 2. Estimated inertial parameters from [16]. Joint k mi [kg] Center of mass pos. [m] Jm [kg m2 ] Jr [kg m2 ] 1 2 3

3.7 8.393 2.33

[0, −0.02561, 0.00193] [0.2125, 0, 0.11336] [0.15, 0.0, 0.0265]

8.8 · 10−5 8.8 · 10−5 8.8 · 10−5

1.07 · 10−4 1.07 · 10−4 1.07 · 10−4

4 5 6

1.219 1.219 0.1879

[0, −0.0018, 0.01634] [0, 0.0018, 0.01634] [0, 0, −0.001159]

2 · 10−5 2 · 10−5 2 · 10−5

0.19 · 10−4 0.19 · 10−4 0.19 · 10−4

40 40 20

20 0

0 0

1

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20 4 10

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0 0

0 1

2

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0

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0

0

0

1

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Fig. 3. Estimated motor electric power consumption.

The good accuracy of the proposed model is supported by the data presented in Fig. 2, which compares the estimated joint torques provided by the robot controller with the one obtained by solving Eq. (1). The two traces overlap almost perfectly, showing a very good agreement between the theoretical model and the behavior of the real manipulator. The electric power absorption for the six actuators (Fig. 3) can then be computed for the same trajectory from the torque estimations together with Eq. (2). The resulting power signals, summed and integrated over time, provide the energy consumption that is shown in Fig. 4 divided in the inertial, friction, and gravity contributions. The preliminary results presented in this work have been validated with other trajectories as well, showing overall a good agreement with the data collected

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Fig. 4. Estimated electric energy consumption over time.

during several experimental trials. The final goal of this work has been not yet reached, since some other details of the dynamic and electro-mechanic model are yet to be defined for a complete validation. In particular, the aim of the authors is to incorporate into the model the thermal effects, as it has been shown [18,19] that the energy consumption generally decreases as the whole robot gets warmer. Our aim is to investigate how temperature affects not only friction effects, but also the efficiency of the motors in generating mechanical power, which is expected given that the properties of conductive materials are generally sensitive to temperature changes.

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Conclusion

In this work the initial development of a testbench for accurately estimating the power consumption of the collaborative robot UR5e has been presented. The proposed model makes use of a combination of nominal parameters provided by the manufacturer, as well as some other data extracted from technical data sheets and available in the literature. The dynamic model has been validated, and complemented with an electric model which describes the electric power absorption by the six brushless motors that move the robot. In order to increase the energy efficiency and sustainability of the industrial applications that use the UR5e robot, future work will focus on refining the model to include the explicit temperature dependence on friction parameters, and on using the model to plan real energy-optimal motion profiles.

References 1. Shyi-Min, L.: A review of high-efficiency motors: specification, policy, and technology. Renew. Sustain. Energy Rev. 59, 1–12 (2016)

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2. De Almeida, A., Fong, J., Brunner, C.U., Werle, R., Van Werkhoven, M.: New technology trends and policy needs in energy efficient motor systems-a major opportunity for energy and carbon savings. Renew. Sustain. Energy Rev. 115, 109384 (2019) 3. Gasparetto, A., Boscariol, P., Lanzutti, A., Vidoni, R.: Path planning and trajectory planning algorithms: a general overview. In: Carbone, G., Gomez-Bravo, F. (eds.) Motion and Operation Planning of Robotic Systems. MMS, vol. 29, pp. 3–27. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-14705-5 1 4. Piazzi, A., Visioli, A.: Global minimum-time trajectory planning of mechanical manipulators using interval analysis. Int. J. Contr. 71(4), 631–652 (1998) 5. Shen, P., Zhang, X., Fang, Y.: Complete and time-optimal path-constrained trajectory planning with torque and velocity constraints: theory and applications. IEEE/ASME Trans. Mechatron. 23(2), 735–746 (2018) 6. Barre, P.-J., Bearee, R., Borne, P., Dumetz, E.: Influence of a jerk controlled movement law on the vibratory behaviour of high-dynamics systems. J. Int. Rob. Syst. 42(3), 275–293 (2005) 7. Biagiotti, L., Melchiorri, C., Moriello, L.: Optimal trajectories for vibration reduction based on exponential filters. IEEE Trans. Control Syst. Technol. 24(2), 609– 622 (2015) 8. Carabin, G., Wehrle, E., Vidoni, R.: A review on energy-saving optimization methods for robotic and automatic systems. Robotics 6(4), 39 (2017) 9. Meike, D., Ribickis, L.: Recuperated energy savings potential and approaches in industrial robotics. In: 2011 IEEE International Conference on Automation Science and Engineering, pp. 299–303. IEEE (2011) 10. Carabin, G., Scalera, L.: On the trajectory planning for energy efficiency in industrial robotic systems. Robotics 9(4), 89 (2020) 11. Carabin, G., Scalera, L., Wongratanaphisan, T., Vidoni, R.: An energy-efficient approach for 3D printing with a Linear Delta Robot equipped with optimal springs. Rob. Comput.-Int. Manuf. 67, 102045 (2021) 12. Park, J.S.: Motion profile planning of repetitive point-to-point control for maximum energy conversion efficiency under acceleration conditions. Mechatronics 6(6), 649–663 (1996) 13. Universal robot UR5e. https://www.universal-robots.com 14. Lee, S.-D., Song, J.-B.: Sensorless collision detection based on friction model for a robot manipulator. Int. J. Precis. Eng. Manuf. 17(1), 11–17 (2016). https://doi. org/10.1007/s12541-016-0002-3 15. Duan, C., Singh, R.: Dynamics of a 3 DoF torsional system with a dry friction controlled path. J. Sound Vibr. 289(4–5), 657–688 (2006) 16. Boscariol, P., Caracciolo, R., Richiedei, D., Trevisani, A.: Energy optimization of functionally redundant robots through motion design. Appl. Sci. 10(9), 3022 (2020) 17. Boscariol, P., Richiedei, D.: Energy optimal design of servo-actuated systems: a concurrent approach based on scaling rules. Renew. Sustain. Energy Rev. 156, 111923 (2022) 18. Eggers, K., Kn¨ ochelmann, E., Tappe, S., Ortmaier, T.: Modeling and experimental validation of the influence of robot temperature on its energy consumption. In: 2018 IEEE IEEE International Conference on Industrial Technology (ICIT), pp. 239–243 (2018) 19. Raviola, A., Guida, R., De Martin, A., Pastorelli, S., Mauro, S., Sorli, M.: Effects of temperature and mounting configuration on the dynamic parameters identification of industrial robots. Robotics 10(3), 83 (2021)

Modeling and Parametric Analysis of Quasi-Translational Parallel Continuum Manipulators Luigi Tagliavini1(B) , Oscar Altuzarra2 , Giuseppe Quaglia1 , and V´ıctor Petuya2 1

DIMEAS, Politecnico di Torino, Corso Duca degli Abruzzi, 24, Torino, Italy {luigi.tagliavini,giuseppe.quaglia}@polito.it 2 Department of Mechanical Engineering, University of the Basque Country UPV/EHU, 48013 Bilbao, Spain {oscar.altuzarra,victor.petuya}@ehu.es

Abstract. Translational Parallel Manipulators proved to be effective mechanisms in different application fields, from industries to haptic devices. The introduction of intrinsic flexibility within these mechanisms looks promising at increasing the safety of robots that are adopted in collaborative work-spaces. This paper focuses on the analysis of different types of Parallel Continuum Manipulator to find the better geometric structure to achieve quasi-translational motions. Therefore, the goal is to look for new flexible architectures that could be used instead of mechanisms composed by rigid links to improve safety in factories, in alignment with the United Nations Sustainable Development Goal 9: build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation. Keywords: SDG9 · Parallel Continuum Manipulators Motion · Parametric Analysis

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Introduction

Translational Parallel Manipulators (TPMs) are closed-loop mechanisms with rigid links and kinematic joints that connect an end-effector to a fixed frame via several kinematic chains arranged in such a way that the manipulator itself is subjected to a set of permanent geometrical constraints that make the output motion a pure translational 3 DoF motion. A typical example of this class of robot is the Delta-Robot [1–3]. Classical applications for this class of robot are pick and place operation [4], adhesive dispensing, packing small products (cosmetics, pharmaceutical industry, etc.) [5], high precision assembly operation [6], 3D printers [7] and haptic controllers [8].

c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 55–64, 2023. https://doi.org/10.1007/978-3-031-32439-0_7

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Compliant mechanisms are a group of mechanisms that acquire mobility thanks to the flexibility of some of their parts [9,10]. Subsets of the aforementioned class are Parallel Continuum Mechanisms (PCMs), devices in which a rigid end-effector is connected to a fixed frame using flexible slender links whose nonlinear deformation is the cause of its mobility. The research community has already proposed methods for PCMs kinematic modeling, together with some case studies. These PCMs have a rigid end-effector connected to the base frame through six flexible rods whose length is controlled by the robot actuators. Based on this architecture, a class of lower mobility PCMs has been proposed in the study [11] to emulate the mobility of a lower mobility parallel robot, the rigidlink 3P RS tripod. The main advantage of a robot with intrinsic flexibility is related to safety in collaborative workspaces. For example, if for any reason the obstacle avoidance control system fails, the compliance of the PCM could help at mitigating the effect of an impact between the robot and the operator. To model this class of parallel robots, different methods had been proposed in the past. Among them, nonlinear deformation is frequently modeled with the Cosserat rod model [12] expressed through a nonlinear system of differential equations (ODEs). In the case of PCMs, it is not possible to reduce the full mobility of the end-effector through permanent constraints, as for their rigid counterparts. Nevertheless, some mechanical arrangements can introduce a much higher limitation of deformation in some directions, producing a similar constraining effect. The goal of this paper is to investigate the properties of a PCM in which the arrangement of the rod is conceived in a way that the expected motion is similar to the one of a Delta-Robot.

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Mechanism Description

In literature, a six degrees of freedom flexible hexapod had already been studied in [13]. In that work, the authors devised a six-degrees of freedom PCM in analogy with the rigid parallel robot 6P RS, by replacing the revolute joint on each limb with the flexibility of cylindrical rod. To change the pose of the endeffector, the length of the rods is controlled by actuators. To achieve a quasitranslational motion, the flexible rods length Li is controlled in pairs by three prismatic actuators placed under the XY plane and mounted with the axis parallel to the z direction. Referring to Fig. 1, the rods with the same color are controlled together. For this reason, the architecture showed in Fig. 1 is called 3P F S.

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Fig. 1. Architecture 1: Flexible Tripod 3P F S with parallel rods: (a) top view and geometric parameters definition, (b) 3D representation.

The end of rods (2j − 1) and 2j (j = 1, 2, 3) are joined to the end-effector at points B(2j−1) and B2j with spherical joints that introduce no restriction of rod’s self rotation. The same rods (2j − 1) and 2j are connected to the base at fixed points A(2j−1) and A(2j) distributed symmetrically and with a fixed vertical orientation, again with no restriction of intrinsic rotation so that torsion effects on the rods are avoided. At the connection to the fixed base, rods are conducted through said guiding holes Ai (i = 1, . . . , 6) to the three linear actuators j below the base that control the length of the rods (2j − 1) and 2j together (j = 1, 2, 3). An alternative flexible mechanism could be devised by keeping fixed rod lengths Li = L and using the z coordinate of points A(2j−1) and A(2j) as inputs for the mechanism, as shown in Fig. 2. As for architecture 1, the rods (2j − 1) and 2j are clamped at points A(2j−1) and A(2j) with a fixed vertical orientation, while spherical joints are used in the connection with the end-effector at points B(2j−1) and B2j . The geometry of the mechanism is described by the following parameters (Fig. 1 and 2): rA distance between the attachment points Ai and the fixed frame origin O, r distance between the attachment points Bi and the end-effector frame origin P , H distance between the attachment points A(2j−1) and A(2j) equal to the distance between B(2j−1) and B(2j) . These geometry parameters, and in particular the parameter H and the ratio rA /r, have a strong influence on the type of motion of the end-effector as it is presented in Sect. 4.

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Fig. 2. Architecture 2: Flexible Tripod 3P F F SS with parallel rods and fixed rod length: (a) top view and geometric parameters definition, (b) 3D representation.

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Simulation Method

In this section the adopted modeling approach for Forward Kinematics (FK) resolution of PCMs is briefly presented. The description is kept concise for space limitation, the interested reader is addressed to the studies [11,13] for further details. The FK Problem consists of determining the pose of the end-effector, i.e. the position vector of reference point P , p, and the orientation given by the rotation matrix REE , when the inputs are known and a given load Fext ; Mext is imposed. To model the non-linear deformation of rods, the Kirchhoff model is adopted. Each section i of the rod is described with a centroid position pi (s) and orienta˜ i (s) with s ∈ [0, Li ]. Rods’ internal moments tion defined with unit-quaternion q T mi (s) are related to the curvature u(s) through the relation u = K−1 BT R m, where KBT is a stiffness matrix for bending and torsion. Extension-compression or shear effects are neglected in the evaluation of internal forces n(s). The change of shape of the flexible rod and the equilibrium of internal forces and moments with the load along s are related through a system of differential equations dy ds = f , that can be stated with the vector y of variables and the vector of functions f : ⎧ ⎫ ⎧ ⎫ R(s)e3 ⎪ ⎪ p(s) ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ 1 ⎨ ⎨ ⎬ ⎬ ˜ q (s)˜ u (s) ˜ (s) q 2 ; f= (1) y= 0 n(s)⎪ ⎪ ⎪  ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎩ ⎭ ⎪ −1 T

⎩ ⎭ u(s) −KBT e3 R (s)n(s) u(s)KBT u(s) +

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where R(s) the rotation matrix of section i associated to the unit-quaternion ˜ (s), and the operation that converts a three-dimension vector into its skewq matrix representation. ˆ i (s), and uxi (s), uyi (s) can be obtained upon integration Evolution of pi (s), q of the system of equations using Runge-Kutta method, from s = 0 to s = Li . At s = 0, the position of base-tip of the rod pi (s = 0) and the orientation of ˜ i (s = 0) are known given the inputs, while some guess values are used base-tip q for uxi (s = 0), uyi (s = 0), ni (s = 0). Given the inputs, each rod evolution is evaluated and an error function is calculated. This error function ef un is made of the mechanism assembly constraints, static equilibrium on the end-effector and unit-quaternion normalization: ⎧ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎨

ef un

⎫ p1 (L1 ) − p − REE r1 + a1 ⎪ ⎪ ⎪ ⎪ ux1 (L1 ) ⎪ ⎪ ⎪ ⎪ uy1 (L1 ) ⎪ ⎪ ⎪ .. ⎪ ⎪ ⎪ . ⎪ ⎬ p (L ) − p − R r + a 6 6 EE 6 6 = ⎪ ⎪ ux6 (L6 ) ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ (L ) u ⎪ ⎪ y6 6 ⎪ ⎪

⎪ ⎪ 6 ⎪ ⎪ ⎪ ⎪ [n (L )] − F i i ext ⎪ ⎪ i=1

6 ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ [(a + p (L )) × n (L ) + m (L )] − p × F − M i i i i i i i ext ext ⎪ ⎪ i=1 ⎩ ⎭ 2 |˜ q| − 1

(2)

where ai is the position vector of point Ai with respect to the fixed frame and ri is the position vector of point Bi with respect to the end-effector frame. To find the FK Problem solution, this residual have to be minimized following an iterative procedure, in our case through a Newton-Raphson scheme. To ensure convergence, a home position configuration is used so that contiguous configurations are solved with a boundary value problem upon slight changes of either input or output variables. In the following sections, some simulations are presented to describe the type of motion of the mechanisms relative to the position of the end-effector within the workspace. To do so, an Inverse Kinematic algorithm would be needed, but since the resolution of the IK is still under study, an approximated IK method as been adopted. The basic assumption of this approximated method is the fact that an increment of the actuation variable j causes a displacement of the endeffector along the direction perpendicular to the segment B2j−1 B2j and an equal increment of all actuation variables causes a displacement of the end-effector along the z direction. Therefore, the approximate IK relationship can be written as: ⎧ ⎫ ⎡ ⎤ ⎨L1 ⎬ 1 √0 −2 1 L2 = ⎣ √3 1 1⎦ p (3) ⎩ ⎭ 3 L3 − 3 1 1

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By using Eq. (3), the trajectories planned in the operative space are converted into joint space variables used as inputs of the FK algorithm presented before. For this reason, in the following sections the trajectories used to analyze the robot mobility are called “quasi-circular motions at a quasi-constant end-effector height”.

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Parametric Analysis and Motion Evaluation

In this chapter, a parametric analysis is presented to select the geometry for the flexible robot to obtain translational-like motions. Later, the output motions of the robot with the selected geometry is evaluated. Since the goal is to achieve translational-like motion in space, in the following analysis the output rotations of the end effector will be called parasitic rotations, in analogy with the parasitic motions of lower mobility rigid parallel manipulators. As previously mentioned, the geometric parameters rA /r and H affect the magnitude of the parasitic motions of the end effector and, therefore, the type of output motion. As case study, the parasitic motions of a 3P F S mechanism had been studied during the execution of a quasi-circular motion at a quasi-constant end-effector height of 450 mm. The motion can be described by the polar coordinate radius d  40% rA and angle θ (the same nomenclature, presented in Fig. 4, is used later to study the output motion of the mechanism). This simulation had been performed with different values of the ratio rA /r at constant H and with different value of H at constant ratio rA /r. From the results, it is clear that if rA /r or H increase, lower parasitic rotations are obtained, as showed in Fig. 3 for the flexible tripod 3P F S (similar values are obtained also for Architecture 2). It should be underlined, that the results are dependent on stiffness of the system (material, rods diameter and lengths). The simulations presented in this study had been performed with an elastic modulus E = 83GPa (similar to the one of Nitinol), a rod diameter of 2.5 mm and an initial rod length of 500 m. Nevertheless, the influence of the geometric parameters on the type of the output motion is the same. Regarding the size ratio rA /r a trade-off value must be selected in order to limit the total encumbrance of the manipulator, while preserving a minimum dimension of the end-effector. From these preliminary results, it seems like the beneficial effect of reducing the parasitic rotations decreases as the ratio increases. Therefore, even if no optimal evaluation has been done yet, a good starting point is the √ for parameter H √ ratio rA /r = 5.0. The possible values lie in the range [0; 3r]. Therefore, the maximum value 3r is selected, which corresponds to the configuration where B2 ≡ B3 , B4 ≡ B5 and B6 ≡ B1 . For future comparison with commercial linear Delta Robot, the following value for the base radius has been selected rA = 210 mm, which leads to the following dimensions: r = 42 mm and H = 73 mm. Moreover, for the flexible tripod 3P F F SS a constant length of L = 500 mm has been defined. In Fig. 4 the two architectures of flexible tripods are represented with these geometric parameters.

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Fig. 3. Parasitic rotations during a quasi-circular motion, defined by a polar radius d  40% rA and the angle θ, expressed in Euler angles (XY Z): (a) influence of the size ratio rA /r with constant H, (b) influence of H with constant size ratio rA /r = 4.5 and rA = 250 mm.

To test the effectiveness of these mechanisms at generating pure translational motions in space, quasi-circular trajectories have been planned for the two manipulators at increasing radius d on a plane at a quasi-constant height. The resulting parasitic rotations, expressed in Euler angles (XY Z) are presented in Fig. 5. From the results, it can be said that during motions on a plane at a constant height the flexible mechanisms 3P F S and 3P F F SS are characterized by parasitic rotations that increase in magnitude as the distance from the symmetric home position increases. Quantitatively, the absolute value of the rotation in below 5◦ is the distance d is below the value rA /2. While the intensity of the parasitic rotation increases a lot in this range. A physical explanation of this result is the fact that when the projection on the XY plane of the attachment point Bi gets close to its homologous Ai the rod flexion is close to zero, and therefore the rod stiffness makes the end-effector pivoting around the point Bi . Nevertheless, it can be said that quasi-translational motions are possible in a limited range of

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Fig. 4. Selected geometry for the flexible mechanism: (a) top view, (b) 3D representation. With the dotted gray line, the quasi-circular path, that it is used afterwards for the motion evaluation, is represented.

displacement. Moreover, from the results presented in Fig. 5, Architecture 1 is characterized by lower parasitic rotations with respect to Architecture 2. This fact is due to the different stiffness of the flexible rods during motions. In Architecture 1, as the end-effect moves away from points A(2j−1) and A(2j) , the rod length Lj increases with a subsequent lower stiffness, while in Architecture 2 the rod length is constant and, therefore, the increase in stiffness is greater than the one in Architecture 1. Finally, it is worth mentioning that the analysis had been performed with no load applied. Contrary to rigid parallel manipulators, the kinematic position problem solution in flexible PCMs is not independent of the load because the endeffector equilibrium is a fundamental component of the kinematic model. Future studies will investigate the influence of loads over position analysis. Nevertheless, it can be stated that this dependence is not always a drawback in these systems. In fact, as compliant grippers are used to compensate for positioning errors in certain tasks execution, such as peg-in-hole [14], the intrinsic flexibility of PCMs could be exploited to achieve the same result, while at the same time, providing improved safety in case of collisions.

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Fig. 5. Parasitic rotations of the flexible mechanism 3P F S (a) and 3P F F SS (b) expressed in Euler angles (XY Z) during the execution of circular-like trajectories in the XY plane at increasing radius.

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Conclusions

In conclusion, this paper investigated PCMs as an alternative to rigid parallel manipulator, to improve safety in collaborative workspace. Different set of inputs had been proposed for an hexapod flexible mechanism to achieve quasitranslational motion. A parametric analysis had been used to find the best geometric structure at achieving quasi-translational motions. Later, the parasitic rotations during motions at constant height had been studied. From the results, it can be said that it is possible to achieve quasi-translational motions with PCMs, even if not negligible rotations are observed for large displacement from the symmetric home position. Future analysis will focus on the performance comparison between a Delta-Robot and the flexible counterpart with geometry and actuation system defined in this work. Moreover, a prototype will be developed to validate the simulation methods and to study the stability of the system.

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References 1. Laribi, M.A., Romdhane, L., Zeghloul, S.: Analysis and dimensional synthesis of the delta robot for a prescribed workspace. Mech. Mach. Theory 42(7), 859–870 (2007) 2. Stock, M., Miller, K.: Optimal kinematic design of spatial parallel manipulators: application to linear delta robot. J. Mech. Des. 125(2), 292–301 (2003) 3. Vischer, P., Clavel, R., et al.: Kinematic calibration of the parallel delta robot. Robotica 16(2), 207–218 (1998) 4. Cheng, H., Li, W.: Reducing the frame vibration of delta robot in pick and place application: an acceleration profile optimization approach. Shock Vibr. 2018 (2018) 5. Weber, A.: Delta robots feed need for speed. Assembly 58(2), 28–31 (2015) 6. McClintock, H., Temel, F.Z., Doshi, N., Koh, J., Wood, R.J.: The milliDelta: a high-bandwidth, high-precision, millimeter-scale delta robot. Sci. Robot. 3(14), eaar3018 (2018) 7. Wang, Y., Liu, J., Guo, M., Wang, L.: Research on the printing error of tilted vertical beams in delta-robot 3D printers. Rapid Prototyping J. 27, 1633–1649 (2021) 8. Mitsantisuk, C., Stapornchaisit, S., Niramitvasu, N., Ohishi, K.: Force sensorless control with 3D workspace analysis for haptic devices based on delta robot. In: 41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015, pp. 001747–001752. IEEE (2015) 9. Howell, L.L.: Compliant mechanisms. In: McCarthy, J. (ed.) 21st century kinematics, pp. 189–216. Springer, Heidelberg (2013). https://doi.org/10.1007/978-14471-4510-3 7 10. McClintock, H., Temel, F.Z., Doshi, N., Koh, J., Wood, R.J.: The milliDelta: a high-bandwidth, high-precision, millimeter-scale delta robot. Sci. Robot. 3(14) (2018) 11. Altuzarra, O., Tagliavini, L., Lei, Y., Petuya, V., Ruiz-Erezuma, J.L.: On constraints and parasitic motions of a tripod parallel continuum manipulator. Machines 11(1) (2023) 12. Antman, S.S.: Problems in nonlinear elasticity. In: Antman, S.S. (ed.) Nonlinear Problems of Elasticity, pp. 513–584. Springer, Heidelberg (2005). https://doi.org/ 10.1007/0-387-27649-1 14 13. Black, C.B., Till, J., Caleb Rucker, D.: Parallel continuum robots: modeling, analysis, and actuation-based force sensing. IEEE Trans. Robot. 34(1), 29–47 (2018) 14. Sanji, M., Nakamura, T., Suzuki, M., Aoyagi, S.: Robot task of pin insertion to a hole without chamfering and with small clearance using fuzzy control. In: Shirase, K., Aoyagi, S. (eds.) Service Robotics and Mechatronics, pp. 33–36. Springer, London (2010). https://doi.org/10.1007/978-1-84882-694-6 6

Energy Efficiency of a SCARA-Like Manipulator with Elastic Balancing Luca Bruzzone(B)

, Shahab E. Nodehi , G. Berselli , and Pietro Fanghella

DIME, University of Genoa, Via Opera Pia 15A, 16145 Genoa, Italy {luca.bruzzone,giovanni.berselli,pietro.fanghella}@unige.it, [email protected]

Abstract. The paper discusses the energetic efficiency of a SCARA-like manipulator with elastic balancing of the gravity force. The mechanical architecture and the main kinematics aspects of the robot are briefly recalled. Multibody simulations are performed to assess the improvement of energy efficiency which can be obtained by means of the elastic balancing. Then further tests are carried out comparing the energy efficiency of two different Cartesian position control schemes: a classical integer-order KD controller and a fractional-order KDHD controller. Simulation results show that the differences are minimal. Keywords: SDG9 · Static Balancing · Energy efficiency · SCARA robot

1 Introduction Along with the gradual transition to renewable energy sources, the reduction of energy consumption in every field of human activity is one of the key challenges of humanity. In this scenario, the improvement of the energy efficiency of robotized lines is an important topic to be considered [1, 2]. The work is focused on this topic, since energy saving in automation is fundamental to promote sustainable industrialization (SDG9). Nowadays, most industrial manipulators are serial robots, mainly due to their higher ratio between workspace size and robot size with respect to parallel robots. Unfortunately, the energy efficiency of serial robots is usually low, since the arm is much heavier than the payload. Consequently, during the robot movements a great part of actuation power must be used to overcome gravity and inertial forces acting on the robot links. Static balancing can improve the energy efficiency of serial and parallel manipulators [3–5]. The static balancing of a robot arm can be achieved using counterweights (mass balancing) or using elastic elements (elastic balancing). With full mass balancing, the global c.o.m. of the robot arm remains fixed in any position, with no load on the actuators in static conditions. On the other hand, the introduction of counterweights increases inertial forces. Using elastic balancing, gravity forces are counterbalanced by torsional or linear springs, avoiding a remarkable increase of arm mass, but balancing is usually exact only in one arm position and only approximated in the rest of the workspace. As a consequence, mass balancing is more efficient for low speed motions, while elastic balancing is preferable in case of high accelerations and inertial forces. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 65–72, 2023. https://doi.org/10.1007/978-3-031-32439-0_8

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In [6] a 4-DOF SCARA-like architecture was proposed, capable of replacing the widely used SCARA robots (RRPR) in all tasks that can be performed by three translations and one rotation around a vertical axis of the end-effector (Schoenflies motion, [7]). In the proposed scheme (RR-4R-R) the vertical prismatic axis is replaced by a four-bar mechanism, and this allows to introduce elastic or mass balancing. The Cartesian space position control of this robot is discussed in [8], comparing the performances of a classical integer-order controller (KD) and of a fractional-order controller with half-derivative damping (KDHD). Simulation results show that the KDHD approach allows to reduce the tracking error with equal integral control effort and similar maximum values of the actuation torques. In this work, the investigation is focused on sustainability, to evaluate if the KDHD controller can be used to reduce energy consumption maintaining similar values of the tracking error.

2 RR-4R-R SCARA-Like Manipulator with Elastic Balancing The RR-4R-R architecture (Fig. 1) is obtained from the RRPR SCARA architecture [9] by replacing the prismatic joint (P) with a four-bar mechanism (4R) with parallelogram shape placed in a vertical plane. This allows to introduce mass balancing or elastic balancing of the gravitational forces [6].

Fig. 1. RR-4R-R SCARA-like architecture with elastic balancing (a); blue: actuated joints; red: passive joints. Kinematic scheme: overall view (b) and top view (c).

In this work elastic balancing is considered, since industrial tasks usually require high speed and acceleration. There are seven arm links, from the base (link 0) to the endeffector (link 6), connected by seven revolute joints, four actuated (blue in Fig. 1) and

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three passive (red in Fig. 1). The actuators of the revolute joints 1, 2 and 4, with vertical axes, are not loaded by gravity. Only the actuator of joint 3 is loaded by the gravity acting on links 3–6, but an elastic balancing can be added introducing a torsional spring on joint 3, acting in parallel with actuator 3. On the basis of constructive requirements, the balancing spring can be placed on anyone of the three passive revolute joint of the four-bar, without changing the dynamic model, as discussed in [8]. The angular positions of the actuated revolute joints are collected in the vector of the internal coordinates, θ = [θ 1 , θ 2 , θ 3 , θ 4 ]T , while the position of the end-effector reference point E and the end-effector rotation with respect to the fixed reference frame O(x, y, z) are represented by the vector of the external coordinates, x = [x, y, z, θ ]T (Fig. 1). The nonlinear position analysis, the Jacobian matrix, and the dynamic model of the robot are extensively discussed in [6], and their expressions are not reported here for brevity.

3 Cartesian Space Position Control The classical KD Cartesian space position control with gravity compensation is expressed by the following control law:   τ = JT (θ) KKD (xd − x(θ)) + DKD (xd − x(q))(1) + τg (θ) (1) where τ = [τ 1 , τ 2 , τ 3 , τ 4 ]T is the vector of the actuation torques, xd is the time-varying vector of the external coordinates of the set-point trajectory, τ g (θ) is the vector of the gravity compensation torques, KKD and DKD are the stiffness and damping matrices. The superscript (i) indicates the i-th order time derivative, and in Eq. (1) it is used to indicate the first-order damping term. The matrices KKD and DKD define the translational impedance, the rotational impedance or both [10]. For robots with Schoenflies motion, as the RR-4R-R arm, their size is 4 × 4; moreover, in order that the 1-DOF rotational behavior is decoupled from the translational behavior, KKD and DKD are usually block-diagonal, with a 3 × 3 submatrix representing the translational impedance and the fourth diagonal element representing the rotational impedance. Gravity acts only on the actuator of joint 3, as discussed in Sect. 2; consequently, the only non-null element of τ g (θ) is the third:   τg,3 (θ3 ) = −(m3 lG3 + m4 lG4 + l3 (m5 + m6 ))g cos θ3 + k3 θ3 − θ3p (2) where mi is the mass of the i-th link, lGi defines the position of the c.o.m. of the i-th link (Fig. 1b), l i are the link lengths of kinematic chain (Fig. 1b), k 3 is the balancing spring stiffness, and θ 3p is the angle of joint 3 corresponding to the spring neutral position. The first term of Eq. (2) is usually negative, since the gravity compensation torque is opposite to the positive direction of θ 3 . The second term of Eq. (2) takes into account the elastic return torque of the balancing spring, and is usually positive, so it compensates the first term, as wanted. If exact static balancing (τ g,3 = 0) is imposed with links 3 and 4 horizontal (θ 3 = 0), the following relationship between the spring parameters holds: θ3p = −(m3 lG3 + m4 lG4 + l3 (m5 + m6 ))g/k3

(3)

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Condition (3) is imposed for a specific payload value, which influences the endeffector mass m6 . If the payload varies without changing the spring parameters k 3 and θ 3p , static balancing is exact for a non-null value of θ 3 , and approximated in the other positions. In general, the spring parameters k 3 and θ 3p should be selected on the basis of the specific task. The effectiveness of static balancing for the RR-4R-R architecture discussed in [6]. The KDHD control law differs from the KD control law (1) for the addition of a damping term proportional, through the half-derivative damping matrix HDKDHD , to the half-derivative (derivative of order 1/2) of the external coordinates error: ⎛⎛ ⎞ n w j ⎜⎜ ⎟ j=0 ⎜⎜ ⎟ τ = JT (θ)⎜⎜KKDHD − 1/2 HDKDHD ⎟(xd − x(θ)) ⎝⎝ ⎠ Ts  + DKDHD (xd − x(q))(1) + HDKDHD (xd − x(q))(1/2) + τg (θ)

(4)

In Eq. (4) the half-derivative is computed using the n-th order digital filter derived by the Grünwald–Letnikov definition [11] of the half-derivative of a time function f(t): ⎛ ⎞ n

1 wj f ((k − j)Ts )⎠, k = [t/Ts ], f (t)(1/2) ∼ = f (kTs )(1/2) ∼ = 1/2 ⎝ Ts j=0 (5)   3 wj−1 , j= 1... n w0 = 1, wj = 1 − 2j In Eq. (4) there are two main differences with respect to the law (1): firstly, the introduction of the half-derivative term; secondly, the compensation of the stiffness term based on the half-derivative matrix. This compensation is necessary since the digital filter (5) is finite-order and thus introduces an unwanted alteration to the stiffness, as discussed in [8]. With this compensation, the steady-state behaviors achieved by the control laws (1) and (4) are the same. The KDHD control law represents an extension of the KD comprising the half-derivative term for MIMO systems, as the PDD1/2 scheme [12, 13] represents the same extension of the PD control for SISO systems.

4 Simulation Results A multibody model of the RR-4R-R manipulator has been implemented using the simulation environment Simscape Multibody™ by MathWorks, neglecting friction in joints. The following link lengths have been considered (Fig. 1): l 1 = 0.9 m, l2 = l 3 = 0.33 m, l4 = 0.387 m. The positions of the c.o.m. of the links are defined by these parameters (Fig. 1): lG1 = l G3 = l G4 = 0.165 m. The masses of the six links are m1 = 10 kg, m2 = 5 kg, m3 = 5 kg, m4 = 5 kg, m5 = 12 kg, m6 = 3 kg (including payload). The balancing spring parameters are k 3 = 247.3 Nm/rad and θ 3p = −15°, which fulfil the condition expressed by Eq. (3).

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In the simulations, a six-phase motion is considered (Fig. 2). In each phase, the end-effector set-point position moves from the reference position xref for a distance d in a time t mov along one axis of the fixed reference frame O(x,y,z) (Fig. 1b), stops at xref + x for t stop , returns to xref in t mov , and stops again for t stop , always with constant the end-effector orientation (θ = 0). In the reference position xref the end-effector is in the central zone of the workspace, with θ = [−45°, 90°, 0°, −45°]T , and links 3 and 4 are horizontal. In the six phases, the displacements x are respectively (d, 0, 0), (0, d, 0), (0, 0, d), (−d, 0, 0), (0, −d, 0), (0, 0, −d). In each phase, the going and the return motions with duration t mov are performed with an s-curve motion divided into three parts: acceleration, with duration αt mov ; constant velocity, with duration (1–2α)t mov ; and deceleration, with duration αt mov . Consequently, the parameters d = 0.15 m, t mov = 0.3 s, t stop = 1 s, and α = 0.2 define completely the set-point motion.

Fig. 2. Set-point reference motion considered in the simulations.

During this motion the end-effector angle is constant, but this hypothesis does not limit the generality of the analysis since, as discussed in Sect. 3, the 1-DOF rotational behavior is usually decoupled from the 3-DOF translational behavior. Therefore, in absence of joint friction, the rotational behavior is linear and decoupled, and can be tuned as discussed for the PDD1/2 control of SISO systems [12, 13]. In the considered motion θ is constant, and the fourth actuator moves accordingly with almost null torque. In the simulations, the Integral Control Effort (ICE) and the Integral Square Error (ISE) of the end-effector translational coordinates are considered: ICE =

T 4 sim

i=1 0

τi2 dt,

ISE =

Tsim 

 (xd − x)2 + (yd − y)2 + (zd − z)2 dt

(6)

0

where T sim is the simulation time, sufficiently long to comprise the residual vibrations. Figure 3 shows the time histories of the actuation torques for the previously discussed reference motion adopting the KD Cartesian space position control (1), comparing two cases, with or without elastic balancing, and adopting the following control parameters: diagonal matrix KKD with elements k KD,x = k KD,y = k KD,z = 8 · 103 N/m, and k KD,θ = 5 · 102 Nm/rad; diagonal matrix DKD with elements d KD,x = d KD,y = d KD,z =

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5 · 103 Ns/m, and d KD,θ = 7.5 Nms/rad. It is possible to note that the elastic balancing influences only the torque of the third actuator, which drives the vertical motion. With elastic balancing, the torque is null when the end-effector remains in the horizontal plane containing xref (in phases 1, 2, 4, and 5).

Fig. 3. Actuation torques with or without elastic balancing (τ 1 , τ 2 and τ 4 are equal in the two cases).

Figure 4 shows the time histories of the end-effector errors, which are equal with or without elastic balancing: as a matter of fact, according to Eq. (2), a part of the gravity compensation term τ g,3 (θ 3 ) is exerted by the spring if elastic balancing is present, reducing the ICE (from 7.69 · 104 N2 m2 s to 4.42 · 104 N2 m2 s, −42.6% for the considered motion), but the overall dynamic behavior, and consequently the end-effector motion, are unaltered, with the same ISE (2.41 · 10–5 m2 s). The results of Figs. 3 and 4 confirm the capability of elastic balancing to reduce energy consumption, provided that the end-effector remains for most time at a vertical position in which elastic balancing is nearly exact. To obtain this, the spring neutral position must be adjusted for the specific task. Now we will discuss the possibility of further reduction of the energy consumption by replacing the KD control law (1) with the KDHD law (4). In [8] it is shown that the KDHD law reduces the tracking error with respect to KD in terms of ISE and maximum and mean absolute values of the x, y, z end-effector errors with equal ICE. In particular, it is verified that a KDHD tuning with halved first order damping (DKDHD matrix), compensated by a half-derivative damping (HDKDHD matrix) which maintains the same ICE, represents a proper compromise between tracking error reduction and peaks of the actuation torques. This tuning, for the considered manipulator and case study, is characterized by the same control values of the previously considered KD law (results of Figs. 3 and 4), except the halved diagonal x, y, z values of DKDHD matrix (d KDHD,x = d KDHD,y = d KDHD,z = = 2.5 · 103 Ns/m) and the HDKDHD matrix with diagonal elements hd KDHD,x = hd KDHD,y = hd KDHD,z = 22500 Ns1/2 /m hd xyz , and hd KDHD,θ = 2.4 · 104 Nms1/2 /rad. Moreover, for the calculation of the half-derivatives, Eq. (5) is used, with n = 10 and T s = 5 ms. In the following, for energy reduction purposes, this KDHD tuning is modified by multiplying the first three diagonal elements of the matrices KKDHD , DKDHD and HDKDHD , related to the x, y, z coordinates, for the same coefficient k l < 1. Figure 5

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Fig. 4. End-effector position errors.

shows the percentage variations of ICE, ISE and maximum values of the actuation torques τ 1 , τ 2 and τ 3 between the KDHD and KD law, as a function of k l .

Fig. 5. Percentage variations between KDHD and KD of ICE, ISE, and maximum values of the actuation torques τ 1 , τ 2 and τ 3 as a function of k l .

As already said, for k l = 1 the KDHD controller requires the same ICE of the KD controller, but it has lower ISE (−4.45%), τ 1max (−0.48%), τ 2max (−1.70%) and τ 3max (−4.63%). Lowering progressively k l , the ISE increases, reaching the same value of the KD law for k l = 0.977 (dashed vertical line in Fig. 5). With this tuning, the reduction of ICE is minimal (−0.14%), and the reduction of the maximum actuation forces is slightly higher (−1.73%, −2.30% and −5.06% respectively for τ 1 , τ 2 and τ 3 ). A further decrease of k l is not convenient since the ISE increases quickly.

5 Discussion of the Results and Conclusions The results reported in Sect. 4 and in [8] show that, while the KDHD overperforms the KD when the objective is to reduce the tracking error with similar ICE, it has not the same effectiveness in reducing the ICE with the same tracking error. In other words, the benefits of replacing the integer-order controller with the fractional-order one are marginal if the main goal is not accuracy improvement but energy saving. On the other

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hand, the reduction of the maximum values of the actuator torques can have an indirect effect if it allows to modify the actuator size and consequently to lighten the manipulator arm, but this possibility has to be evaluated on the basis of the robot detailed design and actuators choice. On the contrary, a significant decrease of the energy consumption can be potentially achieved by replacing the widely used SCARA robots with the proposed RR-4R-R arm with elastic balancing. In the future work, the energy efficiency of the RR-4R-R arm with respect to the SCARA arm will be evaluated not only adopting static balancing, but also exploiting dynamic balancing techniques for high-speed and repetitive motions [14]. Acknowledgements. This research has been partially funded by the Interreg Project SMERF – SME Ready for the Future.

References 1. Pellicciari, M., Berselli, G., Leali, F., Vergnano, A.: A minimal touch approach for optimizing energy efficiency in pick-and-place manipulators. In: Proceedings of the IEEE 15th International Conference on Advanced Robotics (ICAR), Tallinn, Estonia, pp. 100–105 (2011) 2. Meike, D., Pellicciari, M., Berselli, G., Vergnano, A., Ribickis, L.: Increasing the energy efficiency of multi-robot production lines in the automotive industry. In: Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE), Seoul, Korea, pp. 700–705 (2012) 3. Martini, A., Troncossi, M., Rivola, A.: Algorithm for the static balancing of serial and parallel mechanisms combining counterweights and springs: generation, assessment and ranking of effective design variants. Mech. Mach. Theory 137, 336–354 (2019) 4. Carricato, M., Gosselin, C.: A statically balanced Gough/Stewart-type platform: conception, design, and simulation. J. Mech. Robot. 1(3), 1–16 (2009) 5. Russo, A., Sinatra, R., Xi, F.: Static balancing of parallel robots. Mech. Mach. Theory 40(2), 191–202 (2005) 6. Bruzzone, L., Bozzini, G.: A statically balanced SCARA-like industrial manipulator with high energetic efficiency. Meccanica 46(4), 771–784 (2011) 7. Hervé, J.M.: The Lie group of rigid body displacements, a fundamental tool for mechanism design. Mech. Mach. Theory 34, 719–730 (1999) 8. Bruzzone, L., Nodehi, S.E.: Application of half-derivative damping to Cartesian space position control of a SCARA-like manipulator. Robotics 11(6), 152 (2022) 9. Makino, H., Furuya, N.: Selective compliance assembly robot arm. In: Proceedings of the First International Conference on Assembly Automation, Brighton, UK, pp. 77–86 (1980) 10. Bruzzone, L., Molfino, R.M.: A geometric definition of rotational stiffness and damping applied to impedance control of parallel robots. Int. J. Robot. Autom. 21(3), 197–205 (2006) 11. Das, S.: Functional Fractional Calculus. Springer, Germany (2011) 12. Bruzzone, L., Fanghella, P.: Comparison of PDD1/2 and PDµ position controls of a second order linear system. In: Proceedings of the IASTED International Conference on Modelling, Identification and Control MIC 2014, Innsbruck, Austria, pp. 182–188. Acta Press (2014) 13. Bruzzone, L., Fanghella, P.: Fractional-order control of a micrometric linear axis. J. Control Sci. Eng. 2013, 947428 (2013) 14. Carabin, G., Scalera, L., Wongratanaphisan, T., Vidoni, R.: An energy-efficient approach for 3D printing with a Linear Delta Robot equipped with optimal springs. Robot. Comput.-Integr. Manuf. 67, 102045 (2021)

Deep Learning Technique to Identify Abrupt Movements in Human-Robot Collaboration Michele Polito, Elisa Digo(B) , Stefano Pastorelli, and Laura Gastaldi Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy [email protected]

Abstract. According to the ninth Sustainable Development Goal (SDG9) of the 2030 Agenda, an upgrade of technological capabilities promotes the development of a sustainable and inclusive industrialization. In this context, a fundamental requirement is represented by the operator’s safety inside the workspace, especially when it is shared with a collaborative robot. Even if typical collaborative tasks are usually characterized by repetitive and controlled kinematics and dynamics, external disturbances and environmental factors can make the operator executing unexpected and abrupt gestures which are highly variable. The current study aimed at identifying human unexpected movements measuring upper body accelerations through wearable magneto-inertial measurement units. An experimental pick and place task was performed by five subjects, combining both routine and abrupt movements. Recurrent neural network was exploited to distinguish between normal and unexpected gestures. Overall, the chosen deep learning network and the developed pre-classification method for accelerations proved to be suitable for the identification of human abrupt movements in interaction with machines. Keywords: SDG9 · MIMUs · deep learning · human-robot interaction · upper limb · motion tracking

1 Introduction The ninth Sustainable Development Goal (SDG9) of the 2030 Agenda highlights the promotion of an inclusive and sustainable industrialization by significantly raising industry’s share of employment and upgrading the technological capabilities of industrial sectors in all countries [1]. In this scenario, the safety of the operator inside the workspace represents a fundamental requirement. This requirement is enhanced when the worker is sharing the same workspace and interacting with a robot [2]. Indeed, the humanrobot collaboration is becoming an emerging research field focused on optimizing the applicability, performance, and effectiveness of working conditions [3]. Typical industrial and collaborative tasks, such as pick and place, reaching, and assembly are characterized by repetitive and controlled movements associated to normally predictable kinematics and dynamics, within a certain range. In these cases, the tracking of human motion and the recognition of human activities can be easily performed with different technologies such as optical systems [4, 5] or inertial sensors © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 73–80, 2023. https://doi.org/10.1007/978-3-031-32439-0_9

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[6–8]. However, it is possible that distraction, environmental factors or external disturbances make the operator executing abrupt and sudden gestures, different from routine movements [9]. When this situation occurs, gestures are highly variable and characterized by uncertain execution pattern in terms of the number of involved human segments and the kinematic and dynamic ranges [10]. Castellote and colleagues have studied the voluntary reaction to a startling auditory stimulus in tasks in which the main requirement is the accuracy. This kind of stimulus speeds up only the first part of the movement in an accuracy task [11]. In [12], a human involuntary motion is defined as a rapid hormonal reaction resulting in a fast and uncontrolled movement. Therefore, considering that unexpected robot motions can cause human involuntary movements, the authors have found out that hands-on user training can increase cognitive and physical safety in human-robot interaction. Rosso and colleagues have estimated four features based on the kinematics of impulsive gestures, developing a methodological study to characterize this kind of movements through an inertial sensor fixed on the wrist [10]. These works have studied the characteristics and the effects of unexpected movements on the performance of tasks execution. However, to the authors’ best knowledge, the identification of these events in real-time with the final aim of enhancing safety in human-robot interaction has not been investigated yet. Accordingly, the purpose of the current study was to identify human unexpected movements through accelerations signals. An experimental pick and place task was performed by five subjects wearing inertial sensors on their upper body. Since deep learning techniques proved to be efficient architectures when dealing with one-dimensional input data [13], a recurrent neural network was trained with wrists accelerations elaborated with two different methodologies, with the final aim of distinguishing between normal and unexpected movements.

2 Materials and Methods 2.1 Experimental Set-Up The experiment was thought to be executed while seated in front of a table in order to simulate a working location. Two surfaces with thirty holes and one hole respectively (diameter of 6 cm) were realized. The first surface was positioned on the table, while the second one was placed at a height of 30 cm from the table (Fig. 1). Four areas were identified to simulate pick and place gestures in different directions: anterior-posterior (AP), medio-lateral (ML), oblique (OB), and vertical (VE). A couple of LEDs (a green one and a red one) was associated to each of these locations. Moreover, a sound buzzer was placed in the top left area of the table, and it was controlled by the same Arduino nano. A box containing 30 golf balls was positioned in front of the subject location. The instrumentation adopted for the experiment was composed of an inertial system and a microcontroller (Arduino, Italy). The inertial system (Opal™ APDM, USA) adopted for the experiment consisted in five wireless magneto-inertial measurement units (MIMUs) containing a tri-axial accelerometer (range ±200 g), a tri-axial gyroscope (range ±2000°/s), and a tri-axial magnetometer (range ±8 Gauss). Inertial sensors were fixed on participants’ upper body through bands supplied by the APDM kit (Fig. 1): right upper arm, right wrist, sternum, left upper arm, left wrist. Each unit was positioned paying attention to the alignment of its x-axis with the longitudinal axis of the

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corresponding segment. The communication between MIMUs and a PC was guaranteed via Bluetooth. Data were acquired through the proprietary software Motion Studio™ (APDM, USA) with a sampling frequency of 200 Hz. The microcontroller adopted to control the lighting of LEDs and buzzer was an Arduino Nano (processor = ATmega328, clock speed = 16 MHz, operating voltage = 5 V). An integrated development environment was used to write a code setting a random lighting of the LEDs and the buzzer every 3 s (20 bpm). The synchronization of both systems was obtained sending a trigger (5 V) from Arduino to Opal.

Fig. 1. Experimental set up.

2.2 Protocol Five healthy participants (3 males and 2 females) with no musculoskeletal or neurological diseases were recruited for the experiment through a written informed consent. Their anthropometric data (mean ± standard deviation) were collected: age = 37.8 ± 15.8 years, Body Mass Index = 20.7 ± 0.9 kg/m2 , upper arm length = 0.34 ± 0.03 m, forearm length = 0.27 ± 0.01 m. Three subjects were right-handed, while the other two were left-handed. The study was approved by the Local Institutional Review Board and all procedures were conformed to the Helsinki Declaration. First, each subject was asked to sit in front of the table and to choose the more appropriate hole of each area (AP, ML, OB, VE) depending on his/her anthropometric characteristics. The test was a repeated pick and place task with the presence of both normal and abrupt movements (Fig. 2). The normal movement consisted in picking a ball and placing it inside a specific hole. The sequence of holes where to position each ball was marked by the lighting of green LEDs. Instead, the unexpected movements were signaled by randomly blinking a red LED or lighting the buzzer. In the first case, subjects were asked to place the ball inside the hole corresponding to the red LED as fast as possible. In the second case, participants were asked to rise above the head the arm involved in the test as fast as possible. The test was repeated three times for each subject: (i) executing the pick and place with the right hand and with the trunk frontal with respect to the table; (ii) executing the pick and place with the left hand and with the trunk frontal with respect to the table; (iii) executing the pick and place with the left hand and with the trunk lateral with respect to the table. Four unexpected movements (two visual and two sonorous) were generated inside each repetition.

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Fig. 2. Experimental protocol: (a) normal movement - green LED; (b) unexpected movement red LED; (c) unexpected movement - buzzer.

2.3 Data Analysis Considering the purpose of the study, the data processing only focused on accelerations recorded through MIMUs on wrists, with the final aim of training a neural network for the recognition of unexpected movements. Wrists accelerations were first processed by excluding the gravity and estimating the norm of signals. Then, the next step of the data analysis was to extract the single movements from the total acquisition. For the movements defined as normal, the signal was well-paced by the lighting of the green LEDs, which was regular with a frequency of 20 bpm. In this case, each signal section of three-second duration started with the lighting of the green LED, and it ended with the instant before the lighting of the next green LED. Therefore, the signal was segmented as described above, setting the time frame of each section from 0 to 3 s. On the other hand, the unexpected movements occurred within sections previously identified and they were detected by the turning on of the red LED or the audible buzzer. Once the segmentation was performed, two different methodologies were adopted to pre-classify the unexpected movements. First, the entire three-second window in which the abrupt movement occurred was pre-classified as unexpected. This kind of fragmentation led to 26 normal movements and 4 unexpected ones in each trial of each subject. In the second methodology, to move towards real-time situations, each window was divided into three additional sub-windows of one-second duration each. This approach was adopted because unexpected movements generally have a shorter duration than the normal ones. Moreover, the reaction time of each subject can temporally shift the actual onset of the movement. This kind of fragmentation leads to 78 normal movements and 12 potential abrupt ones in each trial of each subject. Moreover, an additional condition was introduced for the potential unexpected windows by evaluating the standard deviation value with respect to a threshold. In detail, only sub-windows with standard deviation above 1.5 m/s2 were considered as abrupt, while the other ones were excluded from the classification. For both methodologies, windows were divided into four groups considering that each LED was associated to a different direction (AP, ML, OB, VE). Considering only normal movements, the average and the standard deviation values of wrists accelerations were calculated for each trial, keeping movements along the four directions separated. These values were first assessed for all the trials and all the subjects. Then, inter-subject mean and standard deviation values were estimated.

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The classification of movements in normal and abrupt ones was performed through a recurrent neural network called Long Short-Term Memory [14] with the following characteristics: 1 input layer, 1 hidden layer of 100 hidden units, 2 output layers, Adam optimization, 100 epochs. For both methodologies, the pre-classified accelerations were divided in training (TR) and test (TE) sets. For the first methodology 120 windows were used for TR (60 normal, 60 unexpected), whereas 630 windows were used for TE (604 normal, 26 unexpected). For the second methodology 120 windows were used for TR (60 normal, 60 unexpected), whereas 2009 windows were used for TE (1932 normal, 77 unexpected). Once the classification was concluded with both methodologies, confusion matrices were built comparing real and predicted classes [15]. Moreover, starting from the values of these matrices (true positives = TP, false positives = FP, true negatives = TN, false negatives = FN), the following scores [6, 16] were estimated to quantify the overall performance of the classification (Eqs. From 1 to 4): Accuracy = (TN + TP)/(TN + FP + TP + FN )

(1)

Precision = TP/(TP + FP)

(2)

Recall = TP/(TP + FN )

(3)

F1-score = 2 · (Precision · Recall)/(Precision + Recall)

(4)

3 Results Table 1 contains inter-subject mean and standard deviation values of wrist acceleration estimated for each trial and for both normal and unexpected movements on windows of 3 s. Results related to the normal movements are reported separately for the four directions. Table 1. Average values of wrists accelerations (m/s2 ) on windows of 3s Mean (standard deviation)

Normal movements

Unexpected movements

AP

ML

OB

VE

Trial 1

1.31 (0.26)

1.37 (0.14)

1.29 (0.27)

1.46 (0.22)

3.54 (0.23)

Trial 2

1.24 (0.18)

1.49 (1.17)

1.37 (0.22)

1.30 (0.08)

3.17 (0.27)

Trial 3

1.07 (0.28)

1.42 (0.20)

1.21 (0.25)

1.18 (0.23)

3.26 (0.81)

Figure 3 shows the average trend of the acceleration collected during normal movements for each direction in a specific trial for the subject 02, as an example. Standard

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deviation bounds are reported. In the same graph it is overlaid the acceleration trend of the abrupt movement. Figure 4 shows the confusion matrices obtained from classification results of the neural network with both methodologies. Table 2 contains percentage values of accuracy, precision, recall, and F1-score calculated from confusion matrices for both methodologies as indices of classification performance.

Fig. 3. Movement acceleration: normal average trend vs unexpected trend.

Fig. 4. Confusion matrices for the first (left) and the second (right) methodologies.

4 Discussions The aim of this study was to identify human abrupt movements applying a deep learning technique to wrists accelerations measured with MIMUs.

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Table 2. Classification scores estimated from confusion matrices Accuracy (%)

Precision (%)

Recall (%)

F1-score (%)

First methodology

18.89

4.33

88.46

8.26

Second methodology

99.25

85.23

97.40

90.91

Considering the comparison between normal and unexpected acceleration trends (Fig. 3), the two signals are different in terms of shape, magnitude, and variation. Indeed, the amplitude of normal accelerations is definitively smaller than the one of abrupt accelerations. In addition, normal movements are very repetitive, as shown by the thin bands formed by mean and standard deviation for each direction (Fig. 3). On the contrary, a comparison among unexpected movements is more complex because each trend is dependent on the subject, the stimulus, and the specific trial. All these considerations are also inferable from inter-subject mean and standard deviation values (Table 1). Indeed, results related to unexpected movements (range 3.17–3.54 m/s2 ) are greater than the ones related to normal movements (range 1.07–1.49 m/s2 ). The unpredictability of the abrupt movements suggests the exploitation of a more complex tool for classifying the different gestures. The comparison between confusion matrices obtained from both methodologies (Fig. 4) demonstrates that a light preprocessing of data improves classification results. In detail, both the choice of an appropriate window duration (1 s instead of 3 s) and a finer pre-classification of unexpected gestures (condition on the standard deviation) allow obtaining a more effective network training and hence higher values on the principal diagonal of the confusion matrices (Fig. 4). Moreover, in both cases, the number of false negatives (first methodology = 3, second methodology = 2) is lower than the one of false positives (first methodology = 508, second methodology = 13). This unbalanced erroneous classification leads to a more conservative situation, which is preferable in the context of collaborative robotics because it guarantees a safer interaction. All these considerations are confirmed by classification scores estimated from confusion matrices (Table 2). In fact, all values are higher when adopting the second methodology instead of the first one. In addition, since the recall is higher than the precision in both cases, it is more frequent that a normal movement is classified as an unexpected one than vice versa. Finally, considering the F1score as an overall index of classification performance combining precision and recall, the second methodology produced a score value very close to 100%. Accordingly, the chosen deep learning network and the developed pre-classification method for MIMUs accelerations can be considered suitable for identifying human abrupt movements in the industrial context. This identification can be implemented in real-time to make the robot aware of human actions in order to guarantee collision avoidance and hence to optimize the collaboration. The main limit of this study is represented by the restricted number of involved subjects, which is not appropriate when applying deep learning techniques. In this regard, current activities consist in extending the same experimental campaign to 100 subjects in order to have a homogeneous sample in terms of gender and age. Moreover, considering that the project is thought for industrial scenarios of collaborative robotics, current efforts

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aim reducing the duration of windows in which the signal is fragmented. This aspect can guarantee lower classification times and make the process closer to real-time.

References 1. United Nations: Goals @ Sdgs.Un.Org. https://sdgs.un.org/goals 2. Melchiorre, M., Scimmi, L.S., Pastorelli, S.P., Mauro, S.: Collison avoidance using point cloud data fusion from multiple depth sensors: a practical approach. In: 23rd International Conference on Mechatronics Technology, ICMT 2019 (2019). https://doi.org/10.1109/ICM ECT.2019.8932143 3. Losey, D.P., McDonald, C.G., Battaglia, E., O’Malley, M.K.: A review of intent detection, arbitration, and communication aspects of shared control for physical human–robot interaction. Appl. Mech. Rev. 70, 1–19 (2018). https://doi.org/10.1115/1.4039145 4. Weitschat, R., Ehrensperger, J., Maier, M., Aschemann, H.: Safe and efficient human-robot collaboration part I: estimation of human arm motions. In: Proceedings - IEEE International Conference on Robotics and Automation, pp. 1993–1999. IEEE (2018) 5. Wang, Y., Ye, X., Yang, Y., Zhang, W.: Collision-free trajectory planning in human-robot interaction through hand movement prediction from vision. In: IEEE-RAS International Conference on Humanoid Robots, pp. 305–310 (2017) 6. Digo, E., Antonelli, M., Cornagliotto, V., Pastorelli, S., Gastaldi, L.: Collection and analysis of human upper limbs motion features for collaborative robotic applications. Robotics 9, 33 (2020). https://doi.org/10.3390/robotics9020033 7. Digo, E., Gastaldi, L., Antonelli, M., Pastorelli, S., Cereatti, A., Caruso, M.: Real-time estimation of upper limbs kinematics with IMUs during typical industrial gestures. Procedia Comput. Sci. 200, 1041–1047 (2022). https://doi.org/10.1016/j.procs.2022.01.303 8. Digo, E., Pastorelli, S., Gastaldi, L.: A narrative review on wearable inertial sensors for human motion tracking in industrial scenarios. Robotics 11 (2022). https://doi.org/10.3390/robotics1 1060138 9. Devin, S., Alami, R.: An implemented theory of mind to improve human-robot shared plans execution. In: ACM/IEEE International Conference on Human-Robot Interact, 2016-April, pp. 319–326 (2016). https://doi.org/10.1109/HRI.2016.7451768 10. Rosso, V., Gastaldi, L., Pastorelli, S.: Detecting impulsive movements to increase operators’ safety in manufacturing. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 174–181. Springer, Cham (2022). https://doi.org/10.1007/978-3030-87383-7_19 11. Castellote, J.M., Valls-Solé, J.: The StartReact effect in tasks requiring end-point accuracy. Clin. Neuroph. 126, 1879–1885 (2015). https://doi.org/10.1016/j.clinph.2015.01.028 12. Kirschner, R.J., Burr, L., Porzenheim, M., Mayer, H., Abdolshah, S., Haddadin, S.: Involuntary motion in human-robot interaction: effect of interactive user training on the occurrence of human startle-surprise motion. In: IEEE ISR 2021 (2021). https://doi.org/10.1109/ISR50024. 2021.9419526 13. Venturini, F., Sperti, M., Michelucci, U., Gucciardi, A., Martos, V.M., Deriu, M.A.: Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks: application to olive oil. J. Food Eng. 336, 111198 (2023). https://doi.org/10.1016/ j.jfoodeng.2022.111198 14. Van Houdt, G., Mosquera, C., Nápoles, G.: A review on the long short-term memory model. Artif. Intell. Rev. 53(8), 5929–5955 (2020). https://doi.org/10.1007/s10462-020-09838-1 15. Düntsch, I., Gediga, G.: Confusion matrices and rough set data analysis. In: Journal of Physics: Conference Series, vol. 1229 (2019). https://doi.org/10.1088/1742-6596/1229/1/012055 16. Krstini´c, D., Braovi´c, M., Šeri´c, L., Boži´c-Štuli´c, D.: Multi-label classifier performance evaluation with confusion matrix, pp. 01–14 (2020). https://doi.org/10.5121/csit.2020.100801

Planning Real-Time Energy Efficient Trajectories for a Two Degrees of Freedom Balanced Serial Manipulator Domenico Dona’(B) , Basilio Lenzo(B) , and Giulio Rosati Department of Industrial Engineering, University of Padova, Via Venezia 1, Padua, Italy [email protected]

Abstract. The recent climate crisis and energy price rises are indicators of the necessity of a paradigm shift in the way we think industry. A more sustainable manufacturing industry is needed to tackle nowadays’ challenges. Practical solutions may be either using cleaner energy sources or reducing the overall energy consumption. Efficient use of robotic systems has been identified as a promising approach, for instance re-shaping robot trajectories ensuring reduced energy consumptions without penalizing throughput at the same time. The problem is herein addressed for a particular class of manipulators, i.e. those that exhibit linear dynamics. In this case, the optimal control problem can be solved in closed form, giving the optimal solution in terms of minimum energy. The solution is obtained for a two degrees of freedom planar balanced manipulator and compared to a reference standard law. Results show a significant reduction of the energy consumption. Since the solution is obtained analytically, the computational burden allows real-time applicability.

Keywords: SDG9 Manipulator

1

· Energy Saving · Optimal Control · Robotic

Introduction

The recent energy price rises and the governments’ goals for sustainable growth suggest efforts on developing strategies for reducing energy expenditure (EE) in the manufacturing industry. In this scenario, both academia and industry are working to reduce the impact of energy consumption of robotic sources without affecting the throughput. For example, in [5,6] lighter parts were designed to obtain a more efficient manipulator. Other approaches exploit elastic elements: for instance, in [2,7,10] a proper spring system was developed to balance gravity-related effects. Elastic elements can be introduced and tuned to obtain an efficient conversion between kinetic and potential energy, as in [9]. Software c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 81–88, 2023. https://doi.org/10.1007/978-3-031-32439-0_10

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solutions have the advantage of easier implementation. Point-to-point (PTP) motions are a typical application. Previous works have exploited the tuning of given laws to obtain energy-efficient trajectories, such as [1,3,4]. Furthermore, not only the motion law has influence on the EE but also the location in the workspace of the given task. For example, in [11] a novel performance index was developed, able to predict the energy expenditure of a task based on the inertia ellipsoid. A more general solution for the problem of finding the minimumenergy trajectory for PTP motions lies in optimal control. On the other hand, a closed-form solution is typically difficult to obtain since the dynamics of manipulators are, in general, nonlinear. Yet, there exist particular cases that exhibit linear dynamics. That is the case, for example, of a balanced planar two Degreeof-Freedom (DoF) manipulator equipped with revolute joints. In this work, a methodology to derive optimal (in terms of minimum EE) trajectories for PTP motions is presented. This is developed for a 2 DoF balanced planar manipulator. The result is obtained using Hamilton’s canonical equations. The methodology can be applied for any manipulator that exhibits linear dynamics, for instance, cartesian robots. The aforementioned planar manipulator was chosen to show the applicability of the method also in presence of coupled dynamics. The remainder of this paper is organized as follows. The formulation of the problem is provided in Sect. 2. Section 3 presents algorithms for real-time computation of energy-optimal trajectories. Numerical results in Sect. 4 demonstrate the benefits of the presented methodology. Conclusions are in Sect. 5.

2 2.1

Problem Statement Electro-Mechanical Model

Considering a manipulator equipped with DC motors (extension to permanent magnet synchronous motors is straightforward using the DC-equivalent model), the electrical power consumption, for each motor, can be computed as: Pj (t) = va,j (t)ia,j (t)

(1)

where Pj is the absorbed electrical power, va,j is the armature tension and ia,j is the armature current for the j-th motor. Based on the equivalent circuit model, the tension is made up of two terms, one related to the copper losses and one to the back electromotive force: va,j (t) = Ra,j ia,j (t) + La,j

d ia,j (t) + kv,j ϑ˙ j dt

(2)

where Ra,j and La,j are the resistance and inductance of the armature of the j-th motor. kv,j is the back electromotive force (EMF) constant and ϑ˙ j is the angular velocity of the j-th motor. The inductive term of the armature tension is not included since it is negligible with respect to the other two terms. In general, the armature current and the torque τ delivered by each motor are related by the

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Fig. 1. Two Degree-of-Freedom balanced planar manipulator.

torque constant ia = τ /kt . As known, numerically the torque constant is equal to the back EMF constant kt = kv . By substituting the current with the torque divided by the torque constant in (1), the following expression is obtained: Pj =

Ra,j 2 ˙ 2 k 2 τj + τj ϑ j kt,j r,j

(3)

where kr,j is the ratio of the j-th gearbox. The efficiency of the gearbox is considered η = 1 for simplicity, but the derivation is straightforward with η < 1. Referring to a two degrees of freedom planar manipulator equipped with revolute joints, some conditions are needed to exhibit linear dynamics. For example, a possible configuration is with the second link balanced (its center-of-mass is coincident with the second revolute joint) in the horizontal plane. A schematic is depicted in Fig. 1. The dynamics are:         I1 + m1 21 + m2 a21 I2 ϑ¨1 F1 0 ϑ˙ 1 τ1 = + (4) τ2 I2 I2 ϑ¨2 0 F2 ϑ˙ 2 where Ij and Fj are, respectively, the total barycentric mass moment of inertia and viscous friction coefficient of the j-th link. m2 is the mass of the second link and a1 the length of the first link, according to the Denavit-Hartenberg convention. From here onwards, the symbol I1∗ = I1 + m1 21 + m2 a21 will be used for the sake of compactness. Substituting (4) into (3) gives the following expression for the powers required: ⎧ 2  Ra,1  ∗ ¨ ⎪ ∗¨ ¨ ˙ ¨ ˙ ˙ ⎪ P I = + I + F + I + I + F ϑ ϑ ϑ ϑ ϑ ϑ 2 2 1 1 2 2 1 1 ϑ1 ⎨ 1 1 1 1 1 2 k2 kt,1 r,1 2  (5) Ra,2  ⎪ ⎪ ⎩P2 = 2 2 I2 ϑ¨1 + I2 ϑ¨2 + F2 ϑ˙ 2 + I2 ϑ¨1 + I2 ϑ¨2 + F2 ϑ˙ 2 ϑ˙ 2 kt,2 kr,2 Clearly, the total power consumption is the sum of the power consumed by each motor.

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Trajectory Requirements

The focus of this work is on PTP motion with fixed final time tf . This means that the trajectory has to satisfy the following boundary conditions: ⎧ ⎧ ϑ1 (0) = ϑin,1 ϑ˙ 1 (0) = 0 ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎨ϑ (t ) = ϑ ⎨ϑ˙ (t ) = 0 1 f f in,1 1 f (6) ˙ ⎪ ⎪ ϑ (0) = ϑ (0) = 0 ϑ 2 in,2 2 ⎪ ⎪ ⎪ ⎪ ⎩ ⎩ ϑ2 (tf ) = ϑf in,2 ϑ˙ 2 (tf ) = 0 where ϑin,j and ϑf in,j are the initial and final values of the angular position, respectively, for the j-th motor. 2.3

Problem Formulation

Since the goal is to minimize the overall energy expenditure, the integral of power has to be minimized. To do so, the problem is rewritten in state-space form, i.e. x˙ = f (x, u, t). Let [ϑ1 ϑ˙ 1 ϑ2 ϑ˙ 2 ] = [x1 x2 x3 x4 ] = x and [ϑ¨1 ϑ¨2 ] = [u1 u2 ] = u. The dynamics of the system are as follows: ⎧ x˙ 1 = x2 ⎪ ⎪ ⎪ ⎨x˙ = u 2 1 (7) ⎪ x ˙ = x 3 4 ⎪ ⎪ ⎩ x˙ 4 = u2 By substituting the symbols of the state-space form, the power required can be rewritten as: P = π1 x22 +π2 x24 +π3 u21 +π4 u22 +π5 x2 u1 +π6 x2 u2 +π7 x4 u1 +π8 x4 u2 +π9 u1 u2 (8) where P = P1 + P2 and the parameters πj are readily obtained from (5). Hence, the optimal control problem at hand is:

tf minimize E = P(x, u, t) dt u∈U 0 (9) subject to (6) x˙ = f (x, u, t) where tf is the prescribed final time and U is the space of the possible controls according to the boundary conditions (6). In this work no constraints, such as torque and velocity limits, are imposed other than the boundary conditions. Let tmin be the minimum time, according to the constraints, to perform the task. In this work, it is assumed that the assigned final time tf is strictly greater than tmin . If tf < tmin , there is clearly no solution. If tf = tmin the solution is the minimum time solution.

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Solution

The problem stated in (9) can be solved using Pontryagin’s maximum principle. The Hamiltonian of the system is: H = P + p f

(10)

where P is given by (8), f by (7) and p = [p1 p2 p3 p4 ] is the vector of co-states. The problem can be solved imposing the boundary conditions given by (6) since for a fixed final-time problem with n states, we can apply 2n boundary conditions. The necessary conditions for strong extrema are provided by Hamilton Canonical Equations. The stationary conditions are: ∂H = 2π3 u1 + π5 x2 + π7 x4 + π9 u2 = 0 ∂u1 ∂H = 2π4 u2 + π6 x2 + π8 x4 + π9 u1 = 0 ∂u2

(11) (12)

while the co-state equations are: ∂H ∂x1 ∂H ∂x2 ∂H ∂x3 ∂H ∂x4

= 0 = −p˙1 −→ p1 = const

(13)

= 2π1 x2 + π5 u1 + π6 u2 = −p˙2

(14)

= 0 = −p˙3 −→ p3 = const

(15)

= 2π1 x2 + π5 u1 + π6 u2 = −p˙4

(16)

By deriving (11) and (12) with respect to time, isolating p˙2 and p˙4 and substituting, respectively, into (14) and (16), it is possible to write them in the following form: ⎤⎡ ⎤ ⎡ ⎤ ⎡ ⎤ ⎡ 0 0 1 0 0 x2 x˙ 2 ⎥ ⎢x˙ 4 ⎥ ⎢ 0 0 0 1 ⎥ ⎢x4 ⎥ ⎢ 0 ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ (17) y˙ = Ay + b → ⎢ ⎣u˙ 1 ⎦ = ⎣α1 α2 α3 α4 ⎦ ⎣u1 ⎦ + ⎣ α9 p1 + α10 p3 ⎦ u˙ 2 α5 α6 α7 α8 u2 α11 p1 + α12 p3 It is worth noticing that p1 and p3 are unknown but constant. The parameters αj are readily obtained from (11), (12), (14) and (16). The solution of (17) is the sum of two terms, a particular solution and the solution of the homogeneous associate system. In mathematical terms y = yst + yom . The particular solution is straightforward by considering yst = const: 0 = Ayst + b → yst = −A−1 b = R [p1 p3 ]

(18)

where in the last step the co-state variables are isolated using the 4 × 2 matrix R. The solution of the associate homogeneous system is: yom (t) = c1 v1 eλ1 t + c2 v2 eλ2 t + c3 v3 eλ3 t + c4 v4 eλ4 t

(19)

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where cj -s are integration constants, vj -s and λj -s are, respectively, the eigenvectors and eigenvalues of A. Once (18) and (19) are obtained, the final solution will be the sum of the two: y = c1 v1 eλ1 t + c2 v2 eλ2 t + c3 v3 eλ3 t + c4 v4 eλ4 t + R [p1 p3 ]

(20)

The integration of y is necessary to obtain the position law. In particular, integrating the first two terms of y gives:

{y}1 dt =

x1 (t) =

(21)

4  1 ck eλk t {vk }2 + r21 p1 t + r22 p3 t + c6 λk

(22)

k=1

x3 (t) =

4  1 ck eλk t {vk }1 + r11 p1 t + r12 p3 t + c5 λk

{y}2 dt =

k=1

where {(·)}n means the n-th component of (·), and rij is the element in the i-th row and j-th column of R. Using the first two terms of vector y defined as in (20) and the position laws given by (21) and (22) it is possible to impose the boundary condition stated in (6). In particular the following 8 × 8 linear system in the unknowns [c1 , . . . , c6 , p1 , p3 ] has to be solved: ⎡ ⎤ ⎡ ⎤ ⎡ ⎤ c1 04,1 V 02 V ⎢ . ⎥ ⎢ .. ⎥ ⎢ ϑin,1 ⎥ ⎥ ⎢ VΛ 02 V ⎥ ⎢ ⎥ ⎢ ⎢ ⎥⎢ = ⎢ ϑin,2 ⎥ (23) ⎢ ⎥ ⎣ VΓ 12 02 ⎦ ⎢ c6 ⎥ ⎥ ⎣ ⎦ ϑ ⎦ ⎣ f in,1 p1 VΛΓ 12 tf V ϑf in,2 p3 where V is the matrix of the eigenvectors of A, Λ = diag(eλ1 tf , . . . , eλ4 tf ) and Γ = diag(1/λ1 , . . . , 1/λ4 ). With 0n,m and 1n,m we indicate the n × m null and the identity matrix1 . Once the constants are obtained, the solution is completely known using equation (21) and (22). By deriving them, also velocity and acceleration laws are known.

4

Results

In this section, numerical examples are provided to show the benefits of the method. First, the solution is compared to a standard law, such as the trapezoidal symmetric velocity law with a 20% acceleration ratio (amount of time with nonzero acceleration over total time tf ). The data used for the comparison are reported in Table 1. The energy consumed in the proposed case is 13.1% less than in the standard case (6.43 J vs 7.40 J). Moreover, the proposed solution is benchmarked with the one provided by a general open source numerical optimal control toolbox, ICLOCS2 [8]. In Fig. 2 a comparison between the proposed solution, the one generated by ICLOCS2 and the standard trapezoidal law is reported. 1

If only one subscript is used, the matrix is considered square.

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Table 1. Manipulator data used in the simulations. Parameter Ij

Fj

Ra,j kt,j

Unit

kg m2 N m s/ rad Ω

j=1

0.21

2 · 10−3

j=2

0.0675 2 · 10−3

kr,j mj aj m

j

ϑin,j ϑf in,j

m

rad

N m/A -

kg

1.0

0.2

50

2.0 0.175 0.0875 0

1.0

0.7

50

4.0 0.225 0

π/2

rad 0 π/2

Fig. 2. The proposed solution is reported in blue. The trapezoidal law is reported in dotted orange line. The benchmark (ICLOCS2) solution is reported in yellow.

Due to the numerical nature of the ICLOCS2 solution, the required solving time is higher than for the herein proposed analytical solution. In particular, the computational time required by ICLOCS2 is 3 s against the 0.008 s of the proposed method (data obtained using a laptop equipped with a Ryzen 5 4500U and 8 GB of RAM). By comparing such figures with the task time tf , the proposed method is deemed real-time capable for this application (0.008 s < tf ), that is an important benefit with respect to ICLOCS2.

5

Conclusions

Reducing the energy expenditure in the manufacturing industry is important to face nowadays challenges. This paper presented a method for deriving optimal trajectories for point-to-point motions in terms of minimum energy expenditure for a two degrees of freedom balanced planar manipulator. This is achieved using Hamilton’s canonical equations, and can be applied to all manipulators that exhibit linear dynamics. The validity of the proposed methodology is demonstrated through numerical results, showing its potential for reducing energy con-

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sumption and its real-time capability. Overall, the method provides a viable solution that can be implemented to reduce energy expenditure in robotic systems without affecting throughput.

References 1. Boscariol, P., Richiedei, D.: Trajectory design for energy savings in redundant robotic cells. Robotics 8(1), 15 (2019) 2. Briot, S., Arakelian, V.: A new energy-free gravity-compensation adaptive system for balancing of 4-DoF robot manipulators with variable payloads. In: The Fourteenth International Federation for the Promotion of Mechanism and Machine Science World Congress (2015 IFToMM World Congress) (2015) 3. Brossog, M., Kohl, J., Merhof, J., Spreng, S., Franke, J., et al.: Energy consumption and dynamic behavior analysis of a six-axis industrial robot in an assembly system. Procedia CIRP 23, 131–136 (2014) 4. Dona, D., Minto, R., Bottin, M., Rosati, G.: A simple but effective approach to generate energy-efficient trajectories of a 2 degree-of-freedom planar manipulator. In: Niola, V., Gasparetto, A., Quaglia, G., Carbone, G. (eds.) IFToMM Italy 2022. Mechanisms and Machine Science, pp. 710–717. Springer, Cham (2022). https:// doi.org/10.1007/978-3-031-10776-4 82 5. Hagn, U., et al.: The DLR MIRO: a versatile lightweight robot for surgical applications. Ind. Robot Int. J. 35, 324–336 (2008) 6. Kim, Y.J.: Design of low inertia manipulator with high stiffness and strength using tension amplifying mechanisms. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5850–5856. IEEE (2015) 7. Lenzo, B., Zanotto, D., Vashista, V., Frisoli, A., Agrawal, S.: A new constant pushing force device for human walking analysis. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 6174–6179. IEEE (2014) 8. Nie, Y., Faqir, O., Kerrigan, E.C.: ICLOCS2: try this optimal control problem solver before you try the rest. In: 2018 UKACC 12th International Conference on Control (CONTROL), pp. 336–336 (2018) 9. Scalera, L., Carabin, G., Vidoni, R., Wongratanaphisan, T.: Energy efficiency in a 4-DoF parallel robot featuring compliant elements. Int. J. Mech. Control 20(02), 49–57 (2019) 10. Shieh, W.B., Chen, D.Z.: Design of a gravity-balanced general spatial serial-type manipulator. J. Mech. Robot. 2, 031003-1 (2010) 11. Vidussi, F., Boscariol, P., Scalera, L., Gasparetto, A.: Local and trajectory-based indexes for task-related energetic performance optimization of robotic manipulators. J. Mech. Robot. 13(2) (2021)

Reducing Energy Consumption and Driving Torque in an Underactuated Robotic Arm Through Natural Motion Jason Bettega , Dario Richiedei , Iacopo Tamellin(B)

, and Alberto Trevisani

Department of Management and Engineering (DTG), University of Padova, Stradella San Nicola 3, 36100 Vicenza, Italy {jason.bettega,dario.richiedei,iacopo.tamellin, alberto.trevisani}@unipd.it

Abstract. Responsible energy consumption is the SDG12 of the United Nation 2030 Development Agenda. Industry is one of the main energy consumers and unresponsible energetic usage affects both the environmental impact and the economic cost of the products. Innovating industry is a key factor to tackle these aspects as pursued through the SDG9. Robots are widely used in the massproduction industry to perform repetitive pick-and-place tasks. The high number of operations performed over the productive cycle by robots suggests that reducing the energetic consumption and the torque required is fundamental to save energy. In this light, this paper proposes a novel method to lower the energy consumption and the driving torque during the pick-and-place operations of a non-minimum phase underactuated flexible joints robotic arm, while ensuring good performances in terms of trajectory tracking. The method relies on the dynamic structural modification of the existing system to obtain a mechanical design that exploits the natural motion of the robotic arm. Keywords: SDG9 · SDG12 · Energy reduction · Driving torque reduction · Natural motion · Multibody Dynamics

1 Introduction 1.1 Motivations and State of the Art Energy saving and wise use of resources in mechatronic systems is currently an issue of huge importance to achieve efficient production systems, while preserving high productivity, high volumes and fast dynamics. For this reason, a recent research trend that is gaining a growing attention is the so-called “Eco-mechatronics” [1] and different solution approaches have been proposed. For example, it can be achieved both through a proper operation of the system, such as energy-optimal motion planning and scheduling techniques [2], and through the optimal selection and design of the machine components. The latter can involve a lightweight design of the mechanism links, the wise selection of © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 89–96, 2023. https://doi.org/10.1007/978-3-031-32439-0_11

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the electro-mechanical components [3, 4], or the addition of elastic elements behaving as energy accumulators [5]. The use of springs is an approach that has attracted attention in the execution of repetitive tasks, thanks to their capability to store and release energy. Different configurations or computational methods are proposed for fully actuated mechanisms and robots, such as in [5, 6] for reducing electric energy, or in [7] for reducing the driving torque. All the mentioned papers refer to fully actuated mechanisms, i.e., when the number of independent control forces is equal to the number of system degrees of freedom (DOF). In contrast, the lightweight design of mechanism or the presence of passive joints (that are widely adopted to reduce moving masses) make the system underactuated, meaning that some DOFs are not actuated. Besides introducing several challenges in motion planning and control, optimal design of these mechanisms is not straightforward. For example, the inverse dynamic problem, that is widely exploited to get the cost function for energy optimal design [5], cannot be often formulated and solved as an algebraic problem, as it is in fully actuated mechanism. In contrast, inverse dynamics in underactuated mechanism requires the solution of an algebraic and differential problem, unless the system is flat [8]. The problem is even more severe if the underactuated mechanism is non-minimum phase: the inverse dynamic problem is diverging due to an unstable internal dynamics [8]. Due to these features, the issue of optimal mechanical design is challenging and requires a different approach that does not require the explicit formulation of a cost function evaluating the torque of the energy for executing the desired motion. The concept of “natural motion” is a good candidate approach to accomplish this task. Although there is not a unique definition of natural motion, and this concept is often confused in the literature of energy optimal design, a representative definition is the motion arising from matching the vibrational property of the system with those of the task to execute. For example, in [9] this idea is translated into designing a fully actuated system such that its free-vibration response matches the task frequency and amplitude of oscillation; consequently, after releasing the robot from the starting position, it moves towards the end position, where the end-effector stops at the given time for the task. Other interesting formulations of the general idea of natural motion are also proposed in [10–12]. 1.2 Contributions of This Paper In this paper, the challenging case of a non-minimum phase underactuated multibody system is considered, in the execution of a high-speed pick-and-place task. Pick-andplace tasks cover huge importance in the field of robotics and industrial automation, due to their exploitation in the manufacturing plants [13]. Moreover, given the high number of cycles per minute, reducing the required driving torque and absorbed energy, without altering the trajectory tracking performances, can lead to huge benefits in the overall production in term of throughput and carbon footprint. A periodic, albeit non-harmonic, motion is assumed, as usually done in underactuated mechanisms. The idea of natural motion is translated into a Dynamic Structural Modification (DSM) problem aimed at modifying some physical features of the system (i.e., the modification of the torsional springs and of the masses composing the system) to match the system two eigenfrequencies with the two dominant harmonics of

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the reference trajectory. Additionally, given their relevance in representing the motion of vibrating system, the related mode shapes are assigned as well through the DSM problem. These features of the proposed method make it original compared to the state of the art.

2 System Model A planar two-DOFs underactuated robotic arm lying in the vertical plane is considered, as shown in Fig. 1. An electric DC (direct current) motor drives joint (A) through the torque C m . The absolute rotations of the actuated link and of the passive link with respect to the vertical configuration are respectively denoted with θ1 and θ2 . The link connected to the output shaft of the motor has length l1 , mass m1 and moment of inertia J1 (defined with respect to A). The second link has length l2 , mass m2 and a moment of inertia J2 (defined with respect to B). The moments of inertia of the motor and of the rigid coupling are denoted with Jm and Jd , respectively. Additionally, a lumped mass mB is assumed to be placed in B. The actuated link is connected to the frame through a rotational spring whose stiffness is k1 , while two linear springs are used to couple the two links, obtaining an equivalent rotational spring with rotational stiffness k2 . In this preliminary study, it is assumed that the spring is massless, with negligible damping, and behaves as a zero free-length spring (at least in the range of motion of interest). The viscous friction coefficients are denoted through c11 , c12 , c21 and c22 (g is the gravity acceleration). Let us define, for brevity of notation, J1,eq = Jm + Jd + J1 and m2,eq = m2 + mB . The nonlinear model of the system under investigation (that is used as a system digital twin in simulating the system response and evaluating torque and energy) is:       1 θ¨1 c11 c12 θ˙1 J1,eq + m2,eq l12 2 m2 l1 l2 cos(θ1 − θ2 ) + 1 θ¨2 c21 c22 θ˙2 J2 2 m2 l1 l2 cos(θ1 − θ2 )    k + k2 −k2 θ1 + 1 −k2 k2 θ2    1  1 m2 l1 l2 sin(θ1 − θ2 )θ˙22 − 2 m1 + m2,eq g l1 sin(θ1 ) 2 = 1 ˙2 + − 21 m2 g l2 sin(θ2 ) 2 m2 l1 l2 sin(θ1 − θ2 )θ1   1 (1) + Cm 0 With the purpose of energy optimal design, the linearized model is adopted to exploit the concepts of modal analysis by linearizing the dynamics around the vertical equilibrium condition, i.e., θ1 = θ2 = 0 (and by neglecting damping):    J1,eq + m2,eq l12 21 m2 l1 l2 θ¨1 1 J2 θ¨2 2 m2 l1 l2  1      −k2 θ1 1 k1 + k2 + 2 m1 + m2,eq g l1 = (2) + Cm 1 −k2 k2 + 2 m2 g l2 θ2 0

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The system natural frequencies ωn,1 , ωn,2 and its mode shapes u1 , u2 can be determined through the solution of the eigenvalue problem:  2 −ωn,i M + K ui = 0, i = 1, 2 (3) where M ∈ R2×2 and K ∈ R2×2 are the mass and stiffness matrices respectively, as inferred from Eq. (2).

Fig. 1. Sketch of the underactuated robotic arm.

3 The Proposed Method This paper exploits the concepts of Dynamic Structural Modification (DSM), i.e., the modification of elastic and inertial physical parameters, to make the eigenstructure of the system “closer” to the one required by the reference trajectory set for the horizontal displacement of the tip x e , where it is supposed to be placed an end-effector. The idea is to modify the two system natural frequencies to match the dominant harmonics of the periodic reference profile adopted in the repetitive task. Ideally, in this way the modified system should be capable of exploiting its free evolution to perform the pick-and-place task. In practice, due to the presence of a non-harmonic reference, of friction, of nonlinearities, and of the underactuation, zero-torque motion is no possible. Nonetheless, by exploiting the large magnitude of the receptances about the system natural frequencies, the desired displacement is expected to be performed with low actuation forces, and hence low energy consumption. The reference displacement xedes (t), with period TF = 2π ωF−1 , is approximated through the truncated Fourier Series: xedes (t)

 A0 +

2

k=1

Ak cos(kωF t + φk )

(4)

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where φk and Ak denote the phase and the amplitude of each harmonic, respectively. The linearity of the system in Eq. (2) allows to split the DSM problem into more subproblems, each one addressing one of the 2 dominant harmonic components of xedes (t). Indeed, since the linearized system features 2 DOFs, 2 mode shapes are assignable through DSM [14]. des , k = 1, 2 The DSM problem for assigning 2 desired natural frequencies ωn,k together with the desired mode shapes udes k , k = 1, 2 is formulated through an optimization problem that ensures its solvability for all the choices of the modification matrices. Further, DSM is usually adopted for assigning poles and mode shapes in vibrating systems, with regard to undamped ones. Indeed, the application of DSM is significantly simplified, and improved in term of solvability and solution reliability, by neglecting damping and by considering harmonic motion [14]. In this scenario, the DSM problem can be solved as an algebraic optimization. The problem is therefore formulated through the following minimization:   2 2

Ak des − ωn,k (M + M(p)) + (K + K(p)) udes min k (y) p,y Amax k=1

(5)

s.t. pL ≤ p ≤ pU , yL ≤ y ≤ yU where the DSM subproblem regarding the k-th harmonic is weighted accordingly to the amplitude Ak of such harmonic in the Fourier Series in Eq. (4) and Amax = max(Ak ). The Structural Modification (SM) matrices are M(p) and K(p) that depend on the N p design variables collected in vector p. The design variables are constrained to belong to a feasible domain defined through the lower and upper bounds, pL and pU to ensure the technical and economical feasibility of the found solution. Additionally, the mode shapes are partially assigned through vector y and its lower and upper bounds, yL and yU . The nonlinear non-convex problem in Eq. (5) is solved by exploiting the approach proposed by the Authors in [14], so additional details are here omitted for brevity.

4 Numerical Assessment Let us consider the model of the underactuated robotic arm proposed in Sect. 2. The value of the system parameters are reported in Table 1. In this test case the desired reference trajectory is obtained by considering as pick location x e = −0.1166 m while the place location is x e = + 0.1166 m. These positions are those achieved by a rigid robotic arm with length l 1 + l 2 and an opening angle equal to 20°. The overall motion time for the symmetric pick-and-place cycle is T F = 0.6 s and a 7th degree polynomial timing law is assumed. The robotic arm under consideration is actuated through a DC motor whose electric parameters are: torque constant k t = 1 Nm/A, back electromotive force constant k b = 1 Vs/rad, armature resistance R = 1  and armature inductance L = 1 mH. The Fast Fourier Transform of the required motion profile yields to two dominant harmonics at the frequencies ωF = 2π 1.67 rad/s and 3ωF = 2π 5 rad/s, whose amplitudes are respectively A1 = 0.1296 m and A2 = 0.0126 m. Henceforth, the DSM algorithm in Eq. (5) is adopted to make the system natural frequencies matching those harmonics.

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Parameter

Original value

DSM constraints

Modified value

l 1 , l 2 [m]

0.17; 0.1705

–

0.17; 0.1705

m1 [kg]

0.05

[−0.033; 0.042]

0.0917

m2 [kg]

0.021

[−0.011; 0.018]

0.0107

m2,eq [kg]

0.1960

–

0.1857

J 1,eq [kgm2 ]

0.0059

[−0.001; 0.005]

0.0084

J 2 [kgm2 ]

2.03e-4

–

1.04e-4

k 1 [N/m]

0.0886

[−0.088; 1.772]

1.0360

k 2 [N/m]

0.1772

[−0.088; 0.443]

0.0886

c11 , c12 , c21 , c22 [Ns/rad]

12e-4; 4e-4; 4e-4; 3e-4

−

12e-4; 4e-4; 4e-4; 3e-4

Further, the mode shapes are partially assigned, within some admissible bounds, such that the first mode shape mimics a rigid mode with θ1 = θ2 . The modifiable parameters are assumed to be: J d , m1 , m2 , k 1 , k 2 . Obviously modifying m2 indirectly affects also J 2 and m2,eq . The optimal SMs are listed in Table 1. The driving torques, required by the original and modified systems, are shown in Fig. 2: the RMS torque decreases from 0.23 Nm to 0.08 Nm (−65.2%) and simultaneously the absolute maximum torque decreases from 0.38 Nm to 0.24 Nm (−38.8%). Clearly, the RMS value is the most significant one since it drives the motor sizing [3, 4] and is a meaningful measure of the electric energy consumption as well. The effectiveness in trajectory tracking for both the original and modified system is shown in Fig. 3.

Fig. 2. Required driving torque for the original and modified systems.

The latter is also explicitly evaluated over a cycle, by assuming the most “energivorous” case of a “non-regenerative drive”. The following model [3, 5] enables to compute the non-regenerative electrical energy consumption of the system (with: W = Vi being

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the electric power, that is not accounted for in the integral when W < 0, since it is assumed to be dissipated, and hence wasted, in a resistance):

T

T R 2 kb L dCm (t) ˙ θ C Eel = C dt + + (W (t))W ≥0 dt = (t) (t)C (t) (t) m m m m kt kt2 kt2 dt 0 0 W ≥0 (6) The electrical energy required for performing one cycle is equal 0.162 J for the original system, while remarkably decreases up to 0.067 J for the modified system. Hence the proposed method enables to reduce the energy consumption of the 58.6%.

Fig. 3. Commanded and simulated trajectories.

5 Conclusions This work proposes a method to design an underactuated robotic arm to lower its energy consumption and driving torque by exploiting the concept of natural motion. The design strategy is based on the DSM adopted to assign the system natural frequencies and mode shapes in order to match the harmonics of the periodic motion profile executed during the pick-and-place operation of the robot. The problem is solved through the optimization of the SM problem for the undamped system. Once the optimized mechanical design has been defined, the driving torques have been computed and applied to both the original and modified systems. The obtained numerical results, with reference to the model of a laboratory prototype, confirm the effectiveness of the proposed method, indeed the energy consumption and the required driving torque are remarkably reduced. These preliminary results highlight the importance of the mechanical design oriented to reduce energy consumption, as required by the SDG9 and SDG12.

References 1. Hehenberger, P., Habib, M., Bradley, D.: EcoMechatronics: Challenges for Evolution, Development and Sustainability, 1st edn. Springer Nature, Heidelberg (2022)

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2. Boscariol, P., Caracciolo, R., Richiedei, D., Trevisani, A.: Energy optimization of functionally redundant robots through motion design. Appl. Sci. 10(9), 3022 (2020) 3. Boscariol, P., Richiedei, D.: Energy optimal design of servo-actuated systems: a concurrent approach based on scaling rules. Renew. Sustain. Energy Rev. 156, 111923 (2022) 4. Boscariol, P., Caracciolo, R., Richiedei, D.: Does inertia matching imply energy efficiency? In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 282–289. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-87383-7_31 5. Richiedei, D., Trevisani, A.: Optimization of the energy consumption through spring balancing of servo-actuated mechanisms. J. Mech. Des. 142(1) (2020) 6. Carabin, G., Palomba, I., Wehrle, E., Vidoni, R.: Energy expenditure minimization for a delta2 robot through a mixed approach. In: Kecskeméthy, A., Geu Flores, F. (eds.) ECCOMAS 2019. CMAS, vol. 53, pp. 383–390. Springer, Cham (2020). https://doi.org/10.1007/978-3030-23132-3_46 7. Hill, R.B., Briot, S., Chriette, A., Martinet, P.: Minimizing input torques of a high-speed five-bar mechanism by using variable stiffness springs. In: Arakelian, V., Wenger, P. (eds.) ROMANSY 22 – Robot Design, Dynamics and Control. CICMS, vol. 584, pp. 61–68. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-78963-7_9 8. Bettega, J., Richiedei, D., Tamellin, I., Trevisani, A.: Model inversion for precise path and trajectory tracking in an underactuated, non-minimum phase, spatial overhead crane. J. Vibrat. Eng. Technol. 1–17 (2022) 9. Barreto, J.P., Corves, B.: Matching the free-vibration response of a delta robot with pickand-place tasks using multi-body simulation. In: 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE), pp. 1487–1492. IEEE, Munich (2018) 10. Iwamura, M., Schiehlen, W.: Minimum control energy in multibody systems using gravity and springs. J. Syst. Des. Dyn. 5(3), 474–485 (2011) 11. Nasiri, R., Khoramshahi, M., Ahmadabadi, M.N.: Design of a nonlinear adaptive natural oscillator: towards natural dynamics exploitation in cyclic tasks. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3653–3658. IEEE, Daejeon (2016) 12. Khoramshahi, M., Nasiri, R., Shushtari, M., Ijspeert, A.J., Ahmadabadi, M.N.: Adaptive natural oscillator to exploit natural dynamics for energy efficiency. Robot. Auton. Syst. 97, 51–60 (2017) 13. Scalera, L., Boscariol, P., Carabin, G., Vidoni, R., Gasparetto, A.: Enhancing energy efficiency of a 4-DOF parallel robot through task-related analysis. Machines 8(1), 10 (2020) 14. Richiedei, D., Tamellin, I., Trevisani, A.: Simultaneous assignment of resonances and antiresonances in vibrating systems through inverse dynamic structural modification. J. Sound Vib. 485, 115552 (2020)

Online vs Offline Calibration of 5 DOFs Robotic Manipulators Francesco Cosco(B) , Michele Perrelli , Rocco Adduci , Arnaldo Michele Cerminara, Giuseppe Carbone, and Domenico Mundo Department of Mechanical, Energy and Management Engineering, University of Calabria, Arcavacata Di Rende, 87036 Arcavacata, Italy [email protected]

Abstract. Developing reliable and sustainable robots with an emphasis on affordability supports the Sustainable Development Goal 9 (SDG9) set by the United Nations by making access to modern industrial technology more equitable. In this context, achieving and maintaining adequate levels of absolute accuracy is paramount for modern robotic applications and crucial to avoid any waste of materials and energy. For this reason, the literature widely addresses how to obtain an optimal estimation of the forward kinematic model by means of various calibration procedures. In this work, a canonical offline approach, based on the nonlinear fitting of the Denavit–Hartenberg (DH) parameters, is compared with a recursive online estimator. The performance of the proposed approach is numerically analyzed and validated by considering as case of study a 5 Degrees-Of-Freedom (DOFs) manipulator. The online iterative approach enables to monitor and to update the accuracy of the manipulator, allowing the user to stop the procedure once the target accuracy values are reached. The obtained results confirm the advantages of the online procedure, which allows to optimize both computational and human resources. Keywords: SDG9 · Parameter Estimation · Robotics · Calibration · Recursive Identification

1 Introduction The shift towards offline programming as a more effective alternative to online programming has driven research on the economic impact of calibration. This focus has led to a deeper understanding of the importance of repeatability and accuracy in a robotic manipulator [1]. Robot manufacturers, such as KUKA, ABB, and Fanuc, offer dedicated software allowing the user to create advanced digital replicas of the production environment and to effectively simulate the manipulator tasks upfront, without requiring the interruption of the production process [2]. The development of reliable and sustainable robots, possibly with a focus on making their usage more affordable may contribute to the overall sustainability goals aiming to make more equitable the access to modern industrial technology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 97–104, 2023. https://doi.org/10.1007/978-3-031-32439-0_12

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Kinematic calibration is a key process in modern robotics, as it allows for increasing flexibility by abstracting the planning activities and sharing the planned actions among multiple robotic units, even if different. The control logic of each robot is then left with the responsibility of meeting the demanded tasks. In this context, it is crucial to adopt an accurate model of the kinematic motion of the manipulator, such that the controller may achieve the required levels of accuracy [3, 4]. There are two main approaches to calibrate a manipulator model. The offline approach involves collecting a set of measuring poses and processing the data in a separate identification step. The online approach, on the other hand, combines the data collection and identification into one continuous process. As a particular case of the Bayesian estimation methods, the proposed online calibration allows to continuously assess the accuracy of the manipulator in real-time, allowing the calibration to be stopped when the desired targets are achieved. Several researchers have been addressing this topic. For example, Shammas and Najjar propose a kinematic calibration as based on Bayesian inference, [5]. Jiang and Huang propose an identification of kinematic parameters by using equalized singular values, as reported in [6]. Wang and Song propose an optimization approach for robot-world and hand-eye calibration, as outlined in [7]. Authors of [8] and [9] propose an improved kinematic calibration method based on product of exponential formula. This work proposes a comparison of a canonical offline approach using nonlinear fitting of DH parameters with a recursive online estimator. The two approaches are compared by considering a specific case of study for a 5 DOF manipulator. In particular, Sect. 2 provides the analytical formulation of the considered manipulator model, whereas Sects. 3 and 4 focus respectively on the implementation of both the offline and online kinematic calibration of open loop manipulators.

2 Kinematic Calibration of Open-Loop Manipulators Accuracy and precision of modern robots rely on using modern model-based control algorithms, as they permit better performance. In this context, the usage of advanced integrated design environments is becoming popular, as it allows the user to plan automated activities more naturally, even decoupling the task itself from the knowledge of which robot will finally execute the tasks. For all these reasons, modern robotics heavily relies on using advanced modeling techniques. Among all, forward kinematics aims to define a model able to predict the spatial motion of each link within the manipulator chain, with particular attention to the pose obtained by the end-effector as a function of the joint variables. The kinematic calibration of a robotic manipulator is a crucial process as it allows to increase precision and accuracy. In fact, the accuracy of a forward kinematic model, intended as the capability of reaching any position within the working space within a given tolerance, is affected by several factors such as production tolerances, joint clearances, and deformability of the linkages. Any identification process is generally targeted on the particular model used. For the purposes of this work, the forward kinematic model was used, which enables to compensate for the deviations of the model due to the geometrical production errors. Therefore, although other phenomena may impact on the

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overall accuracy, their effects will be intrinsically minimized and compensated as geometrically equivalent compensations. The remainder of the section briefly summarizes the fundamentals of the forward kinematic modelling approach used in this work. 2.1 Open-Loop Forward Kinematic Modelling The forward kinematic model of a manipulator is usually expressed as the product of a set of relative transformations, according to: TBE

n         B q, ξ = T0 ξB Ti−1 qi , ξi TnE ξE i

(1)

i=1

where Ti−1 i , is the homogenous transformation matrix representing the relative position between the i-th joint and the previous one, as a function of the corresponding joint variable, qi , and a vector of geometrical parameters, ξi . TB0 is needed to account for possible misalignments between the first motor axis and the fixed frame at the base of the robot. Similarly, TnE is added to compensate for possible misalignments of the endeffector measuring system. It is worth noting that TB0 and TnE are constant with respect to the joint variables, thus they only depend on their respective geometrical parameters, ξB and ξE . The maximum number of independent kinematic parameters is related to the manipulator architecture, serial or parallel, as well as to the number and type of joints in the robotic structure. For an open-chain (serial) structure, the above number can be calculated as n = 4R + 2P + 6

(2)

where R and P are the number of rotational and prismatic joints respectively [10]. The parametric formulation of each of the above-mentioned relative transformations relies on a combination of the three elementary screw transforms: ⎡ ⎤ 1 0 0 a ⎢ 0 cos(α) − sin(α) 0 ⎥ ⎥ TX (α, a) = ⎢ ⎣ 0 sin(α) cos(α) 0 ⎦; ⎡

0

0

0

1

⎤ cos(β) 0 sin(β) 0 ⎢ 0 1 0 b⎥ ⎥ TY (β, b) = ⎢ ⎣ − sin(β) 0 cos(β) 0 ⎦; 0 0 0 1 ⎡ ⎤ cos(θ ) − sin(θ ) 0 0 ⎢ sin(θ ) cos(θ) 0 0 ⎥ ⎥. TZ (θ, d ) = ⎢ ⎣ 0 0 1d⎦ 0

0

(3)

01

Following the widely accepted Denavit-Hartenberg (DH) convention [11], the transformation between two consecutive joints is notably obtained by a sequence of two screw

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displacements: the first acting along the line of action of the current joint, which is canonically aligned to the z-axis of the reference frame; the second acts to bring the resulting frame with the z-axis aligned to the following joint. The DH transform is expressed as: Ti−1 DHi (θi , di , αi , ai ) = TZ (θi , di )TX (αi , ai ).

(4)

The joint variable, qi , affects either θi or di , depending on whether the joint is of revolute or prismatic type. For a revolute joint, we finally obtain: i−1 Ti−1 DHi (qi , ξi ) = TDHi (θi + qi , di , αi , ai ),

with xi = {θi , di , αi , ai }.

(5)

The application of the DH model is known to satisfy all the requirements for obtaining a proportionate, complete and minimal model [12], except in cases where two or more successive actuation axes are parallel by design. To avoid numerical instabilities, the modified DH convention should be adopted [1, 13], which consists in adding a third rotation parameter, β, around the Y-axis, instead of the translational one along the z-axis, as expressed in:   (6) qi , ξi = TZ (θi + qi , 0)TX (αi , ai )TY (βi , 0), ξi = {θi , αi , ai , βi } AMDH i

3 Nonlinear Parameter Identification For the purposes of this work, the use of a position measuring device is considered, in combination with a marker, composed of a set of K fiducial points, arranged in a fixed precise geometry, and attached to the end-effector. The manipulator is driven over a set of m positions, scattered along the working-space, and the measuring device is used to acquire the position of each fiducial points, pk , within the marker. The position of each fiducial point can be transformed from the local homogeneous coordinates, pk , to the corresponding global homogeneous coordinates, Pk,j , associated to the jth configuration, by relying on the forward kinematic model defined in Eq. (1):  Pk,j = T qj , ξ pk (7) where qj and x represent respectively the joint variables and the full set of the geometrical parameters.  The nonlinear function h qj , ξ can be defined by exploiting the relation in Eq. (6), such to extract the global cartesian coordinates of each point, and assemble them in a more compact vectorial form:  T T

Mj = P1,j . . . PK,j = X1,j Y1,j Z1,j . . . XK,j YK,j ZK,j = h qj , ξ . (8) A system of m measurement equations can be assembled by applying Eq. (7) to a set of m configurations of the manipulator:  Mj = h qj , ξ + ν j , with j = 1 . . . m (9)

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where ν represents the additive white noise depending on the accuracy of the considered measuring device. The identification of the parameters is obtained by minimizing the cost function, J: J =

m   T     Mj − h qj , ξ Mj − h qj , ξ ,

(10)

j=1

which represent the sum of the squared distance between the predicted and measured position of each fiducial markers, for each measured configuration. The minimization is achieved by means of a nonlinear least squares (NLLSQ) algorithm. The accuracy of the calibrated manipulator is usually assessed by evaluating the first and the second moments of the gaussian distribution of the measuring errors, Ed :    Ed = Mj − h qj , ξ , j = 1 . . . m (11)

4 Recursive Nonlinear Least-Squares Identification (r-NLLSQ) Considering the first-order Taylor expansion of the measuring function h, already introduced in Eq. (7), a linearization of the noised measuring equation can be defined as:   ∂h qk , ξ (12) Mk = Hk ξ + ν k , with : Hk = ∂ξ where ν k is a zero-mean random vector with covariance Rk . The estimation of the parameters, ξ, can be attempted by adopting a recursive least squares estimator scheme [14]. Whenever a new measurement, Mk , is available, the estimate of the parameters ξk , as well as the estimation-error covariance Pk , are updated as follows:  −1 Kk = Pk−1 HkT Hk Pk−1 HkT + Rk

(13)

   ξk = ξk−1 + Kk Mk − h qk , ξk−1

(14)

Pk = (I − Kk Hk )Pk−1 (I − Kk Hk )T + Kk Rk KkT

(15)

After evaluating the gain matrix, Kk , Eq. (14) can be used to update the parameters: the innovation terms are computed as the product of the gain by the difference between expected and true measures. Similarly, in Eq. (15) the covariance associated with the parameter estimation is updated by mixing it opportunely with the covariance of the measures.

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a)

b)

Fig. 1. A 5dof manipulator: a) an example of a commercial product; b) the D-H kinematic model at its reference configuration.

5 A Case of Study for a 5 DOFs Manipulator For the numerical validation we considered the architecture of a 5 DOFs manipulator, as depicted in Fig. 1. Using the modelling approach summarized in Sect. 2.1, the forward kinematic model of the considered manipulator was obtained as: mDH mDH DH DH A3 A4 A5 TE TBE = TB ADH 1 A2

(16)

where the transformations TB and TE were computed according to the following: TB = TX (αB , aB )TY (βB , bB )TE = TY (βE , bE )

(17)

Table 1 gives an overview of all the nominal parameters used to compose the forward kinematic model described in Eq. (14), showing also the 26 calibration parameters considered for the identification, as prescribed in Eq. (2). A realistic manipulator model was obtained by randomly generating the parameters values and used to simulate the collection of 120 measuring configurations, chosen to randomly span over the reachable workspace. For each scenario, identification of the manipulator was carried out by means of the nonlinear least squares (NLLSQ) identification, and its recursive variants (r-NLLSQ), discussed respectively in Sects. 3 and 4. The full measuring stage was simulated considering a medium white noise level (σ = ±0.032mm). The corresponding results are reported in Fig. 2. Figure 2 shows the comparative results obtained by means of a recursive identification scheme, in combination with very precise calibration instrumentations. As expected, the accuracy of the manipulator improves asymptotically during the calibration process, approaching a precision level which tends to the same order of magnitude of the emulated measuring device. Moreover, it can be noted that a significantly lower number of configurations is needed to achieve an accuracy comparable to the one provided by the calibrating device.

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Table 1. Geometrical parameters according to the reference configuration obtained as the sum of the nominal values and the estimated compensation. α

a

β

b

TB

θ

0 + ξ1

0 + ξ2

0+ξ3

0+ξ4

A1 (q1 )

q1 + ξ5

d1 + ξ6

π +ξ 7 2

0 + ξ8

–

–

A2 (q2 )

q2 + ξ9

-

0 + ξ10

a2 + ξ11

0 + ξ12

–

A3 (q3 )

q3 + ξ13

-

0 + ξ14

a3 + ξ15

0 + ξ16

–

A4 (q4 )

q4 + π2 + ξ17

0 + ξ18

π +ξ 19 2

0 + ξ20

–

–

A5 (q5 )

q5 + ξ21

d5 + ξ22

0 + ξ23

0 + ξ24

–

TE

d

0 + ξ25

0 + ξ26

Fig. 2. Accuracy of the recursive least-square identification with the medium noise level.

6 Conclusions In this work, a recursive online estimation method was proposed to enable online iterative monitoring and updating of the accuracy of a robotic manipulator. A comparison against a non-iterative approach, confirmed the capability of the proposed method to minimize the computational and human resources needed to achieve the system calibration. Despite the traditional offline method is achieving higher accuracy, the study shows that the recursive online approach can also produce effective calibration results, especially in noisy conditions. This opens up the possibility for a more sustainable industry by optimizing the computational and human resources that are required for manipulator calibration.

References 1. Mooring, B.W., Roth, Z.S., Driels, M.R.: Fundamentals of Manipulator Calibration, 2nd edn. Wiley, Hoboken (1991)

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2. Swevers, J., Verdonck, W., De Schutter, J.: Dynamic model identification for industrial robots. IEEE Control Syst. Mag. 27(5), 58–71 (2007) 3. Donnici, M., Lupinacci, G., Nudo, P., Perrelli, M., Danieli, G.: Using navi-robot and a CT scanner to guide biopsy needles. Int. J. Autom. Technol. 11(3), 450–458 (2017) 4. Perrelli, M., Gatti, G., Iocco, M., Danieli, G.: Upper and lower limbs rehabilitation: DARTAGNAN, an alternative solution to exoskeletal robots. In: Arakelian, V., Wenger, P. (eds.) ROMANSY 22 – Robot Design, Dynamics and Control. CICMS, vol. 584, pp. 400–408. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-78963-7_50 5. Shammas, E.: Najjar, S: Kinematic calibration of serial manipulators using Bayesian inference. Robotica 36(5), 738–766 (2018) 6. Wang, X., Song, H.: Optimal robot-world and hand-eye calibration with rotation and translation coupling. Robotica 40(9), 2953–2968 (2022) 7. Chang, C., Liu, J., Ni, Z., Qi, R.: An improved kinematic calibration method for serial manipulators based on POE formula. Robotica 36(8), 1244–1262 (2018) 8. Luo, R., Gao, W., Huang, Q., Zhang, Y.: An improved minimal error model for the robotic kinematic calibration based on the POE formula. Robotica 40(5), 1607–1626 (2022) 9. Jiang, Z., Huang, M.: Stable Calibrations of Six-DOF Serial Robots by Using Identification Models with Equalized Singular Values. Robotica 39(12), 2131–2152 (2021) 10. Craig, J.J.: Introduction to Robotics Mechanics and Control, 4th edn. Pearson, London (2017) 11. Denavit, J., Hartenberg, R.S: A kinematic notation for lower-pair mechanisms based on matrices. ASME J. Appl. Mech. 77, 215–221 (1955) 12. Everett, L.J., Hsu, T.: The theory of kinematic parameter identification for industrial robots. J. Dyn. Syst. Meas. Contr. 110(1), 96–100 (1988) 13. Hayati, S., Mirmirani, M.: Improving the absolute positioning accuracy of robot manipulators. J. Robot. Syst. 2(4), 397–413 (1985) 14. Simon, D.: Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches. John Wiley & Sons, Hoboken (2006)

Task-Specific Synthesis and Design of a Mobile Six-DoF Hexa Parallel Robot for Weed Control Tim Sterneck(B) , Jannik Fettin , and Moritz Schappler Institute of Mechatronic Systems, Leibniz University of Hannover, Hannover, Germany {tim.sterneck,jannik.fettin,moritz.schappler}@imes.uni-hannover.de Abstract. In automated weed control, kinematics of varying complexity are required for tool guidance, depending on the weeding principle. Mechanical tools in particular require several degrees of freedom (DoF) in order to operate in a plant-specific way, which can be realized by parallel kinematic machines due to their dynamic performance. The development of a kinematic structure under task-specific requirements is done using combined structural and dimensional synthesis and a detailed manual design stage, which leads to a new variant of the six-DoF Hexa robot. Keywords: SDG6 control

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Introduction and State of the Art

For most crops in agriculture weed control effort is required due to the competition for biological resources. Still the most widely used approach is applying herbicides, which are economical but come with downsides, as they are usually non-selective and partly inefficient. Herbicides and their degradation products can even infiltrate unintended areas as water bodies, which should be avoided with respect to negative effects on human and animal health. Using automated robotic systems is a promising alternative since manual weeding is expensive. In this paper, we are focusing on the kinematic aspect of robotics for tool Fig. 1. Simplified scheme handling rather than on the topic of mobile robots of the presented weeding e.g. carrying the weeding tools, as shown in Fig. 1. system (rear view) In the following, we refer to this as parallel kinematic machine (PKM). Weeding robots can be categorized according to the operating principle of the weeding tool (mechanical, chemical, electric discharge, laser irradiation, water jet treatment), and accordingly different requirements exist for tool handling. c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 105–114, 2023. https://doi.org/10.1007/978-3-031-32439-0_13

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In numerous applications, the movement of the carrier system is used, so no further kinematics is required for tool positioning. The “Ecorobotix ARA” [1] uses a large array of individually controllable nozzles to fine-dose herbicides, a similar principle is applied in [2]. There are also systems for weed removal by laser irradiation, as in the “Carbon Robotics LaserWeeder” [3], which works without an additional tool positioning. [4] shows more examples of mechanical weeding, both with rotating tools, and completely passive. Selective weeding using mechanical tools requires at least one degree of freedom (DoF) for tool positioning. “Bonirob”, a multifunctional mobile agriculture robot introduced in [5] was used for weeding with fixed nozzles and additional linear actuated stamps. Other systems with one-DoF tool positioning include the “Naio Technologies OZ” [6] with various tools, the “Carre Agriculture Anatis” [3] and the “Farmdroid” [7], both with one-DoF digging tools. In the Farming Revolution “Farming GT” [8] the rotating tool is guided by two-DoF serial kinematics. Further applications with mechanical tools, lasers or water jets can be found in [4], containing only serial kinematics. Systems with tool handling kinematics of three or more DoF can be used for single-plant-based application. Providing high dynamics and a proven design, Delta robots are used in several weeding systems for tool handling, e.g. in the prototype of “Small Robot Company” [9] with a linear Delta and an electrode, and by Ecorobotix [1] with Delta robots for positioning nozzles in an earlier version. Serial kinematics, as in the SwagBot [10], where a six-DoF robotic arm positions a nozzle, are barely represented and not promising for an efficient application. In [11] a six-DoF parallel robot, the Hexa introduced in [12], was used, but primarily for positioning the camera system rather than the weeding tool. Further applications for all types of tool handling can be found in the reviews [4,13,14]. Unlike the references above, we pursue the idea of a six-DoF parallel robot which is able to provide spatial orientation of the rotating tool prototype to be tested, which opens more possibilities for weed control. This is similar to industrial machining tasks, where the task DoF can be termed as 3T2R, i.e. three translations and two rotations are defined. The crucial part of the development of such a weeding robot is the kinematic synthesis. Combined structural and dimensional synthesis is a suitable method for this purpose especially for parallel robots, introduced in [15] also at the example of a Hexa robot and does not suffer from the restriction to very few proven common structures. Using this method, we present the development of parallel robot with the following contributions: – the transfer of technical requirements for a given weeding process into an optimization problem within the combined synthesis framework, – the development of a six-DoF parallel robot prototype for weeding application, which is a new realization of the Hexa robot by its assembly mode and dimensioning. – By optimizing the redundant coordinate (ϕz ) already in the synthesis we can realize structures despite a high risk of self collision. The paper is outlined as follows. The task requirements are collected in Sect. 2 and translated to a synthesis framework in Sect. 3. The design is discussed in Sect. 4 followed by a workspace evaluation in Sect. 5.

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Our focus is on the organic cultivation of onion crops, as their profitability suffers particularly from weeds. The crops are seeded in flat beds, grouped in four evenly spaced rows between the tractor driving lanes as sketched in Fig. 1. The single-plant-based weeding aims at a narrow band of 60 mm around the seed rows (intra-row ), since this is most vulnerable and more rough methods are used at more distant areas, referred to as inter-row methods. The overall system consist of a mobile robot carrying a PKM and a camera system. Image recognition and stereo vision is used to locate the crops and weeds. The developed robot has to guide the rotating milling tool to the desired coordinates based on camera images. For accessibility and promising advantages in treatment, full tilting of the tool is required (3T2R task), since the tool’s rotation axis needs no additional actuation. Further requirements have to be taken into account within the synthesis: – min. workspace in y-direction ±85 mm (including vehicle deviation) – min. workspace in vertical direction of 340 mm (jumping crops possible) – installation space: two parallel robots are placed next to each other (in ydirection) with centers 1000 mm apart from each other, which is the distance of the outer seed rows. Reduced by a safety distance of 100 mm. No vertical limit – driving speed of vehicle (1 km h−1 ) and a density of four plants per meter, which has to be provided by the acceleration and speed of the end effector – min. diameter of mobile platform due to the tool mounting of 42 mm – the total mass of the mounted milling spindle of 1.5 kg has to be carried – min. tilt angle of the mobile platform: 15◦ (accessibility of the plant roots) – mobile platform DoF: 3T3R (unrestricted research on weeding process, redundant DoF can be used to optimize trajectories and avoiding singularities) – position accuracy: 0.5 mm In the following, these requirements are translated into the synthesis framework.

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The robot’s structural and dimensional synthesis is performed based on the idea of [15] using a general implementation, briefly summarized in [16] with remarks the aspect of functional redundancy, relevant for 3T2R tasks. It provides several possible structures with specified kinematic parameters and uses a multi-objective particle swarm optimization with parallel computation of the structures on a computing cluster. A kinematics and dynamics model is used to simulate a given reference trajectory. In order to consider the requirements in synthesis, these must be mathematically formulated within the fitness function. Requirements are ensured by the hierarchical constraints and the objective functions to be minimized, as well as by the choice of the underlying reference

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Fig. 2. Visualizations of kinematic structures considered within synthesis, taken from the results in Fig. 3 with installation space represented by cuboids (sidelengths of 0.9 m)

trajectory. During the synthesis, the 13–16 optimization variables of feasible structures are varied, consisting of the serial leg’s kinematic parameters and further geometric dimensions (base position and radius, platform radius). The reference trajectory has to represent the workspace requirements, therefore it is composed of target positions at the edge of the workspace and random tilt angles of the tool within the specified range. With regard to the constraints, kinematics-derived criteria such as solvable inverse kinematics (IK), joint limits, self collisions and installation space are examined as well as dynamics-derived criteria like force and material stress limits. The constraints of the optimization parameters were chosen on the basis of the task so wide that the optimization is not unnecessarily limited by them. Only static forces are considered within the synthesis, since specific dynamics of the trajectory is not defined at this stage of development. A total platform payload of 2 kg is assumed next to the sizedependent link and platform mass, based on an aluminum alloy tube or plate geometry to optimize for good force transmission. Within the objective function the two minimization criteria drive torque and speed are defined, since these are dominant for the overall system’s cost. The optimization of the tool rotation, resulting from the 3T2R task’s functional redundancy, is performed as an inner loop within the synthesis, as described in [16]. The set of structures is reduced by the presumption that linear drives are excluded due to higher vulnerability to vibrations and dirt. Further, five-DoF (3T2R) structures are prone to tolerance-induced clamping due to overconstraints and are mostly based on prismatic joints, therefore not considered. Thus, six-DoF PKM with revolute actuation at the base remain. Due to technical realization and higher robustness against collisions, only structures with three or four joints are regarded. The remaining structures are various implementations of 6-RRRS, 6-RUS, 6-RURU, 6-RUUR and 6-RRUU-structures, following the terminology in [17] and shown in Fig. 2. This approach does not fully represent special circumstances of a real construction in detail. Thus, the development process is structured as an iterative procedure in which findings from the constructive design are fed back into subsequent synthesis runs. The set of structures, parameter limits and collision bodies

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Fig. 3. Pareto front (a) and performance map of trajectory (b)

are therefore successively adjusted, which is described in Sect. 4 and results in our final solution shown in Fig. 4, representing a 6-RUS variant. Other kinematic structures did not match the requirements in these further synthesis iterations and were discarded due to the complex technical realization. The optimization was rerun for the initial settings to rank our final solution. Figure 3 (a) shows the pareto-optimal particles for the considered structures, as well as our engineered solution. The engineering solution is outperformed by the RUS solutions which are theoretically possible. However, several points must be noted. After the design selection based on the synthesis version of [16], the optimization of the redundant coordinate within the trajectory IK was improved by using dynamic programming (DP) instead of acceleration-level nullspace projection as shown in [18], thus avoiding oscillations which lead to high dynamic forces in simulation. Furthermore, the marked solution was affected by real conditions which does not apply to all other markers with simplified conditions: our engineering solution is based on the DP trajectory within the platform rotation limits -70◦ ≤ ϕz ≤ -29◦ , since this is the range where no limits of the real spherical joints are exceeded (see Sect. 4). The specific joint implementation could not yet be considered within the synthesis framework. Further, additional collision bodies of the motors were used for the design. This may explain the non-optimality of the engineering solutions against the RUS markers. Thus, only a qualitative proposition can be taken from the figure at this stage of development. Based on our solution, Fig. 3 (b) visualizes the result of DP along the reference trajectory from synthesis in a heatmap of the position error, which is shown for variation of the platform rotation ϕz . The error is based on the assumption of a joint angle resolution of 7 by the textbook method from [17]. Therefore, it can not be quantitatively transferred to our prototype and only covers the aspect of encoder accuracy. The qualitative plot shows that a wide range of platform rotations with homogenous performance is achieved by the chosen design. Invalid areas due to collisions and singularities are marked, as well as the mentioned platform limits. It can be seen that the trajectory regards the limits in this post-processing, so the solution’s reliability is sufficient.

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In order to analyse various synthesis solutions, the design process takes place in iterations, as introduced before. Thus, complex structures can be eliminated based on their design effort or manufacturing costs. Furthermore, the angular ranges of passive joints can be calculated and the necessary design effort can be estimated using design catalogues (see e.g. [19]), to evaluate the realization with standard components. The tilting angle range of common universal joints are around 30◦ – 45◦ , while spherical joints are more restricted within 12◦ –30◦ . The rotation angle of spherical joints is not limited, therefore the joint alignment is critical in terms of end-effector movement, although this is not yet explicitly considered within the synthesis framework. The synthesis is based on predefined requirements, therefore the results can be seen as functional structure [20]. Design methods, like a morphological box were used to find suitable realizations. Starting from the drive, the universal joint is connected by an inclined crank (Fig. 4 (a)). The obtained assembly configuration (elbows inside) results in an acute angle between the links, leading to particular requirements for the universal joints as shown in Fig. 4 (b). The following lower connection rod links the universal joint via a spherical joint to the end-effector platform (Fig. 4 (c)). Representing a particular Hexa variant, the proposed PKM is one of the few realized structures where the larger part of the kinematic chain moves above and below the horizontal plane of the base frame. The angled arrangement of the cranks, seen in Fig. 4 (d), and the elbow-inside assembly mode differs from the known Hexa-robot. Both features are not found in existing RUS-structures, which mainly operate in configurations with elbows located below the base and pointing outwards like in [21]. The advantage of this variant compared to existing structures is due to the dominating restriction of the installation space, so a relatively compact design can be achieved within a given workspace requirement (see Sect. 5). As a result of the kinematic chains crossing the base plane, in combination with elbows mounted inside, an open plate concept has been developed. Based on the application, the drives are mounted on top of a multi-part base plate, to protect them from contamination of the weed control process. Furthermore, the mounting of the actuators could be simplified by the fact, that their weight rests on the plate. As for the guiding rods, aluminum tubes have been selected based on their mechanical properties, relatively low weight and costs. Due to the minimum angle in the elbows of 38◦ , commercially available joints could not be used. Thus, custom joints have been developed on basis of [22] with adaptions to limit manufacturing cost and adjust angular range. Based on the reference trajectory, the mounting orientation of the spherical joints is analyzed by determining the minimal angular range to validate whether cost-efficient standard joints (e.g. rod end bearings, Fig. 4 (c)) can be used. Otherwise, the structure could only be realized with custom designed joints. As a result the spherical joints are parallel to the designed planes on the side of the platform. Furthermore, the aluminium end-effector platform (strength 25 mm) has been designed for minimum cost. To estimate the rough performance required for the rota-

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Fig. 4. Overview of the proposed parallel robot (CAD rendering) (a), universal joints (b), end-effector platform (c), inclined crank (d)

tional drives, the inertia properties of the entire robot were determined using the CAD-model and the dynamics calculation was rerun in order to size the drives more precisely. Permanent-magnet synchronous motors (nominal values: MN = 2.40 N m, nN = 2500 min−1 ) in combination with planetary gears (i = 50, Mmax = 50 N m ) have been selected, since direct drives are typically more expensive. In order to classify these values according to Fig. 3 (a), the max. joint moment is determined without gear-friction to Mmax = 50 N m and the max. joint velocity calculated to vmax = 300◦ s−1 , resulting in a safety factor of approximately 2 for the velocity and 3 for the drive torque. The moment requirements resulting from synthesis should be achieved with a higher safety factor as the velocity, because the individual masses are partly under-represented in the synthesis calculation, resulting in fewer loads. Furthermore, the geometry of the guiding rods were determined by the internal forces repeatedly calculated for adjusted inertia properties in the synthesis. The realization results in a moving mass of approximately 16 kg excluding the tool. The maximum static payload is restricted by the selected motor-gearbox combination and is calculated to mmax = 8 kg with respect to the workspace within the relevant installation space.

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Workspace Characteristics

Given the final design, further evaluations of workspace characteristics are provided, which are out the scope of the dimensional synthesis in Sect. 3 due to their high computational effort. Still, the workspace is important for the application since the reference trajectory does not guarantee a gapless workspace. In addition to the kinematic limits themselves, the workspace also suffers from truncation due to inherent collision, installation space and joint angle limits, where the spherical joint’s tilt angles are dominant. The workspace is calculated

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Fig. 5. Workspace of the proposed parallel robot with platform tilt angle of 0◦ (a), −10◦ (b), −20◦ (c)

specifying a fixed platform tilting angle (by using ϕx and ϕy from intrinsic XY -Z Cardan angles). Any rotation ϕz around the tool axis is allowed (subject to other constraints), as this represents the redundant coordinate. Therefore, the computed workspace volumes correspond to the constant-orientation workspace regarding the reduced orientation of the 3T2R task, cf. [17]. The platform tilt angle is set to 0◦ , −10◦ and −20◦ using ϕy , visualized in Fig. 5. First, leaving aside the mentioned design-related limitations and only assuming a tilt angle limit of 29◦ (considered the best case of a real rod end bearing), the workspace with a total volume between 0.522 m3 (ϕy = 0◦ ) and 0.389 m3 (ϕy = −20◦ ) can be seen in Fig. 5 (volumes colored gray), as this gives an undistorted view of the characteristics of the actual kinematic structure. Due to the requirements of the weed control process and the derived reference trajectory, a relatively large workspace can be obtained. The workspace decreases especially in the radius and shifts laterally in x-direction, with increasing platform orientation. In relation to the sketched installation space, which is defined upwards starting at z = 0, the workspace fills a high proportion of the volume. Structures determined in the synthesis are not allowed to exceed this limitation, because this plane represents the ground. Taking the restrictions of the installed spherical joints into account, the resulting workspace volumes are presented in the figure as well (volumes colored green). The remaining volume amounts 0.205 m3 (ϕy = 0◦ ) and 0.125 m3 (ϕy = −20◦ ). Although there is a loss of volume in the peripheral area (radial direction), this meets the requirements of the weed control process. Therefore the kinematic is suitable for the intended purpose.

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Conclusion

The synthesis and design of a six-DoF parallel robot was presented in this paper, with a variety of structures being tested. As a result a particularly compact variant of the well-known Hexa robot was implemented. Task redundancy was already considered within synthesis and using this, the effective avoidance of singularities has been demonstrated. The workspace characteristics examined are suitable for the intended weeding application. Acknowledgement. The project is supported by funds of the Federal Ministry of Food and Agriculture (BMEL) under grant number 2818812B19. The synthesis toolchain was funded by the German Research Foundation (DFG) under grant number 341489206. Matlab code to reproduce the synthesis’ results and figures is available at GitHub under free license at https://github.com/SchapplM/roboticspaper_i4sdg2023.

References 1. Ecorobotix: Ecorobotix : Smart spraying for ultra-localised treatments. - ecorobotix. https://ecorobotix.com/en/. Accessed 24 Jan 2023 2. Utstumo, T., et al.: Robotic in-row weed control in vegetables. Comput. Electron. Agric. 154, 36–45 (2018) 3. Carbon Robotics: Carbon robotics. https://carbonrobotics.com/. Accessed 24 Jan 2023 4. Zhang, W., Miao, Z., Li, N., He, C., Sun, T.: Review of current robotic approaches for precision weed management. Curr. Robot. Rep. 3(3), 139–151 (2022) 5. Ruckelshausen, A., et al.: BoniRob - an autonomous field robot platform for individual plant phenotyping. Precis. Agric. 9(841), 1 (2009) 6. Naïo Technologies: Autonomous weeding & agricultural robots. https://www.naiotechnologies.com/. Accessed 24 Jan 2023 7. Farmdroid: Farmdroid aps - ecological and co2-neutral automatic farming robot (12122022). https://farmdroid.dk/ 8. Farming revolution GmbH (07112022). https://farming-revolution.com/ 9. Small Robot Company: Small robot company. https://www.smallrobotcompany. com/. Accessed 24 Jan 2023 10. Eiffert, S., Wallace, N.D., Kong, H., Pirmarzdashti, N., Sukkarieh, S.: Experimental evaluation of a hierarchical operating framework for ground robots in agriculture. In: Siciliano, B., Laschi, C., Khatib, O. (eds.) ISER 2020. SPAR, vol. 19, pp. 151– 160. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-71151-1_14 11. Blasco, J., Aleixos, N., Roger, J.M., Rabatel, G., Moltó, E.: AE–automation and emerging technologies. Biosys. Eng. 83(2), 149–157 (2002) 12. Pierrot, F., Fournier, A., Dauchex, P.: Towards a fully-parallel 6 DOF robot for high-speed applications. In: Proceedings. 1991 IEEE International Conference on Robotics and Automation, pp. 1288–1293. IEEE Computer Society Press (1991) 13. Fountas, S., Mylonas, N., Malounas, I., Rodias, E., Hellmann Santos, C., Pekkeriet, E.: Agricultural robotics for field operations. Sensors (Basel, Switzerland) 20(9) (2020) 14. Oliveira, L.F.P., Moreira, A.P., Silva, M.F.: Advances in agriculture robotics: a state-of-the-art review and challenges ahead. Robotics 10(2), 52 (2021)

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15. Krefft, M.: Aufgabenangepasste Optimierung von Parallelstrukturen für Maschinen in der Produktionstechnik. Phd thesis, Techn. Univ. Braunschweig. Vulkan-Verl. (2006). ISBN 9783802786891 16. Schappler, M.: Inverse kinematics for task redundancy of symmetric 3T1R parallel manipulators using Tait-Bryan-Angle kinematic constraints. In: Altuzarra, O., Kecskemethy, A. (eds.) Advances in Robot Kinematics 2022. ARK 2022. Springer Proceedings in Advanced Robotics, vol. 24. Springer, Cham (2022). https://doi. org/10.1007/978-3-031-08140-8_22 17. Merlet, J.P.: Parallel Robots, Solid Mechanics and Its Applications, vol. 128, 2nd edn. Springer, Berlin (2006) 18. Schappler, M.: Pose optimization of task-redundant robots in second-order restto-rest motion with cascaded dynamic programming and Nullspace projection. In: Gusikhin, O., Madani, K., Nijmeijer, H. (eds.) Informatics in Control, Automation and Robotics, pp. 106–131. Springer International Publishing, Cham (2023). https://doi.org/10.1007/978-3-031-26474-0_6 19. Stechert, C., Franke, H.J., Vietor, T.: Knowledge-based design principles and tools for parallel robots. In: Schutz, D., Wahl, F.M. (eds.) Robotic Systems for Handling and Assembly. Springer Tracts in Advanced Robotics, vol. 67, pp. 59–75. Springer, Berlin (2010). https://doi.org/10.1007/978-3-642-16785-0_4 20. Neugebauer, R.: Parallelkinematische Maschinen: Entwurf, Konstruktion, Anwendung. VDI-Buch, Springer, Berlin and Heidelberg (2006) 21. Frindt, M., Krefft, M., Hesselbach, J.: Structure and type synthesis of parallel manipulators. In: Schütz, D. (ed.) Robotic systems for handling and assembly, Springer tracts in advanced robotics, vol. 67, pp. 17–37. Springer, Berlin and Heidelberg (2010). https://doi.org/10.1007/978-3-642-16785-0_2 22. Otremba, R.: Systematische Entwicklung von Gelenken für Parallelroboter: Braunschweig, Techn. Univ., Dissertation, 2004, Bericht / Institut für Konstruktionstechnik, Technische Universität Braunschweig, vol. 67. Logos-Verl., Berlin (2005)

Optimization of the Design Parameters of a 6-DOF Mobility Platform L. A. Rybak(B) , A. V. Khurtasenko , V. S. Perevuznik , K. V. Chuev , and D. I. Malyshev BSTU named after V.G. Shukhov, 46, Kostyukova, Belgorod 308012, Russia [email protected]

Abstract. The paper presents the methodology and results of optimization was performed using a dynamic simulation model and rotatable central composition planning. The substantiation of the characteristics of the simulation model used, its parametric capabilities for the investigation of various structural design are given. The obtained optimal values of the design parameters make it possible to reduce the values of force reactions in the joints, when performing various trajectories of movement, taking into account payloads. The results of the research presented in the paper, aimed at creating innovative solutions to enhance the capabilities of the 6-DOF mobility platform for vehicle driver training simulators, will contribute to the build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation within the framework of the UN General Assembly resolution “Transforming Our World: The 2030 Agenda for Sustainable Development”. Keywords: SDG9 · Simulator · Mobility platform · Dynamic model Parallel mechanism · Simulation model · Digital prototype

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Parallel mechanisms are widely used in many technical devices and designs of technological equipment. The success of distribution is determined by the wide technological possibilities of their application in engineering and technology [1– 4]. Such mechanisms have proven very well when used in the construction of platforms with various degrees of mobility for simulators of ground equipment, aircraft, and water vehicles. Scientific investigation aimed at improving the efficiency of such technical ones is usually associated with determining the optimal parameters of the working space [5–7] or analysing their dynamics [8–10]. One of the important areas of investigation is the optimization of the design of mobile platforms in order to improve their kinematic and dynamic characteristics. 6DOF mobility platforms with a parallel structure have features of the arrangement of drive devices (actuators) connecting the base fixed base and the moving The investigation funded by grant of the Russian Science Foundation No. 22-29-01614, https://rscf.ru/project/22-29-01614/. c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 115–124, 2023. https://doi.org/10.1007/978-3-031-32439-0_14

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platform. The optimal parameters of the mutual arrangement of these elements in the structure make it possible to use the capabilities of the parallel structure more effectively and in some cases reduce the force reactions in the joint joints, thereby increasing the durability of the equipment. The purpose of the investigation in this paper is to optimize the design of the mobility platform (MP), which will provide the minimum values of reactions at the points of attachment of the joints to the base. The novelty of the suggested approach is in use of a parameterized simulation model in combination with rotatable and compositional planning, taking into account the design features of the MP and payload, has been implemented. Based on this, new knowledge has been obtained about geometric connections for the basic parameters of 6-DOF mobility platforms, which affect the values of force reactions in articulated supports and allow determining the optimal dimensions of the joint arrangement depending on the payload. The method and model proposed in the paper for optimizing design parameters using the highly efficient ADAMS software package will contribute to the rational and rapid design of mobility platforms for vehicle simulators. This will certainly contribute to the creation of a strong infrastructure, promote inclusive and sustainable industrialization and innovation in the framework of the UN General Assembly resolution “Transforming Our World: The 2030 Agenda for Sustainable Development”.

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The simulation model of MP is shown in Fig. 1. As a prototype of the simulation model, a MP for vehicle simulators was selected. The structure consists of upper and lower platforms connected by actuators and spherical joints.

Fig. 1. MSC Adams simulation model of MP: M01...M60 - markers of the corresponding joints; SJ - spherical joint; TJ - transnational joint; CM is the center of mass; PL is the payload applied at the center of mass.

The simulation model uses the tools of the MSC Adams software environment, which are selected in accordance with the functional elements of a real design. As external influences in the model, gravity and payload are given, from

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the mass of the installed cabin object (given taking into account the industrial design of the cabin). The payload is applied at the center of mass. The MSC Adams software product allows you to create parameterized models that provide flexible control over the standard sizes of the elements of the structure under investigation, by changing the parameters of the corresponding variables. This allows you to change the values of the geometric and physical parameters of the structure without creating a new model. For convenience, the model is made in a cylindrical coordinate system, so the attachment points of the joints to the base and the working platform are set using the circle radius (BD R, T U R) and angle (ϕ01 − ϕ60 ). When new data is entered, the model is automatically rebuilt, according to the imposed restrictions.

3

Investigation Methodology

Certain trajectories of movements of the upper mobile platform have been selected for research. To work out the selected trajectories, the maximum possible velocity characteristics of the selected actuators were used [11]. Features of the movements of the selected trajectories: The first trajectory: lifting - lowering of the moving platform at horizontal orientation. The second trajectory: performing the maximum tilt relative to the OX axis with an offset in the direction of the tilt, then lifting and returning to the starting position. The third trajectory: diagonal displacement of the moving part of the platform from the initial position to the maximum possible one way, then reverse to the other side and return to the initial position. The fourth trajectory: rotation around the vertical axis at the maximum angle and return to the starting position (yaw movements). The fifth trajectory: cyclic lifting and tilting movement due to the sequential alternation of adjacent actuators in operation. At the same time, each actuator first performs the maximum departure of the rod, then turns on the reverse until the minimum departure is reached. To find the optimal design parameters, a complete 2-factor experiment of the 2nd order was carried out. For this, a rotatable central compositional plan of the second order was built. As disadvantages of the central composite rotatable planning, an increased number of series of experiments can be indicated, in comparison with other methods of CCP. Also, the rotatable planning matrix does not meet the orthogonality conditions, so more complex formulas are used to calculate the independent coefficients of the regression equation, with coefficients derived empirically. The output parameter of the response function F = f (s, d) is the value of the maximum resulting sum of forces (F ) that occurs at the point of attachment of the joint to the base when working out the most loaded trajectory. As factors of the experiment, the following were chosen: s is the distance between adjacent points of attachment of the joints to the base, d is diameter of the attachment of the joints to the base. In accordance with the variable factors, Table 1 was constructed with the conditions of the experiment. Table 2 presents a second-order rotatable uniform planning matrix as applied to the investigation objectives. Figure 2 (a) shows the main variable geometric

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Designation of factors

Factor levels

Factor variation intervals

natural(nat) encoded(en) nat

en nat

en nat

en nat

en nat

en

s, mm

x1

391

+a 350

+1 250

0

−1 109

−a 100

d, mm

x2

1732 +a 1650 +1 1450 0

150

1250 −1 1168 −a 200

parameters of the simulation model. To correct the parameters of the simulation model according to the experimental plan, a calculation scheme was made (Fig. 2 (b)), interpreting the design features of the platform, which determine the geometric relationships in the design of the platform under investigation. Table 2. Second Order Rotatable Uniform Planning Matrix. x˜1

1

+ +

350 +

1650 +

+ + 27226

2

+ –

150 +

1650 –

+ + 22586

3

+ +

350 –

1250 –

+ + 150400

4

+ –

150 –

1250 +

+ + 30905

5

+ +1.41 391 0

1450 0

2

0

88248

6

+ −1.41 109 0

1450 0

2

0

11712

7

+ 0

250 +1.41 1732 0

0

2

12590

8

+ 0

250 −1.41 1168 0

0

2

35514

9

+ 0

250 0

0

0

27567

x2

x˜2

x1 x2 x21 x22 yi

Experience number x0 x1

1450 0

Table 3 was compiled based on the calculation scheme for conducting a series of experiments in accordance with the experimental methodology. Table 3. Input data for model modifications in each experiment.

Experience number s, mm d, mm ϕ01 ,◦ ϕ02 ,◦ ϕ03 ,◦ ϕ04 ,◦ ϕ05 ,◦ ϕ06 ,◦ r, mm 1

230

1650

77.8

342.2 317.8 222.2 197.8 102.2 825

2

150

1650

84.8

335.2 324.8 215.2 204.8 95.2

3

350

1250

73.3

346.3 313.7 226.3 193.7 106.3 625

4

150

1250

83.1

336.9 323.1 216.9 203.1 96.9

5

391

1450

74.4

345.6 314.4 225.6 194.4 105.6 725

6

109

1450

86.7

334.3 325.7 214.3 205.7 94.3

725

7

250

1732

81.7

338.3 321.7 218.3 201.7 98.3

866

8

250

1168

77.6

342.3 37.6

9

250

1450

80.1

339.9 320.1 219.9 200.1 99.9

825 625

222.3 197.6 102.3 584 725

Optimization of the Design Parameters of a 6-DOF Mobility Platform

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Fig. 2. a) Changeable parameters of the platform simulation model: s - distance between joints attachment points;d - diameters and φ - the angles of the joints attachment points relative to the center of the platform b) Scheme of the location of the points of attachment of the joints to the base for experiments 1, 2, .. 9 (shown for joints M01 and M06).

In the course of dynamic modeling of the selected trajectories of the MP, the force values arising in the joints during the specified time of execution of all five selected trajectories (T1, T2 ... T5) were fixed. The results are shown in Figs. 3 and 4 in the form of curves (trends) M s SF 01, M s SF 02 .. M s SF 06, showing changes in force reactions at the attachment points of the joints M 01, M 02...M 06, respectively. The analysis showed that the most critical is the trajectory (T3). In this case, smaller peak values of reactions occur in the design variant of experiment 6 (plot RP P 22 i6, Fig. 3), and the largest ones occur in the design variant of experiment 3 (plot RP P 22 i3, Fig. 4).

Fig. 3. Graphs of the peak values of the resulting sum of forces in the design with parameters for the 6th experiment.

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Fig. 4. Graphs of the peak values of the resulting sum of forces in the design with parameters for the 3th experiment

For clarity and convenience of processing the results when forming a mathematical model, Table 4 is made, which presents the output parameter of the peak value of the resulting sum of forces in coded (line yi ) and natural values (line F ). Also indicated are the parameters for the occurrence of peak values of the resultant, such as the moment in time, the joint and the executed trajectory. Table 4. Peak values of the resulting sums of forces (reactions) for 3 trajectories. Experience number 1

2

3

4

5

6

7

8

9

F, N

27726 22586 150400 30905 88248 11712 12590 35514 27567

Trajectory

T3

T3

T3

T3

T3

T3

T3

T3

T3

Joint

M05

M04

M05

M04

M05

M05

M05

M05

M05

Moment of time, s

11.6

13.6

11.6

13.6

11.6

11.6

11.6

11.6

11.6

After calculating the regression coefficients, the mathematical model for the distribution of the peak values of the sum of forces from the distance between the joints and the diameter of base is presented as a Eq. (1): F = 27550 + 29045 · x1 − 20488 · x2 − 28714 · x1 · x2 + 16387 · x21 + 3431 · x22 (1) where F is the peak value of the sum of forces; x1 - 1st factor - the distance between adjacent points of attachment of the joints to the base - s; x2 - 2nd factor - the diameter of the attachment of the joints to the base - d. After decoding, the regression equation can be written in this form: F = 1.64s2 + 1552.86 s − 1.4ds + 7.73d2 + 0.09d2 − 134205

(2)

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The dependence of the peak values of the sum of forces on the distance between the adjacent points of fastening the joints to the base and the diameter of fastening the joints to the base is presented in the form of a three-dimensional graph in Fig. 5.

Fig. 5. The function of the response of the peak values of the sum of forces on the distance between adjacent points of attachment of the joints and the base diameter of the location.

To search for the optimum region, it is necessary to find a critical point located on the response surface and which is the center of the geometric figure (Fig. 5) described by Eq. (2). Having made the necessary calculations, we can conclude that in the given range s (150 − 350) and d (1250 − 1650) the peak value of the resulting sum of forces (F ) is minimal when the distance between adjacent points of attachment of the joints to the base (s) takes the value is 196 mm, and the diameter of the attachment of the joints to the base (d) takes on the value of 1525 mm. To conduct an investigation of an optimized design, it is necessary to correct the variable values of the geometric parameters of the MP simulation model, in accordance with the found optimal values of the factors. Such investigations are useful for checking the optimized design based on the obtained force values in the joints and comparing them with the minimum and maximum allowable values. The initial data for updating the simulation model are presented in Table 5. Table 5. Optimal Design Parameters for the Simulation Model. s, mm d, mm ϕ01 ◦ ϕ02 ◦ ϕ03 ◦ ϕ04 ◦ ϕ05 ◦ ϕ06 ◦ r, mm 196

1525

88

332

328

212

208

92

762.5

122

4

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Investigation Results

The simulation results of the optimized design for the previously selected trajectories are presented in Fig. 6 as graphs of the resulting forces in the joints. Designations M s SF 01, M s SF 02, M s SF 03, M s SF 04, M s SF 05 and M s SF 06 correspond to joints 1, 2, 3, 4, 5 and 6. The peak value of the design resulting from the simulation of the experiment with optimal parameters (s=196, d=1525) was Fopt = 9405 N, which is 20% less than during the simulation of experiment 6, in which earlier (before optimization) the minimum peak values of reactions in the joints were observed. Figure 7 shows graphs of changes in the values of the resultant separately for joints 3 and 5 (in these joints the highest peak values) when simulating the most loaded trajectory - T3. Curve I6 T 3 (red) corresponds to the design for the 6th experiment. Curve I extr T 3 (blue color) - corresponds to the design with optimal parameters.

Fig. 6. Graphs of changes in the resulting sum of forces applied to the attachment points of the joints to the base of the optimized design.

Fig. 7. Comparison of trends (curves) of the dependence’s of the resulting sum of forces on time at 6 points of attachment of the joints to the base of the MP.

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Analysis of the graphs shows a similar nature of the change in force values throughout the entire trajectory. However, in a design with optimal parameters, a decrease in the peak values of force reactions in all joints is observed.

5

Conclusion

The investigations carried out using a digital dynamic simulation model. Application of the rotatable central compositional planning made it possible to determine the optimal values of the basic geometric parameters that reduce force reactions in the jointed supports of the platform. The application of the presented technique can provide the possibility of determining the optimal force parameters for actuators under the required loads and trajectories of moving parts of similar platforms. In the future, when developing industrial models of mobility platforms, this will allow selecting the most effective designs of actuators according to their type and characteristics. The presented research methodology can be used in the development of effective digital twins necessary in the investigation of the possibilities of mechanisms with parallel structures, as well as in solving design problems. Acknowledgments. The investigation funded by grant of the Russian Science Foundation No. 22-29-01614

References 1. Merle, J.-P.: Parallel Robots. Springer, Heidelberg (2006) 2. Gabutdinov, N.R., Glazunov, V.A., Filippov, D.N.: Developing six-degree-offreedom parallel mechanisms at the research institute for machine science n.a. A.A. Blagonravov. Proc. High. Educ. Instit. Mach. Build. 7, 83–89 (2014) 3. Petraˇsinovi´c, M., Grbovic, A., Petraˇsinovi´c, D., Petrovi´c, M.: Real coded mixed integer genetic algorithm for geometry optimization of flight simulator mechanism based on rotary stewart platform. Appl. Sci. 12(14), 70–85 (2022) 4. Khalapyan, S., Rybak, L., Gaponenko, E., Carbone, G.: Motion control of 6-DOF relative manipulation device. In: Zeghloul, S., Laribi, M.A., Arsicault, M. (eds.) MEDER 2021. MMS, vol. 103, pp. 217–225. Springer, Cham (2021). https://doi. org/10.1007/978-3-030-75271-2 23 5. Rafael, B.H., Sebastien, B., Abdelhamid, C., Philippe, M.: Minimizing the energy consumption of a delta robot by exploiting the natural dynamics. In: RoManSy 2020 - 23rd CISM IFToMM Symposium on Robot Design, Dynamics and Control, pp. 213–221, Sapporo, September 2020 6. Rybak, L.A., Gaponenko, E.V., Khalapyan, S.Y.: Issues of planning trajectory of parallel robots taking into account zones of singularity. In: IOP Conference Series: Materials Science and Engineering, vol. 327, p. 042092 (2018) 7. Cetin, K., Tugal, H., Petillot, Y., Dunnigan, M.: A robotic experimental setup with a Stewart platform to emulate underwater vehicle-manipulator systems. Sensors 22, 1–16 (2022) 8. Rashoyan, G.V., Lastochkin, A.B., Glazunov, V.A.: Kinematic analysis of a spatial parallel structure mechanism with a circular guide. J. Mach. Manuf. Reliab. 44(7), 626–632 (2015)

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9. Zabalza, I., Ros, J., Gil, J., Pintor, J.M., Jimenez, JM.: Tri-scott. a new kinematic structure for a 6-DOF decoupled parallel manipulator. In: Proceedings of Workshop on Fundamental Issues and Future Directions for Parallel Mechanics and Manipulators, pp. 12–15 (2002) 10. Brinker, J., Schmitz, M., Takeda, Y., Corves, B.: Dynamic modeling of functionally extended delta-like parallel robots with virtual tree structures. In: Arakelian, V., Wenger, P. (eds.) ROMANSY 22 – Robot Design, Dynamics and Control. CICMS, vol. 584, pp. 171–179. Springer, Cham (2019). https://doi.org/10.1007/978-3-31978963-7 23 11. Khurtasenko, A.V., Chuev, K.V., Rybak L.A., Skitova V.M. : Dynamic platform model with 6 degrees of freedom. In: Bulletin of BSTU: Mechanical Engineering and Mechanical Engineering, pp. 124–136 (2023)

Biomechanical and Medical Systems

Identification of Surgical Forceps Using YOLACT++ Shoko Memida(B) and Satoshi Miura The Department of Mechanical Engineering, The School of Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro 152-8550, Tokyo, Japan {memida.s.aa,miura.s.aj}@m.titech.ac.jp

Abstract. Forceps tracking in laparoscopic surgery contributes to improved surgical outcomes. We identified forceps by deep learning. Since it is important to identify forceps in real-time, we selected YOLACT++ for fast and accurate segmentation and verified whether the detection speed can be maintained in the video. We annotated a total of 2537 images combining multiple datasets including various surgical environments, and divided them into training, validation, and test data at a ratio of approximately 8:1:1. In training, the hyperparameters were adjusted while performing holdout validation to determine the optimal combination of hyperparameters that maximized the identification speed. The training was conducted with a batch size of 32, a number of iterations of 100106, and a number of epochs of 1588, and the results showed that the forceps identification speed was 25.79 fps and accuracy was 84.31%. The results of the test using the trained model with this hyperparameter showed that the forceps identification speed was 28.01 fps and accuracy was 71.42% for images, and the forceps identification speed was 17.70 fps for the video (frame rate 60 fps, resolution 584 × 328). Keywords: SDG3 · Biomechanical Engineering · Biomedical Engineering · Medical Robotics · Laparoscopic Surgery · Surgical Tool Detection · Deep Learning · Image Processing

1 Introduction Minimally invasive laparoscopic surgery is performed by inserting surgical instruments through a small incision. Compared to laparotomy, laparoscopic surgery is widely used in many surgical procedures because of its quicker recovery and less pain. However, laparoscopic surgery has problems such as a narrow field of view and surgical space, and difficulty in depth perception. As a result, there is a high risk of surgical errors such as damage to organs by forceps. Therefore, surgical outcomes need to be improved by making it easier to perceive the position of the forceps in laparoscopic surgery [1]. Miura et al. [2] used image processing to obtain the posture of forceps. However, the use of colored tape is not practical in actual surgical practice, because forceps coated with different colors for each part are not always used. A more accurate forceps identification method is needed to minimize the error from the actual posture without the use of colored tape. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 127–135, 2023. https://doi.org/10.1007/978-3-031-32439-0_15

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As a method that does not use colored tape, a convolutional neural network (CNN) can be used to detect forceps. Sarikaya et al. [3] and Zhang et al. [4] have developed an object detection system Faster R-CNN [5]. Faster R-CNN has a two-stage structure: it learns whether a certain rectangle in an image is an object or background, and if it detects an object, it learns what exactly is in the image. Therefore, the processing speed was low and could not perform high-speed detection. Choi et al. [1] proposed a CNN-based surgical instrument detection model based on the object detection system YOLO (You Only Look Once) [6], which can recognize objects at high speed and in realtime. Validation results showed that the accuracy of the dataset containing information on seven surgical instruments was only 72.26%. In addition, two surgical instrument regions were detected for one surgical instrument, and non-surgical instrument regions were detected. These problems may be attributed to the small number of images used and insufficient preprocessing of the data. An object detection algorithm that achieves both high speed and high accuracy is the Single Shot MultiBox Detector (SSD) [7]; Ali et al. performed an object recognition task for dental instruments using SSD and achieved an accuracy of 87.3% [8]. Segmentation (region extraction) is required to obtain forceps posture; Mask R-CNN [9] is a model that performs both object detection and instance segmentation. Semantic segmentation only identifies classes, whereas instance segmentation distinguishes object instances individually so that two forceps can be distinguished and recognized even if they overlap. The segmentation accuracy of Mask R-CNN is high because segmentation is performed after object detection; Ciaparrone et al. achieved 87% accuracy in segmenting medical instruments in laparoscopic surgical images [10]. However, there was a problem with the low processing speed of about 2 fps. Since real-time forceps identification is required in the surgery, a higher processing speed is needed. The deep learning model YOLACT++ [11] has a one-stage structure that simultaneously performs object detection and instance segmentation. Angeles Ceron et al. [12] achieved highly accurate and fast segmentation of medical instruments in images using YOLACT++, but it is necessary to verify whether the high speed can be maintained in videos as well. In this study, we assess the performance using YOLACT++ for real-time and highly accurate forceps identification. To improve the forceps identification performance, we train on existing datasets with enough data. Finally, we evaluate the forceps identification speed and accuracy by comparing those with the results of forceps identification using Mask R-CNN. The rest of the paper is organized as follows. Section 2 describes the collected dataset, the image annotation process, the framework and models used for deep learning. In Sect. 3 we describe the training, validation, testing methods, the results of hyperparameter validation, the results of model testing, and a discussion. Finally, Sect. 4 concludes the article.

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2 Materials and Methods 2.1 Dataset Collection The datasets used were Cholec80 Dataset [13], Crowd-Source Data Instrument Segmentation dataset [14], Hamlyn Centre Laparoscopic Endoscopic Video Datasets [15], MICCAI EndosVis’15 Instrument Subchallenge Dataset [16], and m2cai16-tool dataset [13] (Fig. 1). The Cholec80 Dataset and the m2cai16-tool dataset are datasets provided by CAMMA (Computational Analysis and Modeling of Medical Activities). The Cholec80 Dataset contains 80 videos of laparoscopic cholecystectomies performed by 13 surgeons. The m2cai16-tool dataset contains 15 videos of laparoscopic cholecystectomies. The Crowd-Source Data Instrument Segmentation dataset was created from 6 surgical images of 3 laparoscopic adrenalectomies and 3 laparoscopic pancreatectomies, with a total of 120 images from 20 images containing one or more medical instruments extracted from each surgery. The Hamlyn Centre Laparoscopic Endoscopic Video Datasets are provided by the Hamlyn Centre. This dataset contains 82,862 surgical images using the da Vinci endoscopic surgery robot. The MICCAI EndosVis’15 Instrument Subchallenge Dataset contains 160 pieces of annotated training data and 140 pieces of test data generated from four laparoscopic colorectal surgeries. 2.2 Annotation Processing Generally, a large amount of annotated teacher data is required to create highly accurate deep learning models. Annotation is the process of combining images and other data by assigning meaning to them and associating them with each other. Region extraction, one of the image annotation processes, is a method of extracting specific regions in an image and tagging them with the meanings they represent. To perform the annotation process, the 25-fps video in the Cholec80 Dataset and the m2cai16-tool dataset was first divided into frames. Then, images were acquired every 250 frames, or every 10 s, to obtain forceps images in various postures. The frame segmentation process was performed using OpenCV (Open Source Computer Vision Library)-Python, an open source computer vision library for processing images and videos. The region extraction was performed to generate teacher data for the deep learning model that identifies the position of the forceps. The annotation process was performed on all five datasets. Although the Crowd-Source Data Instrument Segmentation dataset and the MICCAI EndosVis’15 Instrument Subchallenge Dataset contained annotated images but did not contain the JSON files we wanted to use. Therefore, we did not use the annotated images in the dataset but annotated them ourselves. The annotation process was performed manually using CVAT (Computer Vision Annotation Tool), an OpenCV annotation tool, which is a library created on Django, a web application framework implemented in Python. CVAT is a library created on Django, a web application framework implemented in Python, and can be used on Google Chrome. The annotation procedure using CVAT is as follows (Fig. 2). Surround the first forceps with a polygon while left clicking with the mouse. The point on Fig. 2 indicates the area selected by clicking. Once confirmed, the forceps area is selected in red and labeled “Forceps 1”. The second forceps is then enclosed in the same way with a polygon. Once confirmed, the

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forceps area is selected in blue and labeled “Forceps 2”. The two forceps are annotated with separate labels so that they can be distinguished when they overlap. After completing the region selection, the data was exported to the segmentation mask format. The result was an image with the selected regions filled in. The data was exported in COCO format to obtain a JSON file, since the segmentation information was to be displayed in text format when the model was used for training. The above series of operations were performed to create 2,537 pieces of labeled data. To accommodate a variety of surgeries and forceps types, we used a combination of different surgical environments even within the same dataset.

Fig. 1. Five types of datasets used for deep learning to identify surgical forceps.

2.3 Deep Learning Model The structure of YOLACT++ is shown in Fig. 3. It has a one-stage structure that performs mask generation and mask coefficient prediction in parallel to achieve fast and accurate segmentation. Backbone Detector extracts features from images. It uses DCNs to learn the convolution location. Protonet predicts masks from the most feature extracted map, Prediction Head predicts classifications, bounding boxes, and mask coefficients, Fast NMS removes overlapping bounding boxes, and Assebmly combines multiple masks output by Protonet and mask coefficients output by NMS to generate masks. Crop trims the mask with bounding boxes, Fast Mask Re-Scoring Network improves the correlation between classifier confidence and mask accuracy, and Threshold thresholds the mask contour.

Fig. 2. Annotation processing procedure for medical forceps using CVAT.

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Fig. 3. YOLACT++ architecture.

3 Identification Speed and Accuracy Validation 3.1 Training/Validation/Testing Methods NVIDIA Corporation GA102 [GeForce RTX 3090] was used for training, validation, and testing. The hyperparameters were adjusted through repeated training and validation to find the hyperparameters that maximize the forceps identification speed. In this study, we adjusted the batch size, the number of iterations, and the number of epochs. The hyperparameters learning rate and weight decay are the default values in YOLACT++. The learning rate is initially set to 1 × 10–3 (batch size 8), 2 × 10–3 (batch size 16), and 4 × 10–3 (batch size 32), divided by 10 for every 280 k, 600 k, 700 k, and 750 k epochs. The weight decay is 5 × 10–4 . Holdout verification was selected as the verification method. The 2537 annotated images were divided into training data, validation data, and test data at a ratio of approximately 8:1:1, and three JSON files with segmentation information were created and used for training. The batch sizes were set to 8, 16, and 32, which are commonly used values. For each batch size, training was stopped when the slope of the mask loss in the stochastic gradient descent method was minimized and the mask accuracy was stable, and the number of epochs was obtained. In the stochastic gradient descent method, the gradient is calculated using only one randomly selected data set, and the weight parameters are updated to minimize the loss. After training was completed, we determined the one with the largest forceps identification speed among the three batch sizes and measured the forceps identification speed and accuracy with test data in the selected trained model. The forceps identification speed was measured using not only images but also videos as test data. The target accuracy was set at 82%, with the goal of keeping the accuracy within 5% of the drop from the Mask R-CNN. The target speed was set to 25 fps, which is close to real time, because the forceps identification speed of the Mask R-CNN [9] was lower than that of the COCO dataset [10], and the same was expected for YOLACT++. In addition, we set the target speed of YOLACT++ to 20 fps based on previous AR studies, because we considered that the speed would decrease in the processing of moving images because forceps identification must be performed for each frame while dividing the frames.

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3.2 Hyperparameter Validation Results Table 1 shows the validation results for the three batch sizes and the associated number of iterations and epochs, as well as a comparison of the results using Mask R-CNN [9]. The accuracy was measured with an IoU threshold of 0.50 (percentage of forceps that overlap with the labeled correct mask by more than 50%). 32 batch size, 100106 iterations, and 1588 epochs were selected as the combination with the maximum validation speed among the three hyperparameter combinations. The correlation between the number of training cycles and mask loss for this model is shown in Fig. 4, and the correlation between the number of training cycles and mask accuracy is shown in Fig. 5. 3.3 Model Test Results Table 2 shows the results of testing the selected trained models with images and videos, as well as a comparison table of the test results when using Mask R-CNN [9]. Note that the tests were performed three times for each image and video data, and the average forceps identification speed and accuracy were measured. The results shows that the forceps identification speed and accuracy were 28.01 fps and 71.42% for the images, and 17.70 fps for the video (frame rate 60 fps, resolution 584 × 328). The segmentation images obtained as a result of the test are shown in Fig. 6. The number next to the label name indicates the confidence level of the classification (maximum 1.00).

Fig. 4. Correlation between the number of iterations and loss.

Fig. 5. Correlation between the number of iterations and AP50 .

3.4 Discussion The highest accuracy was achieved when training with a batch size of 8. This is thought to be because the smaller the batch size, the easier it is to capture individual features of the data. There was a possibility that a smaller batch size would reduce the accuracy due to the influence of noise. However, among the three batch sizes selected, the lower the batch size, the higher the accuracy, and the optimal batch size for the default learning rate in terms of accuracy was 8. On the other hand, the processing speed increased as the batch size increased, with batch size 32 being the fastest. This is believed to be due to the averaging of data features as the batch size is increased. Comparing the test results with Mask R-CNN, the forceps identification speed of the image was approximately 14 times faster, achieving the target speed of 25 fps and

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(A) The model can identify closed forceps.

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(B) The model can identify open forceps as well.

Fig. 6. YOLACT++ test results on the m2cai16-tool dataset.

Table 1. Validation speed and accuracy comparison table. Learning model YOLACT++

Hyperparameters

Processing speed (fps)

AP50 (%)

Batch size

Iteration

Epoch

8

800000

3149

24.45

86.30

16

244162

1932

24.77

86.07

32

100106

1588

25.79

84.31

1.67–2.50

92.00

Mask R-CNN

Table 2. Test speed and accuracy comparison table. Learning model

Test data

YOLACT++

Mask R-CNN

Processing speed (fps)

AP50 (%)

Images

28.01

71.42

Video (60 fps, 584 × 328)

17.70

Video (25 fps, 584 × 328)

17.33

Video (60 fps, 292 × 164)

17.23

Video (60 fps, 1168 × 656)

17.37

Images

1.67–2.50

87.00

eliminating the low-speed problem. The accuracy of the validation data achieved the target value of 82%, but the test accuracy compared to Mask R-CNN was more than 10% lower than the target value of 82%, showing a large gap between the accuracy of the validation data and that of the test data. Although we attempted to reduce the influence of bias by selecting various surgical environments with different operation numbers, the difference in the number of images included in each dataset may have caused the difference in estimation accuracy depending on the type of operation and forceps. In k-fold cross-validation, the original dataset is partitioned to create k combinations of

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training and validation datasets, each of which is trained on data other than the validation dataset, and then validated, and finally all models are averaged. The bias is also expected to be eliminated by increasing the number of training data. In particular, when we checked the test result images, the identification accuracy was low when the forceps overlapped or when the forceps were in the back, so adding such images to the training data may improve the accuracy. Although the target value was achieved in the image processing, the processing speed of the video was reduced, and the target value of 20 fps was not achieved. This may be due to the time required to split the video frames. Tests were conducted by changing the frame rate and resolution of the video, but no significant changes were observed. Possible solutions include increasing the performance of the PC by adding a GPU, using some programming language other than python, and reducing the number of layers in the YOLACT++ structure, which has many layers, to create a model that specializes in speed.

4 Conclusion In this study, we used deep learning to identify surgical forceps. We achieved a forceps identification speed of 28.01 fps and 71.42% accuracy in images, a forceps identification speed of 17.70 fps in the video (frame rate 60 fps, resolution 584 × 328). The lowspeed problem of forceps identification using the Mask R-CNN model was solved. To improve accuracy, we can use k-fold cross-validation as a validation method, increase the number of training datasets, and increase the number of images with overlapping forceps and forceps positioned at the back. In addition, to improve the speed, we can increase the performance of the PC by adding a GPU, use some programming language other than python, or reduce the number of layers in YOLACT++ to make the model more specialized for speed.

References 1. Choi, B., Jo, K., Choi, S., Choi, J.: Surgical-tools detection based on convolutional neural network in laparoscopic robot-assisted surgery. In: Proceedings of the Annual International Conference on IEEE Engineering in Medicine and Biology Society EMBS, pp. 1756–1759 (2017). https://doi.org/10.1109/EMBC.2017.8037183 2. Miura, S., et al.: Virtual shadow drawing system using augmented reality for laparoscopic surgery. Adv. Biomed. Eng. 11, 87–97 (2022). https://doi.org/10.14326/abe.11.87 3. Sarikaya, D., Corso, J.J., Guru, K.A.: Detection and localization of robotic tools in robotassisted surgery videos using deep neural networks for region proposal and detection. IEEE Trans. Med. Imaging 36(7), 1542–1549 (2017). https://doi.org/10.1109/TMI.2017.2665671 4. Zhang, B., Wang, S., Dong, L., Chen, P.: Surgical tools detection based on modulated anchoring network in laparoscopic videos. IEEE Access 8, 23748–23758 (2020). https://doi.org/10. 1109/ACCESS.2020.2969885 5. Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. Total Perform. Scorec. 159–183 (2020). https://doi.org/10.4324/ 9780080519340-12

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6. Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. ACM Int. Conf. Proc. Ser. (2018). https://doi.org/10.1145/3243394.3243692 7. Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21–37. Springer, Cham (2016). https://doi.org/ 10.1007/978-3-319-46448-0_2 8. Ali, H., Khursheed, M., Fatima, S.K.: Object recognition for dental instruments using SSDMobileNet. In: 2019 International Conference on Information Science and Communication Technology (2019). https://doi.org/10.1109/CISCT.2019.8777441 9. He, K., Gkioxari, G., Dollar, P., Girshick, R.: Mask R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2961–2969 (2017). https://doi.org/10.48550/ arXiv.1703.06870 10. Ciaparrone, G., Bardozzo, F., Priscoli, M.D., Kallewaard, J.L., Zuluaga, M.R., Tagliaferri, R.: A comparative analysis of multi-backbone Mask R-CNN for surgical tools detection. In: 2020 International Joint Conference on Neural Networks 2020 Conference Proceedings (2020). https://doi.org/10.1109/IJCNN48605.2020.9206854 11. Bolya, D., Zhou, C., Xiao, F., Lee, Y.J.: YOLACT++: Better Real-time Instance Segmentation, December 2019. https://doi.org/10.1109/TPAMI.2020.3014297 12. Angeles Ceron, J.C., Chang, L., Ruiz, G.O. Ali, S.: Assessing YOLACT++ for real time and robust instance segmentation of medical instruments in endoscopic procedures. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, 1824–1827 (2021). https://doi.org/10.1109/ EMBC46164.2021.9629914 13. Twinanda, A.P. et al.: EndoNet: a deep architecture for recognition tasks on laparoscopic videos. IEEE Trans. Med. Imaging 36, 86–97 (2017) 14. Maier-Hein, L., et al.: Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images. Med. Image Comput. Comput. Assist. Interv. 17, 438–445 (2014) 15. Ye, M., et al.: Self-supervised siamese learning on stereo image pairs for depth estimation in robotic surgery. Hamlyn Symp. Med. Robot. 2017 27–28 (2017). https://doi.org/10.31256/ hsmr2017.14 16. Bodenstedt, S., et al.: Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery (2018). https://doi.org/10.48550/arXiv.1805.02475

RehaWrist.q - Development of a 3 DoF Cable-Driven End-Effector Wearable Robot for Rehabilitation of the Wrist Joint Giuseppe Quaglia1(B) , Andrea Botta1 , Giovanni Colucci1 , and Yukio Takeda2 1

Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy {giuseppe.quaglia,andrea.botta,giovanni colucci}@polito.it 2 Department of Mechanical Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan [email protected]

Abstract. This paper proposes the development of a 3 DoF cabledriven end-effector robot for the rehabilitation of the wrist joint named RehaWrist.q. This device is wearable, small, and does not require external support. To properly size the assistive robot, a new index, called transmission index, was defined to derive the definition of the robot proportions. Then, an optimisation problem based on a quasi-static system was proposed to implement the force control required to safely use this device and to correctly size the actuation sub-system. Keywords: SDG3 · Wrist Rehabilitation Robot · Cable-Driven · Force Control

1

· Limb Injuries · Service

Introduction

Approximately 75% of people of working age have upper limb injuries of varying severity [3], with forearm and wrist injuries being the most common [1]. Rehabilitation exercises are necessary to recover joint mobility [1,3], and as the population ages, the demand for rehabilitation care and specialised staff is likely to grow. The use of robotic devices for rehabilitation aid towards the achievement of Sustainable Development Goal 3 (SDG 3), “ensure healthy lives and promote well-being for all at all ages”, by reducing the costs of therapies, and increasing their effectiveness and the possibility of use. Robotic rehabilitation involves the ability to repeat therapeutic movements without the direct involvement of a therapist, so much so that clinical trials conducted by Kwakkel et al. and Reinkesmeyer et al. [6,9] confirmed that robotic rehabilitation is effective. c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 136–145, 2023. https://doi.org/10.1007/978-3-031-32439-0_16

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In response to these essential challenges, this study proposes the development of a 3 DoF cable-guided end-effector system that is also wearable, small, lightweight, and does not require external support named RehaWrist.q.

2 2.1

Wrist Rehabilitation Robot Proposal Wrist Joint

The wrist joint consists of two DoFs [8]: flexion-extension (FE, β) and radialulnar deviation (RUD, γ). Also, the additional movement of pronationsupination (PS, α) is usually considered a useful and effective motion for rehabilitation, although it is not part of the wrist but corresponds to the rotation of the entire forearm. Such a complex kinematic chain is simplified as depicted in Fig. 1: a simpler 2 DoFs universal joint with perpendicular axes intersecting at the ideal wrist centre is used to model FE and RUD motions. PS is represented by a revolute joint between the elbow and the forearm.

Fig. 1. Kinematic diagram of a simplified representation of the wrist joint.

Table 1 displays the ranges of motion derived by averaging the values available in the literature [4,8,10], both for the maximum range of motion and for the ranges usually involved in activities of daily living (ADLs). Table 1. Wrist joint maximum and ADLs ranges of motions with the adopted sign convention Motion

Max Range ADL Range

α, PS pronation (−) supination (+) [−86◦ , 71◦ ]

[−85◦ , 70◦ ]

[−71◦ , 73◦ ]

[−54◦ , 60◦ ]

◦

[−33◦ , 19◦ ]

β, FE extension (−) flexion (+) γ, RUD ulnar (−) radial (+)

◦

[−33 , 19 ]

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Robot Functional Design

This paper presents the development of RehaWrist.q, a cable-driven device to realise a lightweight and wearable end-effector solution as shown in Fig. 2a. The device is made of two platforms: the fixed platform is fixed by means of a bracelike structure to the arm to properly distribute the reaction forces; the mobile one instead moves together with the user’s hand, thanks to and handle. There is also a revolute joint between the forearm and the fixed platform to allow for PS motion. The two bases are connected by four actuated cables anchored at points A0 , B0 , A1 , and B1 , where the subscript 0 represents the fixed platform and 1 refers to the mobile one. The fixed platform has a width of 2L0 and is placed at a distance d0 from the wrist centre OW . Similarly, the mobile platform has a width of 2L1 and is at a distance d1 from OW (Fig. 2b).

Fig. 2. (a) Functional diagram of the proposed rehabilitation robot. Cable p1 is green, p2 is red, p3 is magenta, and p4 is blue. (b) Simplified representation of the proposed cable-driven robot for rehabilitation with its main design parameters.

It is possible to achieve one of the three DoF or a combination of them by properly tensioning the four cables by means of an actuation system. By −−−→ −−−→ −−−→ pulling cables p1 = A0 A1 and p2 = B0 A1 while releasing cables p3 = A0 B1 −−−→ and p4 = B0 B1 a radial deviation motion (γ˙ > 0) occurs. To obtain an ulnar −−−→ −−−→ deviation (γ˙ < 0), cables p3 = A0 B1 and p4 = B0 B1 must be pulled instead. In a similar fashion, the pairs p1 and p3 or p2 and p4 control the FE motion while the pairs p1 and p4 or p2 and p3 drive the PS motion. To properly control the motion of the hand, all four cables must be in tension. This means that there is always an undesired force compressing the hand on the wrist. As a result, platforms must be precisely sized to maximise the net force to create the correct motions while minimising the longitudinal force acting on the wrist. At the same time, to produce a lightweight and wearable device, the total dimensions must be lowered.

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Cable-Driven Parallel Robot Design

The design process of the wrist rehabilitation device RehaWrist.q involves defining an adimensional approach to size the proportions, outlining a quasi-static model of the robot, and proposing a final design. 3.1

Mechanism Kinematics

Figure 3 depicts the robot reference frames andtheir main parameters. {O0 } is the reference frame of the fixed platform centred on O0 and oriented in such a z0 points towards B0 . The mobile way that x ˆ0 lies along the forearm axis and ˆ base reference frame {O1 } is obtained by applying a combination of homogeneous transformations 0

1T

= Td0 TRαβγ Td1

(1)

where Td0 is the translation d0 x ˆ0 , TRαβγ is a rotation about the mobile axes with the sequence xyz by the angles α, β, and γ and then Td1 is the final ˆ1 . As introduced before, the generic i-th cable is represented by translation d1 x the vector pi . Finally, the vector ri defines the position of the anchor point on the mobile base of the i-th cable with respect to the centre of the wrist OW .

Fig. 3. References frames and other significant quantities of the rehabilitation robot when in neutral position (a) and in a generic one (b). Only the vectors related to cable 1 are shown to improve clarity.

3.2

Adimensional Synthesis

The objective of device synthesis is to find an optimal compromise between minimizing reaction forces on the wrist and maximizing the contribution of cable tension to useful torques on the hand. Similarly to what was proposed by Takeda and Funabashi [11], a transmission index τi for each cable that can

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quantify how much of the total tension of the cable is transmitted to the hand and generates a useful torque is defined as τi =

ri × ˆ a) p ˆ i · (ˆ =p ˆ i · (ˆ ri × ˆ a) ˆ pi 

(2)

where ˆ a is a generic rotation axis that passes through OW and p ˆ i · (ˆ ri × ˆ a) is the projection of the i-th cable direction along the most effective direction to generate a torque to rotate the hand about ˆ a. For further details, interested readers are referred to [2]. Figure 4 graphically represents the concept of the transmission ratio τi in the case of the three elementary rotations. In the case of the PS motion, the endz1 and p ˆ1 · ˆ z1 effector rotates about x ˆ1 , therefore the most effective direction is ˆ is the projection of the direction p ˆ i along ˆ z1 , or, in other words, it is the useful part of p ˆ i that contributes to the rotation. Likewise, in the case of a FE rotation, z1 . During a RUD the rotation axis is y ˆ1 and the most effective direction is again ˆ ri × ˆ z1 , motion instead, the rotation axis is zˆ1 and the most effective direction is ˆ ˆ1 and y ˆ1 which does not correspond to an axis of {O1 } but is a combination of x depending on d1 and L1 .

Fig. 4. Graphical representation of the effective direction for each elementary rotation.

Since the transmission index τi depends on unit vectors that depend on the geometric proportions and pose of the device, it is possible to define adimensional quantities related to the robot size to optimise its proportions to maximise τi . In particular, the following dimensionless parameters have been defined: K = L0 /d1 , J = L1 /d1 , Q = d0 /d1 . They respectively represent the size of the fixed and moving platforms and their distance from the centre of the wrist. The authors in [2] described in depth this approach and proposed three promising proportions. Here, the configuration that favours both PS and FE motions, where K = 8, J = 5, and Q = 3, is further developed to obtain a final design.

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Quasi-Static Analysis

Although RehaWrist.q’s proportions can be related to system efficiency, the actual size defines the requirements of the actuation system. Therefore, it is useful to derive the system dynamics equation (Fig. 5)

Fig. 5. Free body diagram of the mobile platform in quasi-static conditions.



⎡ ⎤    f1 ⎢f2 ⎥ p ˆ2 p ˆ3 p ˆ4 p ˆ1 ⎢ ⎥ = F1 r1 × p ˆ 1 r2 × p ˆ 2 r3 × p ˆ 3 r4 × p ˆ 4 ⎣f3 ⎦ T1 f4

(3)

ˆ i is the force applied by the i-th cable where fi is the tension of the i-th cable, fi p T T to the mobile platform, and F1 = [F1x , F1y , F1z ] and T1 = [T1x , T1y , T1z ] are, respectively, the net force and the net torque applied to the mobile platform. Equation 3 can also be written as Af = b

(4)

There are four cables to drive just three DoFs. Hence, an optimisation problem must be solved to solve the inverse dynamics to generate the required combination of three torques acting on the mobile platform by adequately tensioning the four cables. Thus, the following optimisation problem can be defined min f

subject to

g(f ) = F1x

(5a)

Ain f ≤ bin , Aeq f = beq ,

(5b) (5c)

f ≤ f ≤ f.

(5d)

The idea behind the optimisation is to compute the value of f that minimises the wrist joint compression force that the user could feel while using this device

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(Eq. 5a) . Equation 5b is the inequality constraint where Ain is made of the T

second and third rows of A and bin = F 1y , F 1z collects the maximum values of F1y and F1z . It is necessary to avoid applying too large lateral forces to the hand. Equation 5c is the equality constraint where Aeq is made of the last three T rows of A and beq = [T1x , T1y , T1z ] is the vector of the desired torques that have to be applied to the hand. At last, f and f are the lower and upper bounds of f and impose that all cables are always in tension but below a safety threshold. To achieve all of that, the Interior-Point optimisation algorithm is used. 3.4

Final Design

By averaging the values found in the literature [4,5,7], a maximum value of T 1x = T 1y = T 1z = 1.5 Nm has been assumed to size the actuation system and the dimensions of the robot. Thanks to the solution of the optimisation problem introduced early it was possible to evaluate the effects of the scaling factor d1 on the required tension on each cable. As expected, the larger d1 is, the better, however, by increasing d1 , the whole robot grows in size. Therefore, in the end, a trade-off value of d1 = 20 mm was chosen, obtaining the final size of the robot as: d0 = 60 mm, L0 = 160 mm, and L1 = 100 mm. At this stage, it was then possible to size the actuation system under the hypothesis that the maximum angular velocities of the hand during rehabilita˙ = 55◦ /s, and |γ| ˙ = 33◦ /s. The functional diagram of the tion are |α| ˙ = 55◦ /s, |β| actuation system and its final design are shown in Fig. 6. A DC motor (28LT12 289.49 by Portescap) with a planetary gearbox (R32-2R-0-574 by Portescap) drives a drum with a diameter of 50 mm where the cable is wounded. The cable is guided to the corresponding anchor point in the fixed platform by means of an idle pulley. Between the drum and the pulley, a small idle pulley on a lever is used to measure the cable tension by pushing onto a force sensor (FSR, force sensitive resistor). With this setup, it is possible to control the cable tension precisely without relying on current measurements that are usually particularly noisy. This sub-assembly is repeated for each cable. Figure 7 shows the overall final design of RehaWrist.q. The fixed platform is mounted on a commercial brace to allow the upper arm to support the reaction forces more comfortably. The forearm is placed in a cylindrical shell fixed to two curved rails to create the revolute joint between the forearm and the fixed platform. The hand holds an adjustable handle integral to the moving platform. All custom parts are planned to be 3D printed and made of a micro carbon fiber filled nylon as material. The overall expected weight is about 2 kg.

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Fig. 6. (a) Functional diagram of the cable-based actuation system (b) Final design of the cable-based actuation system

Fig. 7. Final design of the cable-driven robot for rehabilitation of the wrist joint RehaWrist.q.

4

Conclusion

This paper proposes the development of a 3 Dof cable-driven robot for the rehabilitation of the wrist joint named RehaWrist.q. Compared to the available robotic devices, this proposal is lightweight and wearable. Also, due to its end-effector architecture, it is not affected by the joint misalignment issue typical of exoskeleton solutions.

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To properly size the assistive robot, a new index, called transmission index, was defined to drive the definition of the robot proportions. Then, an optimisation problem based on a quasi-static system was defined to implement the force control required to safely use this device and to correctly size the actuation subsystem. Finally, the final design was presented. Once the first prototype will be manufactured, an extensive experimental campaign will be conducted. Acknowledgment. This work has been developed with the support of the Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellowships for Research in Japan.

References 1. Albanese, G.A., et al.: Assessment of human wrist rigidity and pain in posttraumatic patients. In: 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), pp. 89–94 (2019). https://doi.org/10.1109/ICORR.2019. 8779508. ISSN: 1945-7901 2. Colucci, G., et al.: A preliminary synthesis of a light and compact wearable cabledriven parallel robot for wrist joint rehabilitation. In: Proceedings of Jc-IFToMM International Symposium, vol. 5, pp. 57–64. Japanese Council of IFToMM, Yokohama (2022). https://doi.org/10.57272/jciftomm.5.0 57. https://www.jstage.jst. go.jp/article/jciftomm/5/0/5 57/ article 3. Crowe, C., et al.: Global trends of hand and wrist trauma: a systematic analysis of fracture and digit amputation using the Global Burden of Disease 2017 Study. Inj. Prev. 26(Suppl 2), i115–i124 (2020). https://doi.org/10.1136/injuryprev-2019043495. https://injuryprevention.bmj.com/content/26/Suppl 2/i115. BMJ Publishing Group Ltd Section: Original research 4. Kane, P.M., Vopat, B.G., Got, C., Mansuripur, K., Akelman, E.: The effect of supination and pronation on wrist range of motion. J. Wrist Surg. 03(3), 187–191 (2014). https://doi.org/10.1055/s-0034-1384749. https://www.thieme-connect.de/ DOI/DOI?10.1055/s-0034-1384749. Thieme Medical Publishers 5. Krebs, H.I., et al.: Robot-aided neurorehabilitation: a robot for wrist rehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. 15(3), 327–335 (2007). https:// doi.org/10.1109/TNSRE.2007.903899. IEEE Transactions on Neural Systems and Rehabilitation Engineering 6. Kwakkel, G., Kollen, B.J., Krebs, H.I.: Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabilitation Neural Repair 22(2), 111–121 (2008). https://doi.org/10.1177/1545968307305457. SAGE Publications Inc STM 7. Liu, Y.C., Irube, K., Takeda, Y.: Kineto-static analysis and design optimization of a 3-DOF wrist rehabilitation parallel robot with consideration of the effect of the human limb. Machines 9(12), 323 (2021). https://doi.org/10.3390/ machines9120323. https://www.mdpi.com/2075-1702/9/12/323. Multidisciplinary Digital Publishing Institute 8. Neumann, D.A.: Kinesiology of the Musculoskeletal System - Foundations for Rehabilitation, 3rd edn. Elsevier Health Sciences, Amsterdam (2016)

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9. Reinkensmeyer, D.J., Kahn, L.E., Averbuch, M., McKenna-Cole, A., Schmit, B.D., Rymer, W.Z.: Understanding and treating arm movement impairment after chronic brain injury: progress with the ARM guide. J. Rehabil. Res. Dev. 37(6), 653–662 (2014). https://escholarship.org/uc/item/65z7c4s7 10. Ryu, J., Cooney, W.P., Askew, L.J., An, K.N., Chao, E.Y.S.: Functional ranges of motion of the wrist joint. J. Hand Surg. 16(3), 409–419 (1991). https://doi.org/10. 1016/0363-5023(91)90006-W. https://www.sciencedirect.com/science/article/pii/ 036350239190006W 11. Takeda, Y., Funabashi, H.: A transmission index for in-parallel wire-driven mechanisms. JSME Int. J. Ser. C 44(1), 180–187 (2001). https://doi.org/10.1299/jsmec. 44.180

Lifting Assist Device for Transfer in Cooperation with Caregivers Mari Kurata1(B) , Ming Jiang1 , Kotaro Hoshiba1 , Yusuke Sugahara1 , Takahiro Uehara2 , Masato Kawabata2 , Ken Harada2 , and Yukio Takeda1 1 Department of Mechanical Engineering, Tokyo Institute of Technology, Tokyo, Japan

{kurata.m.ae,jiang.m.ad,takeda.y.aa}@m.titech.ac.jp 2 Hirakata General Hospital for Developmental Disorders, Osaka, Japan {t.uehara,kawabata,ken-harada}@hirakataryoiku-med.or.jp

Abstract. To promote good health and well-being is one of the Sustainable Development Goals (SDGs) drawn by the United Nations. To this end, the development of assistive devices is important to improve the quality of life for both caregivers and patients. This study aims to provide support in transfer assist, which is known to be strenuous work in the care environment. In this study, a concept of a lifting assist device for transfer that is able to adjust the patient’s posture according to the intention of the caregiver is proposed. The device can reduce both physical and mental burden of caregivers and patients. The main components of the device are motors, load cells and wires. The device can be operated by the values of the tension force of wires. Since the proposed device has a simple structure, its system is easy to use and inexpensive such that it can be widely introduced, which can contribute to the realization of the SDGs. Two subject experiments including the threshold determination experiment and the transfer simulation experiment were conducted using a fabricated full-scale prototype. In the first experiment, the intention detection strategy based on the change of the tension force of wires was determined, and was applied to the prototype. In the second experiment, it was confirmed that the proposed intention detection method worked well and the upper body posture changed appropriately during the lifting process. Keywords: SDG3 · Robotics and mechatronics · Assist device · Transfer · Lifting process · Human cooperating system · Intention detection · Posture adjustment

1 Introduction The 17 Sustainable Development Goals (SDGs) were adopted by the United Nations in 2015 [1]. Global aging has been becoming a more severe problem, and it has led to the lack of nursing workforce. It is crucial to install assistive devices to solve this problem in line with SDG3, which aims to ensure healthy lives and promote well-being for all ages. Transferring a patient from one place to another, such as from a bed to a wheelchair, is one of the most strenuous nursing tasks for caregivers in the nursing field [2]. As Occupational Safety and Health Administration (OSHA) guidelines dictate how to transfer © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 146–153, 2023. https://doi.org/10.1007/978-3-031-32439-0_17

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and how to choose the appropriate device depend on the patient’s symptoms [3]. The lifting process of transferring severe patients is especially hard because they cannot move their remaining functions by themselves, and caregivers have to lift their whole body to transfer. Due to heavy work, the policy that caregivers should not lift patients called “No Lifting Policy” was suggested and use of transfer assist devices is strongly recommended [4]. On the other hand, it is important for the patients to feel at ease and comfortable with the devices because a patient is transferred frequently everyday and that is deeply involved in their quality of life including the improvement of psychological awareness and health [5]. Thus, the development of transfer assist devices helps both caregivers and patients to be more comfortable and healthy. Recently, lifting assist devices such as mobile floor lifts and ceiling lifts are widely used for severely disabled patients [6]. A sling seat is placed under the patient and wires connect the seat to the device, then the patient wrapped by the seat is lifted. These lifts are superior to other assistive devices in the aspect that they can reduce caregivers’ burden with a relatively low cost, short operation time and easier usage than other devices with a similar function [7]. However, when using a lifting assist device, the patient’s position is higher than the case without any device, which is called human assistance. Because of this, the patient might sway in the air when the caregiver’s hands leave the patient due to remote controller operation [8]. Such an unstable status may cause the patient to feel anxious and unsafe. Furthermore, the patient runs the risk of injury or tipping over from hitting the bed, the wall or the lifting device. Because of these problems, the installation rate of lifting assist devices is still low and human assistance is often chosen [9]. Hirakata General Hospital for Developmental Disorders is a welfare facility where many patients have severe disabilities which include conditions with limb deformities and limitations in joint motions. Caregivers do transfer assistance frequently between a bed and a wheelchair during the day for daily living and rehabilitation. In this process, caregivers in this facility use mobile floor lifts or transfer by human assistance. A characteristic of conventional lifts is that the patient’s lifting posture is fixed in a certain orientation due to the device structure whose sling seat wires gather at one hung point. Caregivers are concerned that unreasonable postures, outside the range of motion of patient’s joints, may cause them pain. Compared with mobile floor lifts, human assistance is preferred as caregivers can adjust the upper body posture of the patients by observing their movements and feedbacks, such as facial expressions, during the lifting process. Since the caregiver directly touches the patient, it also makes the patient feel relieved. Hence, reflecting the caregiver’s intention in operating the device is also considered essential to enable the caregiver to change the position and posture of the patient freely by observing the patient’s expression. To solve the problem of preventing swaying, a mobile floor lift that can be operated by a power assist system, with no remote-controlled operation, has already been developed [10]. Using this device, the caregiver applied force to the patient directly and the device was able to detect the caregiver’s intention depending on the tension force. However, the patient’s posture during lifting was determined uniquely so it is difficult to use this device for severely disabled patients. Therefore, the purpose of this study is to develop a cooperative lifting assist device that can reflect the caregiver’s intention and change the patient’s posture during lifting.

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This will reduce the burden on both the caregivers and the patients during transfer and improve comfort for patients with severe disabilities who have not been using existing lifts. Based on this concept, the structure of the full-scale device and the results of subject experiments conducted with the device is described.

2 Method 2.1 Proposed Concept of Lifting Assist Device Considering the care environment in Hirakata General Hospital for Developmental Disorders as a case study, the case where a caregiver who lifts a patient from a bed to a wheelchair was the focus of this paper. Figure 1(a) shows a situation where a caregiver operates the proposed device to lift a patient. A sling seat is placed under the patient to hold the whole body. The patient’s weight is supported by two wires connected to the seat near the waist and shoulder of the patient. The caregiver touches the back sides of the patient’s shoulder and knees with both arms. During the lifting process, two motion patterns for controlling the patient’s position and posture are proposed, including the whole body’s translational motion and the upper body’s rotation, as shown in Fig. 1(b). To do these movements, three intentions of the caregiver shown in Fig. 1(c) are considered necessary to be separately detected during operation, which are defined as static, whole and up. Static represents the intention to keep the patient’s current position and orientation; Whole represents the intention to move upward the patient’s whole body; Up represents the intention to raise the patient’s upper body. Once the caregiver applies force to the patient with intention, the tension values should change accordingly. Detection of the caregiver’s intention will be done by the measured tension force of the two wires. Based on the detected intention, desired motion is given as a reference to the controller of the device, and wires are wound up by each motor. This concept of intention detection using wire tension values was investigated by experiments with a fabricated one-third scale prototype [11]. In this paper, this concept is applied to the full-scale device. 2.2 Experiments with Full-Scale Prototype Structure of the Fabricated Full-Scale Prototype. A full-scale device was designed, whose composition and photo are shown in Figs. 2(a) and 2(b). A sling seat is laid under a dummy, whose height and mass are 165 cm, 43 kg, respectively. The dummy is lifted with two wires, denoted as I and II, whose tension values are T1 and T2 , respectively. Movable pulleys are connected directly below load cells I and II. Each of them measures the tension of the corresponding wire. Wire I’ is connected to the sling seat near the dummy’s waist, and wire II’ is connected to the sling seat near the dummy’s  shoulder, and each of tension values T1 andT2 are the same as T1 /2andT2 /2 because of movable pulleys. Wires I and II are wound up by changing the angles of motors I and II, θ1 and θ2 , respectively. Three LED lights are set to the device frame to instruct the subject which intention should be thought of during the experiment. The hip position d and the orientation angle θp of the dummy shown in Fig. 2(a) are measured.

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Intention Detection Method for Operating the Device. The proposed operation flow for intention detection is shown in Fig. 2(c). To determine the values used in Conditions I and II, two subject experiments were conducted, which are discussed in the following section. It was assumed that when the intention is static, the subject only applies small forces to the dummy. Both T1 and T2 should have relatively large values compared with the case of up and whole because the dummy is mainly supported with the wires. Based on this assumption, T1 + T2 was used as a measure for discriminating between static and the other two intentions. As to discriminate between the up and whole intentions, it is assumed that the ratio R calculated by Eq. (1) should be effective. It is assumed that the smaller the R value is, the stronger the intention to lift the upper body. R=

T2 T1 +T2

× 100%

(1)

Experiment Methods for Evaluating Intention Detection. Two experiments were conducted, including the threshold determination experiment and the transfer simulation experiment. The threshold determination experiment aims to investigate the appropriate methods used for determining the subject’s intention. In this experiment, the subject applied force on the dummy continuously with static, up and whole intentions each time. The dummy’s upper posture is changed slowly during the experiment by changing θ2 due to be measured different values of T1 and T2 in each upper posture regardless of the intentions. Then, T1 and T2 in different intention conditions are measured, respectively.

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d, θp

(b) Fabricated full-scale prototype

(c) Flow for detecting the intentions

Fig. 2. Full-scale prototype based on the proposed concept.

Based on these measured data collected in the threshold determination experiment, each subject’s decision criteria and thresholds are determined to detect the subject’s intention in the later transfer simulation experiment. In the transfer simulation experiment, intentions that the subject should think of are instructed by lightening each LED: in the order of up → static → whole → static for three sets. Subjects applies force as guided by the LED. If the device can detect subject’s intention correctly, motors I and II are moved respectively as shown in Fig. 2(c). During this experiment, the results of the intention detected by the device are recorded. The proposed strategy flow of intention detection is evaluated by checking the consistency rate between the instructed intention and the detected intention.

3 Results and Discussions Figures 3(a) and 3(b) show the values of the total tension T1 + T2 , the ratio value R in each of θ2 and determined thresholds of them to discriminate the intentions of subject #1 as an example. It is found that the collected data of four subjects showed a similar tendency in both T1 + T2 and R. In Fig. 3(a), the data shows a gap between static and the other two intentions. Hence, the condition to discriminate the intention static was determined as a linear function of (θ2 − θ1 ) in Eq. (2) with the threshold shown in the right side of the equation. The condition to discriminate between the intention up and whole was determined as a linear function of (θ2 − θ1 ) in Eq. (3) with the threshold shown in the right side of the equation.

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Condition I for discrimination of static from others: (pS,up +pS,whole )+2pS,static 4

T1 + T2 ≤ · (θ2 − θ1 ) +

(qS,up +qS,whole )+2qS,static

(2)

4

Condition II for discrimination between up and whole: p +p q +q R ≤ ( R,up 2 R,whole ) · (θ2 − θ1 ) + ( R,up 2 R,whole )

(3)

pS,static , pS,up and pS,whole are the slopes of the approximate straight-line calculated based on each data in Fig. 3(a). qS,static , qS,up and qS,whole are the intercepts of the same line. The subscripts S and R represent the data for the sum of T1 and T2 , and R defined with (1), respectively. The subscripts static, up and whole represent each intention condition, respectively. Equations (2) and (3) are the decision conditions for discriminating each intention adopted in the flow shown in Fig. 2(c). Each threshold for T1 + T2 and R for four subjects was summarized in Figs. 3(c) and (d). It is interesting to note that the data from all four subjects showed similar threshold tendency, which suggests that different users may share and use devices with a common discrimination condition. Figure 4(a) shows the results of subject #1’s intention (indication by LED) and the intention detected by the device obtained in the transfer simulation experiment. The experimental time was 72 s. It was found that the device successfully detected the caregiver’s intentions with a high consistency. The consistency rate for subjects #1–4 was 88.4%, 86.6%, 78.9% and 80.8%, respectively. The average consistency rate of the four subjects was 83.7%. The inconsistencies in intention detection are expected to be mainly caused by the delay between the timing for giving the instructions by the LED and the timing of subject’s actual reaction to start to apply force on the dummy. This delay will not occur in the real use situation because there is no delay time between the thinking of the intention and the application of force by the caregiver. Also, this delay problem can be reduced by accelerating the response time of the device, as this will allow the subjects to feel that the device is more responsive to the force applied. Figure 4(b) shows the position d and the orientation angle θp of the dummy that were measured from the positions of markers attached to the dummy. By correctly identifying the subject’s intention based on the values of tension force, the appropriate motion of the dummy was performed.

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(b) Transition of d and θp of subject #1

Fig. 4. Results of transfer simulation experiment

4 Conclusion A full-scale device was fabricated based on the proposed concept of a lifting assist device that detects the caregiver’s intention based on the tension force of wires and adjusts the patient’s posture during the lifting process. Two subject experiments, including the threshold determination and the transfer simulation experiments, were conducted to confirm that the proposed strategy functioned appropriately for intention detection. In the first experiment, it was confirmed that the appropriate thresholds were determined for detecting each caregiver’s intentions and each threshold of all subjects showed a similar tendency, which indicates that unified detection thresholds may be applied. In the second experiment, it was confirmed that the device detected the intentions of the subjects according to the threshold determined above and the dummy’s position and posture were controlled appropriately. Further subject experiments will be carried out

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to investigate user-independent characteristics of intention detection and improve the comfort of the operation system with the full-scale device. This study aimed to develop transfer devices that can improve the quality of life for caregivers and patients. Since our proposed device has a simple structure, it can also provide insights that can lead to more widespread use of transfer devices in the lifting process, which can contribute to realizing the SDGs. Acknowledgement. The subject experiments conducted in this study followed the Ethical Guidelines for Life Science and Medical Research Involving Human Subjects and have been approved by the Ethics Review Committee of Tokyo Institute of Technology (No. 2022251).

References 1. World Health Organization: World health statistics 2016: monitoring health for the SDGs sustainable development goals (2016) 2. Collins, J.W., Wolf, L., Bell, J., Evanoff, B.: An evaluation of a “best practices” musculoskeletal injury prevention program in nursing homes. Inj. Prev. 10(4), 206–211 (2004) 3. Reese, C.D., Eidson, J.V.: Handbook of OSHA Construction Safety and Health, 2nd edn. CRC Press, Boca Raton (2006) 4. Choi, S.D., Brings, K.: Work-related musculoskeletal risks associated with nurses and nursing assistants handling overweight and obese patients: a literature review. Work 53(2), 439–448 (2015) 5. Kasven-Gonzalez, N., Souverain, R., Miale, S.: Improving quality of life through rehabilitation in palliative care: case report. Palliat. Support. Care 8(3), 359–369 (2010) 6. Miller, A., Engst, C., Tate, R.B., Yassi, A.: Evaluation of the effectiveness of portable ceiling lifts in a new long-term care facility. Appl. Ergon. 37(3), 377–385 (2006) 7. Vinstrup, J., Jakobsen, M.D., Madeleine, P., Andersen, L.L.: Biomechanical load during patient transfer with assistive devices: cross-sectional study. Ergonomics 63(9), 1164–1174 (2020) 8. Sivakanthan, S., Blaauw, E., Greenhalgh, M., Koontz, A.M., Vegter, R., Cooper, R.A.: Person transfer assist systems: a literature review. Disabil. Rehabil. Assist. Technol. 16(3), 270–279 (2021) 9. Kucera, K.L., et al.: Factors associated with lift equipment use during patient lifts and transfers by hospital nurses and nursing care assistants: a prospective observational cohort study. Int. J. Nurs. Stud. 91, 35–46 (2019) 10. Funato, K., Tasaki, R., Miyoshi, T., Kakihara, K., Terashima, K.: Design and analysis of novel nursing transformative assistive robot comprised of transfer and omnidirectional carrying. J. Robot. Soc. Japan 37(1), 81–91 (2019). (in Japanese) 11. Kurata, M., et al.: Concept proposal of cooperative transfer assist device capable of controlling posture of patient’s upper body. In: LIFE2022, Sapporo, Japan, 19–21 August 2022, pp. 442– 445 (2022). (in Japanese)

Design and Prototyping of a Semi-wearable Robotic Leg for Sit-to-Stand Motion Assistance of Hemiplegic Patients Micah J. P. Alampay(B) , Ming Jiang, Yusuke Sugahara, and Yukio Takeda Department of Mechanical Engineering, Tokyo Institute of Technology, 2-12-1(I6-09) Ookayama, Meguro-Ku, Tokyo 152-8552, Japan {alampay.m.aa,takeda.y.aa}@m.titech.ac.jp

Abstract. With the increasing number individuals living with the long-term effects of stroke, it has become more important to provide accessible healthcare, in line with the UN SDG 3 on promoting good health and well-being. Hemiplegia, the paralysis of one side of the body, is a common side effect of stroke. The condition of hemiplegia provides unique challenges for afflicted individuals, including asymmetric body strength and limited mobility, especially in the sit-tostand (STS) motion. High weight-bearing asymmetry also leads to poor mobility outcomes and increased fall risk for hemiplegic patients. To address these concerns, a semi-wearable sit-to-stand assist robot is proposed to provide assistive force, motion guidance, and stability during the STS motion. The proposed robot is a planar 2-DoF assistive robot attached to the hip of the user that acts as an extra support leg during the STS motion. The designed robot is semi-wearable, and is worn when needed during the STS motion, but can easily be detached when not needed. The robot was designed to reduce the weight-bearing asymmetry of hemiplegic users during sit-to-stand, to allow them to complete the motion in a more symmetric and stable manner. The design requirements and concept are outlined, along with the control scheme for device operation. Human experiments demonstrated the ability of the assist robot to reduce average weight-bearing asymmetry during the STS motion. Keywords: SDG3 · robotics and mechatronics · assistive robotics · hemiplegia · sit-to-stand · wearable robotics

1 Background From 1990 to 2017, it was found that there has been an overall 3.1% increase in agestandardized stroke prevalence rate, and a greater number of people must live with the long-term impairments caused by stroke [1]. Motor impairment on one side of the body, i.e., hemiplegia or hemiparesis, is a common effect of stroke, with about 80% of survivors being affected [2]. Patients with hemiplegia experience problems in active movement and mobility. Maintaining mobility is critical in performing activities of daily living (ADL), and one important ADL impaired by hemiplegia is the sit-to-stand (STS) motion [3]. For © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 154–161, 2023. https://doi.org/10.1007/978-3-031-32439-0_18

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impaired individuals, the assistance of a caregiver or the use of large STS lifts is needed during the motion, as it is a significant fall risk [4]. Hemiplegia also affects how the STS motion is conducted, and significant asymmetry in leg weight-bearing and during the STS motion has been observed in hemiplegic individuals. Cheng et al. found that average weight-bearing asymmetry between the affected and non-affected legs during the STS motion is higher in hemiplegic patients, and that higher asymmetry was related to a greater risk of falls and poorer mobility outcomes [5]. Effort should be exerted to reduce weight-bearing asymmetry and help the patient perform the STS motion more symmetrically and avoid non-use syndrome. Reduction of weight-bearing asymmetry and more use of the paretic leg is critical for long-term mobility and quality of life of hemiplegic patients [3]. Devices have been developed to provide support and assistance for elderly or injured individuals in the STS motion, but not many have been designed to address the challenges faced by hemiplegic patients. External support devices, such as STS lifts, are sold commercially to aid in the STS transfer in hospitals or care facilities. However, they can be difficult to use in smaller home environments [6]. Wearable assistive devices, particularly exoskeletons such as ReWalk or other similar commercial exoskeletons, are also used to increase mobility of elderly or impaired users [7]. While these devices can provide beneficial assistive force, their cost is still prohibitive, making them not accessible for many people. Furthermore, such exoskeletons can take a long time to don and take off, making them inconvenient to use regularly, especially for hemiplegic users [8]. Other directions for the design of wearable assistive devices for STS have also been explored. Zheng et al. developed a pneumatically actuated semi-wearable robotic device for sit-to-stand assistance that was designed to be easily detached after completion of the STS process [9]. Treers et al. developed lightweight supernumerary robotic limbs for sitting/standing assistance [10]. These designs provide interesting directions for the development of STS assist devices, however they do not address the unique challenges presented by hemiplegia, such as asymmetrical loading of the legs, differences in muscle activation, and balance in the frontal plane. There is a dearth of assistive devices for hemiplegic individuals, and the increasing number of post-stroke patients means there is a need to develop interventions to aid in the care of hemiplegic patients, in line with the UN Sustainable Development Goal 3 of Good Health and Well-being [11]. Therefore, the objective of this study is to develop an STS assist robot for hemiplegic patients that can provide support and reduce the weight-bearing asymmetry of the legs during the STS motion. The current research expands on previous work done on the concept and design of the STS assist robot [12]. Another method for determining the target STS path is presented, along with initial experiments on a fabricated prototype to assess the effectiveness of the assist robot.

2 Sit-to-Stand Assist Robot Design A semi-wearable sit-to-stand assist robot for hemiplegic patients is proposed to address the unique challenges posed by their ailment, such as their asymmetrical body strength and reduced coordination. Furthermore, the design is focused on maintaining the physical capabilities of the hemiplegic person, as exercise, especially of the paretic leg, is

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important for their overall quality of life [3]. The design concept for the STS assist robot can be seen in Fig. 1a. The STS assist robot is a planar 2-DOF assistive robot attached to the user at the hip to provide stability and assistive force throughout the STS motion. It acts as a support leg to compensate for the loss of strength of the hemiplegic limb and perform the STS motion more symmetrically. The robot will work in coordination with the human user and should provide assistive force while still allowing the user to exert force and effort to perform the motion on their own. The robot provides motion assistance by guiding the user along the correct STS motion path and facilitating more use of the affected leg and more symmetrical execution of the motion. The structure and actuation of the robot will provide stability to the user in the frontal and sagittal planes during the STS motion. The designed robot is semi-wearable, meaning it is worn when needed during the STS motion, but can be easily detached when not needed. A gait belt is used as the interface between the robot and the user and provides a stable point for application of assistive force.

Fig. 1. (a) Model of the assist robot. (b) Schematic diagram of the assist robot with a user. (c) Image of the fabricated prototype being worn by a user.

Figure 1b shows the schematic diagram of the proposed assist robot attached to a user used to estimate the load to be supported by the actuators. The base of the robot was assumed to be fixed to the ground during the motion and in line with the user’s feet. The robot ankle, knee joint, and hip attachment are represented by points A, B, and C, respectively. Point D represents the center of mass of the user at the torso. The relative position vectors of the points, DC , CB , and BA, were calculated using Eqs. (1) to (3). The estimated actuator torques, τ1 and τ2 , were calculated using Eqs. (4) and (5). q is the proportion of total body mass to be supported by the robot, taken to be 10%, as this allows the asymmetry between the affected and unaffected side to be reduced from the range of a hemiplegic faller to the range of a hemiplegic non-faller [5]. Link lengths of 350 mm for l1 and 600 mm for l 2 were used in the calculations. θhip values and the estimated position of point C at the hip throughout STS motion path were calculated using measurements by Nuzik et al. [13]. Inverse kinematics was used to obtain an initial estimate of θ1 and θ2 needed to reach point C during the STS motion. The user

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was assumed to have a mass of 62.5 kg, and masses of 2 kg for m1 and m2 were assumed. The effects on inertia on the assist robot limbs were neglected. Based on the calculations, about 25 N·m for τ1 , and 60 N·m for τ2 would be needed.    cos θhip + θ1 + θ2 (1) DC = ltorso sin θhip + θ1 + θ2   cos(θ1 + θ2 ) C B = l1 (2) sin(θ1 + θ2 )   cos θ2 B A = l2 (3) sinθ2   τ1 = m1 g × C2B + qmuser g × (DC + C B ) (4) τ2 = m2 g ×



BA 2



+ m1 g ×



CB 2

 + BA + q(muser g) × (DC + C B + BA )

(5)

Based on the estimated torque requirements, two Turnigy Aerodrive SK3-5065 BLDCs with 1:30 and 1:100 gear reduction for actuators 1 and 2, respectively, were selected for actuation. The robot prototype was controlled using an ODrive v3.6 BLDC Motor Controller together with an Arduino Mega microcontroller. Figure 1c shows the fabricated prototype being worn by a user.

3 Control Scheme of the STS Assist Robot To determine the output position of the assist robot actuators, it is necessary for the STS motion of the user to be tracked in real time. Treers et al. measured the angle of the user’s thigh with respect to the horizontal, called the leg angle, using an accelerometer and related it to the output force profile of an assistive device during the STS motion [10]. This method showed that the leg angle can be used to determine the progression of an individual through the STS motion, and that the leg angle corresponds to the position of an individual during the STS motion. For the proposed STS assist robot, the leg angle of the user, θleg , is related to the user’s hip position during STS, where the assist robot is attached to the user. The hip position corresponds to specific actuator angles of the assist robot, θ1 and θ2, needed to reach that position. The relationship between leg angle and hip position varies between users. To determine this relationship for a particular user, the user is asked to do their target STS motion while wearing the unactuated assist robot. An Inertial Measurement Unit (IMU) is used to measure the user’s leg angle in real time. As the STS motion is done, the leg angles of the user are measured together with the actuator angles which are measured using the assist robot motor encoders, and a relationship between the leg angles and target actuator output angles is be obtained. This process only needs to be conducted once for each user, and the obtained relationship allows the assist robot actuator output angles can be controlled in real time during the STS motion as a function of the IMU-measured leg angles, f(θleg ). This method

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Fig. 2. (a) Image of the assist robot worn by a user with relevant angles marked. (b) Process diagram for obtaining target STS path. (c) Target actuator angles vs leg angles during the STS motion for one test subject, with deviation from average marked by shaded area.

allows individualized target STS paths to be generated for each user. Figure 2b summarizes the methodology to relate the user STS motion to the target assist robot motion. The obtained relationship between the user’s leg angles and actuator angles is loaded into the microcontroller which is used for real-time control of the robot. The IMU readings of the leg angle are used to command the actuators to go to the target angles, based on the relationship. The target output angles are commanded to the assist robot using PID position control, and actuator encoders provide feedback for the actual position of the robot. The progress of the human throughout the STS motion is monitored by the IMU every 20 ms, updating the target actuator output angles.

4 Experiment Design and Methodology Initial assessment of the capacity of the designed assist robot to reduce weight-bearing asymmetry of the designed robot was done with healthy test subjects wearing a hemiplegia simulation suit (Sakamoto Model Corporation), which consists of hard plastic splints fastened with elastic straps to the ankle and knee of one leg to prevent bending of the joints, as seen in Fig. 3a. This restriction to one leg causes the subject to generate force asymmetrically between the left and right sides. A total of four (N = 4, 4 male) healthy test subjects were recruited for the experiments (age: 28 ± 3.96 years, body mass: 64.31 ± 3.13 kg, height: 175.75 ± 4.32 cm). The experiments conducted were approved by the Tokyo Institute of Technology Human Subjects Research Ethics Review Committee (Permit No. 2022302). The experiment consisted of two phases, calibration, and STS measurement. During the calibration phase, the target STS path of the robot was determined. The subjects were asked to wear the unactuated assist robot, and then do the STS motion normally 10 times, to obtain the target assisted STS motion path. In the STS measurement phase, the test subject was asked to complete three sets of STS motions: normal, with the hemiplegic restriction, and with the hemiplegic restriction and assist robot. For each set, the test subject was asked to do the STS motion at least

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five times. Ground reaction forces under the left and right feet during the STS motion were measured using 60 cm × 90 cm embedded force plates (Kistler Group, USA) under the left and right foot (with assist robot, as needed). Motion data of the left and right shoulders were also recorded using a motion capture system (Motion Analysis Corporation, USA) to determine the timing of the start and end of the STS process. Average weight-bearing asymmetry between the left and right legs during the STS motion as a percentage of body weight was analyzed.

Fig. 3. (a) Experiment setup with user wearing assist robot and hemiplegic restriction. (b) Ground reaction forces (GRF) of STS motion of one test subject during the experiment.

5 Results and Discussion The individual motion paths generated during the calibration phase were able to reliably follow the STS motions for all the test subjects, and an example of the generated actuator output angles vs leg angles for one test subject can be seen in Fig. 2c. The results of the human test subject experiments for the three sets of STS motions, normal, with hemiplegic restriction, and with hemiplegic restriction and assist robot, are summarized in Table 1. A graph of ground reaction forces (GRF) exerted during one STS motion for all three conditions of one test subject can be seen in Fig. 3b. The restriction on one leg of the test subjects to simulate hemiplegia was able to induce an asymmetric force generation condition on the test subjects. Test subjects 1 and 2 demonstrated a very high degree of average weight-bearing asymmetry with the restriction on one leg, at 80.9% and 71.8%, respectively. Test subjects 3 and 4 exhibited a high degree of force asymmetry at 45.5% and 46.8%, respectively. While wearing the assist robot, average weight-bearing asymmetry during STS was significantly reduced for test subjects 1 and 2, at 55.7% and 46.4%, a roughly 25% decrease in asymmetry for both. Asymmetry was slightly reduced for test subjects 3 and 4 with the assist robot, at 43.8% and 44.6%, respectively, about a 2% decrease. These results show that the assist robot can facilitate greater use of the restricted side. The restriction also caused a slight increase in time taken to conduct the STS motion, however this time was still within hemiplegic STS speed of about 3.3 s. in literature [14].

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Test Subject 1

2

3

4

Duration (s)

Ave. Asymmetry (%BW)

Normal

1.22

1.3

Hemiplegic

1.39

80.9

Hemi. w/robot

2.45

55.7

Normal

1.37

3.2

Hemiplegic

1.88

71.8

Hemi. w/robot

2.93

46.4

Normal

1.30

4.4

Hemiplegic

1.45

45.5

Hemi. w/robot

2.79

43.8

Normal

1.79

1.5

Hemiplegic

2.71

46.8

Hemi. w/robot

2.88

44.6

The experiment could not fully simulate overall weakness or cognitive impairments of a hemiplegic patient, so the test subjects could still utilize motion strategies that a hemiplegic individual would not be able to. An increase in time taken to complete the STS motion while the assist robot was worn can be observed, due to the designed speed for the assist robot being based on the average speed of a hemiplegic individual, but it was still within the STS time taken by hemiplegic individuals. Overall, the experiments demonstrated the capability of the robot to reduce average weight-bearing asymmetry when one leg is limited in force generation capacity.

6 Conclusion The design, prototype, and initial experiments with a novel planar 2-DoF robotic leg for assistance in the STS motion of hemiplegic individuals was presented. The robot was designed to address the unique requirements provided by the asymmetrical body strength condition of hemiplegic individuals by providing stability in the frontal and sagittal planes and by reducing weight bearing asymmetry of hemiplegic users during the STS motion to facilitate more use of the paretic leg. The design of the robot and the method for generating the target STS motion path allowed the assist robot motion to be easily adjusted for users of different sizes. A prototype of the assist robot was fabricated and experiments with healthy human test subjects were conducted while having their motion restricted to simulate the asymmetric weight-bearing of hemiplegic individuals. The experiments demonstrated the capability of the assist robot to reduce average weightbearing asymmetry during the STS motion when one leg is limited in force generation capacity. The proposed device can aid in improving mobility of hemiplegic patients, and further work to improve the assistive capacity of the device and robustness versus falls

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will be done to develop an effective and accessible assist robot, in line with the UN SDG 3 on promoting good health and well-being. Acknowledgement. We would like to thank NSK Ltd. for their support from 2020–2021.

References 1. Avan, A., et al.: Socioeconomic status and stroke incidence, prevalence, mortality, and worldwide burden: an ecological analysis from the Global Burden of Disease Study 2017. BMC Med. 17, 1–30 (2019) 2. Langhorne, P., Coupar, F., Pollock, A.: Motor recovery after stroke: a systematic review. Lancet Neurol. 8, 741–754 (2009) 3. Boukadida, A., Piotte, F., Dehail, P., Nadeau, S.: Determinants of sit-to-stand tasks in individuals with hemiparesis post stroke: a review. Ann. Phys. Rehabil. Med. 58, 167–172 (2015) 4. Robinovitch, S.N., et al.: Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study. Lancet 381, 47–54 (2013) 5. Cheng, P.T., Liaw, M.Y., Wong, M.K., Tang, F.T., Lee, M.Y., Lin, P.S.: The sit-to-stand movement in stroke patients and its correlation with falling. Arch. Phys. Med. Rehabil. 79, 1043–1046 (1998) 6. Tang, R., Poklar, M., Domke, H., Moore, S., Kapellusch, J., Garg, A.: Sit-to-stand lift: effects of lifted height on weight borne and upper extremity strength requirements. Res. Nurs. Health 40, 9–14 (2017) 7. Rewalk Robotics Inc.: ReWalk. https://rewalk.com/ 8. Vaughan-Graham, J., Brooks, D., Rose, L., Nejat, G., Pons, J., Patterson, K.: Exoskeleton use in post-stroke gait rehabilitation: a qualitative study of the perspectives of persons post-stroke and physiotherapists. J. NeuroEng. Rehabil. 17, 1–15 (2020) 9. Zheng, H., Shen, T., Afsar, R., Kang, I., Young, A.J., Shen, X.: A semi-wearable robotic device for sit-to-stand assistance. In: IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 204–209 (2019) 10. Treers, L., et al.: Design and control of lightweight supernumerary robotic limbs for sitting/standing assistance. In: Kuli´c, D., Nakamura, Y., Khatib, O., Venture, G. (eds.) ISER 2016. SPAR, vol. 1, pp. 299–308. Springer, Cham (2017). https://doi.org/10.1007/978-3319-50115-4_27 11. UN General Assembly: Transforming our world : the 2030 agenda for sustainable development (2015) 12. Alampay, M.J.P., Jiang, M., Sugahara, Y., Takeda, Y.: A semi-wearable robotic leg for assistance in the sit-to-stand motion of hemiplegic patients. In: 28th Robotics Symposia. Wakayama, Japan (2023) 13. Nuzik, S., Lamb, R., Vansant, A.N.N., Hirt, S.: Sit-to-stand movement pattern a kinematic study. Phys. Ther. 66, 1708–1713 (1986) 14. Faria, C.D., Teixeira-Salmela, L.F., Silva, E.B., Nadeau, S.: Expanded timed up and go test with subjects with stroke: reliability and comparisons with matched healthy controls. Arch. Phys. Med. Rehabil. 93, 1034–1038 (2012)

Comprehensive Control Strategy Design for a Wheelchair Power-Assist Device Valerio Cornagliotto(B) , Michele Polito, Laura Gastaldi, and Stefano Pastorelli Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy [email protected]

Abstract. Rear add-ons are assistive devices developed to assist users who have difficulty propelling wheelchairs. Improving the mobility of wheelchair users and allowing them access to more activities is in line with the objective of the sustainable development goals SDG3, and SDG11. Currently, commercial rear add-on devices implement speed-based controls. The speed-based control consists in setting the reference speed that the device must keep constant which makes rear add-on devices suitable for long journeys but, makes them unsuitable for use in narrow spaces. In this paper an hybrid control is presented. The proposed control law takes into account the thrust exerted by the user (torque-based), the forward speed of the wheelchair (speed-based), as well as the surrounding environmental conditions. The total torque delivered by the device is evaluated as the sum of a contribution proportional to the user’s thrust, a delayed contribution as a function of forward speed, and the gravity compensation contribution. The proportional contribution synchronous with respect to the user’s push at low speeds improves manoeuvrability and controllability of the wheelchair, whereas, at higher speeds, the introduction of the delayed thrust distributes the assistance torque over a longer period, reducing the peak of torque provided by the device. A dynamic multibody model of a wheelchair was also developed and implemented in the Simulink environment to test the proposed control algorithm. As a future step the algorithm will be implemented on a rear add-on device and it will be tested experimentally by wheelchair users. Keywords: SDG3 · SDG11 · control · multibody · wheelchair · assistive

1 Introduction Many manual wheelchair users may find it difficult to get around and perform daily activities. Difficulty could be due to reduced physical ability, upper body weakness, pain, injury, or fatigue from prolonged wheelchair pushing. Facilitating wheelchair users’ mobility is in line with the aim of the third sustainable development goal (SDG3) healthy lives and promotion of well-being, as well as promoting human settlements inclusive for persons with reduced mobility (SDG11). Previous studies have shown that power assisted devices (PADs) positively affected propulsion capabilities, reducing biomechanical and physiological strain associated with manual wheelchair self-propulsion [1–3] and improving mobility [4]. Currently, there are different types of propulsion assist © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 162–170, 2023. https://doi.org/10.1007/978-3-031-32439-0_19

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devices for wheelchairs. The main ones can be divided into three categories: pushrim activated power-assisted wheelchairs (PAPAW), which consist of replacing the standard wheels with two motorized and sensorised wheels; the front-end attachments, which consist of a motorized wheel steered by a handlebar that transforms the wheelchair into a tricycle; rear-end attachments, also called rear add-ons, which consist of a drive wheel placed under the seat in the rear part of the wheelchair. The drive wheel provides an amount of torque sufficient to propel the wheelchair autonomously. In previous studies, the user perception and performance of some of the most common PADs have been investigated [5–11]. The main positive aspects of the add-on devices that have emerged from users’ perception are the small size and low weight. However, some gaps in intuitiveness and control reliability have been highlighted. The control laws currently integrated into assistive devices are mainly speed-based control and torque-based control. PAPAW-type devices mainly exploit torque-based controls by acting as torque multipliers. To estimate the action exerted by the user on the wheels, the motorized wheel has built-in sensors. Hence, whenever the user performs a push gesture, the control generates a torque reference for each wheel proportional to the torque exerted on the handrim. By exerting greater action on one of the two wheels, the control generates a different torque reference for the left and the right side, and consequentially the wheelchair steers. To compensate for any kinetic or temporal thrust asymmetries, controls that consider the torque balance ratio have been developed [12]. In addition, some control strategies integrate gravity compensation to assist the user pushing the wheelchair up a ramp [13]. On the contrary, the integrated controls on the rear add-on devices are speed-based. The user sets a speed command and the device sustains the propulsion at the given speed until the user provides input to change the speed or halt the device. In this case, the user can manoeuvre the wheelchair by braking both wheels. In the speed control the gravity is intrinsically compensated because whenever going uphill the device automatically supplies a higher torque to follow the set speed reference. Overall, torque-based control as a thrust multiplier is more suitable in narrow spaces and for small movements while a more uniform thrust, like the one provided in speed controller, is more suitable for long trips. In this work, a hybrid-control for assistance devices is presented. The goal is to obtain a comprehensive control law for a power assist device that takes into account the force exerted by the users on the handrim, the ground inclination, and the travel speed. As a result, the assistance device would be able to provide more suitable assistance according to the user’s needs and to adapt continuously to external conditions.

2 Dynamic Model A standard reference wheelchair (14 kg and 24 inches wheels diameter), a multibody dummy 50th percentile Italian male, and a rear add-on device were conceived as multibody dynamic models and implemented in Simulink Simscape (Fig. 1), as described in the previous work [14]. The wheelchair dynamic behavior is mainly influenced by the forces exerted by the user on the handrims, the additional thrust provided by the rear add-on device, and losses. In particular, losses can be due to rolling friction, air drag, and viscous losses in the wheels

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Fig. 1. Virtual representation of the multibody dynamic model

bearings. The contact between tyres and ground was modelled as a stick-slip continuous contact model (μs : static friction coefficient, μd : dynamic friction coefficient) and a visco-elastic model was adopted for tyre deformation (k tyre : stiffness, ctyre : damping). The rolling friction force Froll was modelled as Eq. (1): Froll = croll FN

(1)

where croll is the rolling coefficient and FN is the normal contact force between the wheel and the ground. The estimation of the rolling friction values can be non-trivial due to many non-linearities; many previous works have investigated the link between rolling friction and tyre type, ground, speed, and other dependencies [15, 16]. The viscous damping torque Tωi has been applied on the two wheels and defined as Eq. (2): Tωi = ηv ωi

(2)

where ηv is a loss coefficient set according to [17] and ωi is the wheel angular speed. The air resistance Fair was defined as in Eq. (3). Fair =

1 2 v CD Aρ 2

(3)

where CD is a form factor and A is the frontal area [16], v is the wheelchair speed, and ρ the air density. The force exerted by the user has been modelled as a sinusoidal function saturated positive, with the push pattern consistent with the results presented in [18]. The main features considered (Table 1) are the cycle time C time , the push phase Pp , the peak tangential force F t peak , and the mean tangential force F t mean The resulting handrim tangential force Ft is shown in Eq. (4).     2π π Ft = max 0; Ftpeak sin − bias (4) t− Ctime 2

Table 1. Push gesture parameters Parameters

Ctime (s)

Pp (%)

F t peak (N)

F t mean (N)

1.15

36

33

21

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The additional thrust provided by the add-on is defined as a function of Ft , speed, and wheelchair inclination. The assistive torque produced by the rear add-on device is transmitted to the wheelchair through a revolute joint coaxial to the wheels. The control law will be described deeper in the specific section. In order to find the optimal parameters that fit the wheelchair behaviour in lab trials, deceleration test have been performed. The experimental test showed a decay of the linear speed of the free wheelchair from 0.9 m/s to 0 m/s in approximately 9 s as shown in Fig. 2a. Hence, a curve fitting procedure was carried out, and all the optimal parameters were set as shown in Table 2. To validate the model an experimental test consisting in 8 pushes from standstill was performed and the forces exerted by the user on the handrims and the wheel speed were acquired by suitable sensors embedded in the wheels. The forces during trial were provided as input to the model. The wheelchair speed acquired experimentally and the one estimated through the simulation were compared. Numerical results well approximate the experimental data (Fig. 2b). Table 2. Model optimal parameters k tyre (N/m)

ctyre (Ns/m)

ηv (Nms/rad)

μs

μd

Front croll

Rear croll

3e5

1e4

0.05

0.85

0.65

0.012

0.007

Fig. 2. Experimental and simulated angular velocity decay (a), model validation output (b)

3 Control Law The control law of the add-on device is designed as described in Eq. (5)      a1 δ a1 δ T addon (t, v, α) = T H (t) a1 − + T H (t − δ) 2δmax 2δmax ·(1 − b1 α) + Mtot g sin(α)r δ = max(0; min(d1 v − d2 ; δmax ))

(5) (6)

where T H (t) = Ft (t)R is the human torque provided at the handrims, δ is a delay factor described in Eq. (6), r is the radius of the add-on wheel, R is the radius of the wheelchair

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Parameters

a1

b1 (rad−1 )

d 1 (s2 m−1 )

d 2 (s)

δmax (s)

r (m)

R (m)

M tot (kg)

0.75

6.02

0.67

0.17

0.25

0.11

0.26

89,2

wheels, M tot is the total mass, v is the linear speed of the wheelchair, and a1 , b1 , d 1 , d 2 , and δmax are coefficients. The values of all parameters are defined in Table 3. The total torque T addon consists of three main contributions: proportional (P), delayed (), and gravity compensation (G). P makes the add-on device responsive to fast changes in input torque and is the only contribution at low speed (v < 0.25 m/s).  makes the speed ripple smoother as the assistance torque lasts longer than the human torque. The introduction of  contribution makes the assistance more suitable for higher speed in steady state conditions. G is introduced to compensate gravity when the wheelchair is on a ramp. It prevents the rolling back of the wheelchair and reduces the effort of the user going on graded roads. In order to have a more continuous torque, the value of the gains of P and  are proportional to the delay. In particular, the P gain is decreasing with the delay whereas the  gain is increasing. An overall gain of the sum of P and  contributions is applied in order to decrease the maximum torque on the graded surface. The overall gain is equal to 0.5 when the wheelchair inclination reaches 4.8° (which is the maximum inclination angle of ramps according to ISO 21542:2021). That adjustment decreases the speed upward giving the user the perception of going uphill.

4 Results and Discussions The first simulation was done with no assistance by introducing the forces exerted by the user to propel the wheelchair on a levelled surface as described in Sect. 2. A steady state speed of 2.1 m/s is obtained as shown in Fig. 3a.

Fig. 3. Steady-state speed and provided torques without assistance (a) and with assistance (b)

Then, the assistance thrust of the device has been introduced. To evaluate the value of the a1 coefficient, a simulation with only the P contribution was performed. The value of a1 was estimated to obtain the same steady-state speed when 50% of the torque is exerted by the user as shown in Fig. 3b. Then, the  contribution was introduced (Fig. 4).

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The δmax was set equal to 0.25 s, which corresponds to about a quarter of the period of the push phase. d 1 and d 2 were chosen in order to have the delay starting above 0.25 m/s and the maximum delay at 0.60 m/s. To limit the sum of P and  when the two contributions overlap, the gain proportional to T H . Was adjusted proportionally to the delay. In the maximum-delay condition, the P gain is halved with respect to the no-delay condition. The  gain is proportional to the delay and its maximum value was set to be equal to P evaluated in the maximum-delay condition.

Fig. 4. Transient (a); steady-state (b)

Analysing the speed trend and the torque delivered by the device it can be inferred how it is possible to obtain a smoother ripple at the same average speed (Fig. 5a) by delivering about half of the peak torque (Fig. 5b). Moreover, even if the maximum transmissible torque increases as the assistive torque increases [14], reducing the peak torque can be an advantage in low grip conditions to avoid wheel slippage.

Fig. 5. Speed ripple comparison (left); torque comparison (right)

Eventually, the G gravity compensation was introduced. The amount of assistive torque to compensate for the force of gravity has been estimated analytically by imposing the wheelchair to be still on a ramp without any additional torque exerted by the user. Hence, a simulation of the wheelchair approaching an 8% graded surface was carried out. The total assistive torque is equal to the sum of the three contributions, in particular, the G contribution is highlighted in Fig. 6.

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Fig. 6. Complete additional torque control law

5 Conclusions The development of a comprehensive control algorithm that adapts to user actions as well as environmental conditions is essential to make rear add-on devices more intuitive and all-round. In this paper, a control law that takes into account the action that the user exerts on the handrims, the forward speed, and the pitch angle of the wheelchair is presented. The total torque delivered by the device is calculated as the sum of three contributions: proportional to the user’s thrust, delayed as a function of forward speed, and gravity compensation. At low speeds the torque is purely proportional and synchronous with the user’s thrust, improving the controllability and manoeuvrability in narrow spaces. At higher speeds, the assistance torque is distributed over a longer period than the user’s thrust period, guaranteeing a more gradual and more suitable assistance for longer distances. A dynamic multibody model of a wheelchair was developed and implemented in the Simulink environment to design the control algorithm. At the moment the algorithm is being implemented on a rear add-on prototype (patent pending) designed by authors and experimental tests are being carried out with actual users. Hence, it will be possible to tune optimised control parameters on the basis of the subjects’ perceptions. Acknowledgments. This research was partially conducted within the project “Advanced Light Body Assistants - Sistema avanzato leggero per l’assistenza a persone diversamente abili”- P.O.R. FESR 2014/2020 - Azione I.lb.2.2 Bando Pi.Te.F.

References 1. Algood, S.D., Cooper, R.A., Fitzgerald, S.G., Cooper, R., Boninger, M.L.: Effect of a pushrimactivated power-assist wheelchair on the functional capabilities of persons with tetraplegia. Arch. Phys. Med. Rehabil. 86(3), 380–386 (2005). https://doi.org/10.1016/j.apmr.2004. 05.017 2. Cooper, R.A., et al.: Evaluation of a pushrim-activated, power-assisted wheelchair. Arch. Phys. Med. Rehabil. 82(5), 702–708 (2001). https://doi.org/10.1053/apmr.2001.20836 3. Algood, S.D., Cooper, R.A., Fitzgerald, S.G., Cooper, R., Boninger, M.L.: Impact of a pushrim-activated power-assisted wheelchair on the metabolic demands, stroke frequency, and range of motion among subjects with tetraplegia. Arch. Phys. Med. Rehabil. 85(11), 1865–1871 (2004). https://doi.org/10.1016/j.apmr.2004.04.043

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4. Levy, C.E., Buman, M.P., Chow, J.W., Tillman, M.D., Fournier, K.A., Giacobbi, P., Jr.: Use of power assist-wheels results in increased distance traveled compared to conventional manual wheeling. Phys. Med. Rehabil. Serv. 89(8), 625–634 (2010). https://doi.org/10.1097/PHM. 0b013e3181e72286 5. Khalili, M., Eugenio, A., Wood, A., Van der Loos, M., Mortenson, W.B., Borisoff, J.: Perceptions of power-assist devices: interviews with manual wheelchair users. Disabil. Rehabil. Assist. Technol. 1–11 (2021). https://doi.org/10.1080/17483107.2021.1906963 6. Flockhart, E.W., Miller, W.C., Campbell, J.A., Mattie, J.L., Borisoff, J.F.: Evaluation of two power assist systems for manual wheelchairs for usability, performance and mobility: a pilot study. Disabil. Rehabil. Assist. Technol. 1–13 (2021). https://doi.org/10.1080/17483107. 2021.2001063 7. Khalili, M., Kryt, G., Mortenson, W.B., Van der Loos, H.F.M., Borisoff, J.: Comparison of manual wheelchair and pushrim-activated power-assisted wheelchair propulsion characteristics during common over-ground maneuvers. Sensors 21(21), 7008 (2021). https://doi.org/ 10.3390/S21217008 8. Sawatzky, B., Mortenson, W.B., Wong, S.: Learning to use a rear-mounted power assist for manual wheelchairs. Disabil. Rehabil. Assist. Technol. 13(8), 772–776 (2017). https://doi. org/10.1080/17483107.2017.1375562 9. Kloosterman, M.G., Buurke, J.H., Schaake, L., Van der Woude, L.H., Rietman, J.S.: Exploration of shoulder load during hand-rim wheelchair start-up with and without power-assisted propulsion in experienced wheelchair users. Clin. Biomech. 34, 1–6 (2016). https://doi.org/ 10.1016/j.clinbiomech.2016.02.016 10. Cooper, R.A., et al.: Performance assessment of a pushrim-activated power-assisted wheelchair control system. IEEE Trans. Control Syst. Technol. 10(1), 121–126 (2002). https:// doi.org/10.1109/87.974345 11. Best, K.L., Kirby, R.L., Smith, C., Macleod, D.A.: Comparison between performance with a pushrim-activated power-assisted wheelchair and a manual wheelchair on the Wheelchair Skills Test. Disabil. Rehabil. 28(4), 213–220 (2009). https://doi.org/10.1080/096382805001 58448 12. Heo, Y., Hong, E.P., Chang, Y.H., Jeong, B., Mun, M.S.: Experimental comparison of torque balance controllers for power-assisted wheelchair driving. Measurement 120, 175–181 (2018). https://doi.org/10.1016/j.measurement.2018.02.024 13. Lee, K.M., Lee, C.H., Hwang, S., Choi, J., Bang, Y.B.: Power-assisted wheelchair with gravity and friction compensation. IEEE Trans. Ind. Electron. 63(4), 2203–2211 (2016). https://doi. org/10.1109/TIE.2016.2514357 14. Cornagliotto, V., Perino, F., Gastaldi, L., Pastorelli, S.: Evaluation on implementing an active braking system in wheelchair rear-mounted power-assisted device. In: Müller, A., Brandstötter, M. (eds.) Advances in Service and Industrial Robotics (RAAD 2022). Mechanisms and Machine Science, vol. 120, pp. 351–358. Springer, Cham (2022). https://doi.org/10.1007/ 978-3-031-04870-8_41 15. Sauret, C., et al.: Assessment of field rolling resistance of manual wheelchairs (2014). To cite this version : HAL Id : hal-01086723 Science Arts & Métiers (SAM) 16. Hoffman, M.D., Millet, G.Y., Hoch, A.Z., Candau, R.B.: Assessment of wheelchair drag resistance using a coasting deceleration technique. Am. J. Phys. Med. Rehabil. 82(11), 880– 889 (2003). https://doi.org/10.1097/01.PHM.0000091980.91666.58

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17. Nguyen, V.T., Bentaleb, T., Sentouh, C., Pudlo, P., Popieul, J.C.: On a complete dynamical model of manual wheelchair for virtual reality simulation platform. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 2417–2422. IEEE (2019). https://doi.org/10.1109/SMC.2019.8913960 18. Soltau, S.L., Slowik, J.S., Requejo, P.S., Mulroy, S.J., Neptune, R.R.: An investigation of bilateral symmetry during manual wheelchair propulsion. Front. Bioeng. Biotechnol. 3, 86 (2015). https://doi.org/10.3389/fbioe.2015.00086

Analytical Synthesis of the Seven-Bar Linkage 7-RR(RRRR)RR Used for Medical Disinfection Robot Elida-Gabriela Tulcan(B)

, Alexandru Oarcea , and Erwin-Christian Lovasz

Politehnica University of Timis, oara, 300006 Timis, oara, Romania {elida.tulcan,alexandru.oarcea}@student.upt.ro, [email protected]

Abstract. The paper presents the type and analytical synthesis of seven-bar linkage. The analytical synthesis equations lead to the computation of the elements lengths of a symmetrical seven-bar linkage with only revolute joints. This mechanism is intended to be further used in the development of a medical disinfection robot, mostly because its structure allows different configurations and a large height variation between its minimum and maximum position, which will solve the problem of disinfecting the hard-to-reach areas from the medical environment. Keywords: SDG3 · seven-bar linkage · folding mechanism · disinfection robot

1 Introduction The seven bar-linkages have been briefly studied, even if they have a wide range of applications in multiple domains, from industrial applications to medical applications. For example, Liu et al. studied in [1] a kinematic design of a seven-bar linkage with optimized centrodes used for pure-rolling cutting. In [2] Daivagna et al. presented an analytical method to synthesize a seven-bar slider mechanism with variable topology for motion between two dead-center positions. Gadad et al. performed in [3, 4] Dyad and Triad synthesis of a planar seven-link mechanism with variable topology. A geometric and kinematic analysis of a seven-bar three-fixed-pivoted-compound-joint mechanism was performed by Wei and Dai in [5]. Other syntheses of the seven-bar slider mechanism for motion generation using variable topology were presented by Tadalagi and Balli in [6, 7]. An interesting link optimization and kinetostatic analysis was performed on a hybrid ˇ c et al. presented in [9] a dynamic seven-bar press mechanism by Kütük et al. in [8]. Cavi´ optimization of the seven-bar linkage Zero-Max variator mechanism, consisting of a basic mechanism - Watt II mechanism - and the control lever by which adjusting of the transmission ratio of the variator is done. The considered seven-bar linkage is intended to be further used in the development of a medical disinfection robot. A robot with a similar structure was already designed in [10], achieving a large variation of the mechanism’s height, with an increase of more than three times from the minimum position to the maximum position. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 171–180, 2023. https://doi.org/10.1007/978-3-031-32439-0_20

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2 Type Synthesis of the Seven-Bar Linkage The determination of the mechanism structure, otherwise known as the type synthesis, from the kinematic point of view, can be summarized in the following points [11]: • • • • •

imposition of the mechanism degree of freedom M and the number of elements n; computation of the number of kinematic joints and specification of the joint types; computation of the number of the kinematic loops and the rank of the elements; development of all distinct types of kinematic chains; development of all the derived mechanisms from each kinematic chain, based on the Reuleaux method; • limitation of the mechanism structures that satisfy the imposed additional condition. According to Luck and Modler [12], the condition to have a constrain motion of a mechanism structure is given by the following relationship: 2 · (e1 +

e2 )−3·n+3+M =0 2

(1)

where: e1 – number of kinematic pairs with DOF = 1, e2 – number of kinematic pairs with DOF = 2, n – number of elements, M – mobility degree of the mechanism. By considering all the elements of the kinematic chain, the input conditions for the kinematic chains should be to contain only revolute kinematic pairs with DOF = 1 (e2 = 0), to have 7 elements and the mobility degree of the mechanisms M = 2. This being said, the constraint motion Eq. (1) with the previous input conditions is: e1 =

3·n−5 ∈N 2

(2)

The first two solutions of the Eq. (2) are: n = 2 → e1 = 2 ∈ N n = 5 → e1 = 5 ∈ N

(3)

which are not convenient, and the third convenient solution which is: n = 7 → e1 = 8 ∈ N The number of elements satisfy the following equations system:   n = n2 + n3 7 = n2 + n3 2 2 · i=1 ei = 2 · n2 + 3 · n3 16 = 2 · n2 + 3 · n3

(4)

(5)

where n2 and n3 are the number of binary and ternary elements (other higher rank elements were neglected because the results were not useful). The obtained number of binary and ternary elements is: n2 = 5 and n3 = 2

(6)

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Applying the Reuleaux similar method for the kinematic chain related to the sevenbar mechanism using only revolute joints, leads to obtaining the mechanism structures presented in Fig. 1. The Reuleaux similar method consists in successive considering an element as frame, two elements in frame jointed as drive elements and one element as driven element or one joint as characteristic point. The proposed notation of this type of linkage chain is 7-RR(RRRRR)R, where R – revolute joint, while in the brackets is indicated the parallel connected kinematic chain. Additionally, the developed linkages also contain in brackets the considered frame element (ex. (a)) and underlined the drive joints, in this case two of them (ex. RR(RRRR)RR(f)). The similar structures were eliminated in the development.

Fig. 1. Development by Reuleaux method of the seven-bar linkage

3 Positional Analysis of the Symmetrical seven-bar linkage 7-RR(RRRR)RR(f) The presented seven-bar linkage 7-RR(RRRR)RR(f) was chosen from the developed type synthesis as symmetrical linkage type to the y axes, as can be observed in Fig. 2. Also, the lengths of the drive elements l2 and l5 , as well as the lengths of the driven elements l3 and l4 , respectively l6 and l7 were chosen to be equal due to functional requirements (l2 = l5 , l3 = l4 , l6 = l7 ). The coordinates of the characteristic point M can be computed by using four vector loops, first OA0 BC and CBM, and second OE0 DC and CDM, as it follows: xM = − l21 + l2 · cosϕ2 + l3 · cosϕ3 + l6 · cosϕ6 yM = l2 · sinϕ2 + l3 · sinϕ3 + l6 · sinϕ6

(7)

xM = l21 + l5 · cosϕ5 + l4 · cosϕ4 + l7 · cosϕ7 yM = l5 · sinϕ5 + l4 · sinϕ4 + l6 · sinϕ7

(8)

By imposing the driven positional angles ϕ2 and ϕ5 , then successively separating the terms which contain ϕ6 in Eq. (7), and the terms which contain ϕ7 in Eq. (8), squaring each member and adding them accordingly, results the following transmission equations: F3 (xM , yM ) = A3 (xM , yM ) · cosϕ3 + B3 (xM , yM ) · sinϕ3 + C3 (xM , yM ) = 0

(9)

F4 (xM , yM ) = A4 (xM , yM ) · cosϕ4 + B4 (xM , yM ) · sinϕ4 + C4 (xM , yM ) = 0

(10)

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where the coefficients are: A3 (xM , yM ) = l3 · (2 · l 2 · cosϕ2 − 2 · xM − l1 ) B3 (xM , yM ) = 2 · l 3 · (l2 · sinϕ2 − yM ) C3 (xM , yM ) = xM 2 + yM 2 +l 2 2 + l3 2 − l6 2 + +l1 · (xM − l2 · cosϕ2 ) − 2 · l2 (xM · cosϕ2 + yM · sinϕ2 ) +

(11) l1 2 4

and: A4 (xM , yM ) = l4 · (2 · l 5 · cosϕ5 − 2 · xM + l1 ) B4 (xM , yM ) = 2 · l 4 · (l5 · sinϕ5 − yM ) C4 (xM , yM ) = xM 2 + yM 2 +l 4 2 + l5 2 − l7 2 + +l1 · (l5 · cosϕ5 − xM ) − 2 · l5 (xM · cosϕ5 + yM · sinϕ5 ) +

(12) 2

l1 4

Repeating the previous procedure, but this time separating the terms which contain ϕ3 and ϕ4 , we obtain the next transmission equations: F6 (xM , yM ) = A6 (xM , yM ) · cosϕ6 + B6 (xM , yM ) · sinϕ6 + C6 (xM , yM ) = 0

(13)

F7 (xM , yM ) = A7 (xM , yM ) · cosϕ7 + B7 (xM , yM ) · sinϕ7 + C7 (xM , yM ) = 0

(14)

where the coefficients are: A6 (xM , yM ) = l6 · (2 · l 2 · cosϕ2 − 2 · xM − l1 ) B6 (xM , yM ) = 2 · l 6 · (l2 · sinϕ2 − yM ) C6 (xM , yM ) = xM 2 + yM 2 +l 2 2 − l3 2 + l6 2 + +l1 · (xM − l2 · cosϕ2 ) − 2 · l2 (xM · cosϕ2 + yM · sinϕ2 ) + and:

Fig. 2. Kinematic scheme of the symmetrical seven-bar linkage

(15) l1 2 4

Analytical Synthesis of the Seven-Bar Linkage 7-RR(RRRR)RR

A7 (xM , yM ) = l7 · (2 · l 5 · cosϕ5 − 2 · xM + l1 ) B7 (xM , yM ) = 2 · l 7 · (l5 · sinϕ5 − yM ) C7 (xM , yM ) = xM 2 + yM 2 −l 4 2 + l5 2 + l7 2 + +l1 · (l5 · cosϕ5 − xM ) − 2 · l5 (xM · cosϕ5 + yM · sinϕ5 ) +

175

(16) 2

l1 4

The positional angles of the seven-bar linkage links are calculated using the following equation:  Bi (xM , yM ) ∓ Ai (xM , yM )2 + Bi (xM , yM )2 − Ci (xM , yM )2 ϕi (xM , yM ) = 2 · arctan Ai (xM , yM )2 − Ci (xM , yM )2 (17) where i ∈ {3, 4, 6, 7}.

4 Analytical Synthesis of the Symmetrical Seven-Bar Linkage The analytical synthesis of the considered seven-bar linkage aims to compute the lengths of the elements in order to avoid the singularities on the movement of the characteristic point M on y axis. In this sense, it is necessary to avoid the collinearity of the mobile neighboring links. Because of the symmetrical design of the seven-bar linkage, the conditions to avoid the singularities for the first two loops OA0 BC and CBM, and the second two loops OE0 DC and CDM are identical. This being said, the maximum distance between the drive joint A0 and the characteristic point M should be lower than the sum of the links lengths, respectively the minimum distance between the drive joint A0 and the characteristic point M should be bigger than the difference of the links lengths.  l1 2 l6 + l2 ≥ (xM2 + ) + yM2 2 (18) 2  l1 2 |l6 − l2 | ≤ (xM1 + ) + yM1 2 (19) 2 The next dimensional conditions involve the avoidance of collinearity between the driven links l3 and l4 (l2 = l5 and l3 = l4 ): l 1 + 2 · l 2 ≤ 2 · l3

(20)

as well as the avoidance of the collinearity of the elements l3 and l6 : l3 ≤ l 6

(21)

The inequalities system given by the relationships (18)–(21) can be substituted with an equations system by imposing a multiplier coefficient k > 1. This coefficient

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ensures the avoidance of singularities in the dexterous workspace along with avoiding the collinearity between the mobile neighboring elements. The equations system is given by the next relationships:  l1 2 (22) l6 + l2 = k · (xM2 + ) + yM2 2 2  1 l1 2 (23) l6 − l2 = · (xM1 + ) + yM1 2 k 2 k · l 1 = 2 · (l 3 − l2 )

(24)

k · l3 = l6

(25)

The solution of the equations system is the links lengths of the seven-bar linkage. l1 = ⎡



2 · (l 3 − l2 ) k

(26) 

⎤

2

2

1 ⎣ 1 l1 l1 · − · (xM1 + ) + yM1 2 + k · (xM2 + ) + yM2 2 ⎦ 2 k 2 2  ⎤ ⎡  2 1 ⎣1 l1 2 l 1 l3 = · · (xM1 + ) + yM1 2 + k · (xM2 + ) + yM2 2 ⎦ 2·k k 2 2  ⎡  ⎤ 2 1 ⎣1 l1 2 l 1 l6 = · · (xM1 + ) + yM1 2 + k · (xM2 + ) + yM2 2 ⎦ 2 k 2 2 l2 =

(27)

(28)

(29)

By substituting l2 and l3 from Eqs. (27)–(28) into Eq. (26), we obtain an equation with only one unknown, from which we compute l1 : l 1 4 · a − l1 2 · b + c = 0

(30)

where the following notations were used:



  2 1 · (1+k)4 + 1 − k 4 a = k 4 + 16 + k2 · 1 − k2 + − 21 · (1+k) 8 2



 2 (1+k)2 ·(1−k)2 − 1 − k2 2 k k ⎡ 2 ⎤ 





  (1+k)2 ·(1−k)2 −4· 1−k 2 (1+k)4 (1−k)4 2 2 2 2 2 2 2 ⎣ ⎦ b = 2 · yM1 · (1 + k) − + yM2 · k · (1 − k) − − yM1 + yM2 · 4 4·k 8 4·k 4 1 · 4·k 4

 2 2·yM 2 ·yM 2 4 1 2 · (1 + k)2 · (1 − k)2 − 2 · 1 − k 2 c = (1+k) · yM1 4 + (1 − k)4 · yM2 4 + k8 k4

(31) The links lengths l5 , l4 and l7 are symmetrical and equal with the links lengths l2 , l3 and l6 : l 5 = l2 , l4 = l3 , l6 = l7

(32)

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177

5 Numerical Example The numerical example shows the results of the analytical synthesis of the seven-bar linkage. The coordinates of the characteristic point M as M1 in the minimum position and M2 in the maximum position are given in Table 1. The links of the elements obtained using equations (26)–(30) for a multiplier coefficient k = 1.2 are presented in Table 2. Table 1. Coordinates of the characteristic point in minimum and maximum position Point

xM [mm]

yM [mm]

M1

0

130

M2

0

330

Table 2. Computed links lengths Link

Length [mm]

l1

128

l2

141

l3

218

l4

218

l5

141

l6

262

l7

262

Figure 3 shows the seven-bar linkage with the obtained links in the two extreme positions resulted from the analytical synthesis. As it can be observed, all positions

Fig. 3. Minimum and maximum position of the symmetrical seven-bar linkage

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inside the workspace can be reached without having collinearity between the neighboring elements. Figure 4 presents the computed singularities of type I for the symmetrical seven-bar linkage. As it can be observed, the singularities of type I are avoided, because all the values of det(Jq ) are different from zero.

Fig. 4. Computed singularities of type I for the symmetrical seven-bar linkage

Figure 5 presents the computed singularities of type II for the symmetrical seven-bar linkage. As it can be once again observed, the singularities of type II are also avoided, since all the values of det(Jx ) are different from zero.

Fig. 5. Computed singularities of type II for the symmetrical seven-bar linkage

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179

The presented numerical example shows that the conditions, as well as the results, of the analytical synthesis of the symmetrical seven-bar linkage are fulfilled in order avoid having singularities inside the total workspace.

6 Conclusions The paper presented the type synthesis, positional analysis, analytical synthesis and numerical example of the seven-bar linkage. The numerical example chapter presented the minimum and maximum position of the symmetrical seven-bar linkage, as well as the computed singularities of type I and type II, concluding that the conditions of the analytical synthesis were fulfilled in order to avoid having singularities in the total workspace. This structure is intended to further be used to design a medical disinfection robot. The main reason why we considered this mechanism is because it allows a large height variation between the minimum and the maximum position of its configuration, thus being a good solution also for the disinfection process of the hard-to-reach areas or areas where the space is limited from the medical environment and other facilities. As Diab-El Schahawi et al. in [15] said, “disinfection robots are a promising tool for surface decontamination in the hospital already today, but with even greater potential tomorrow”. Still there is room for design improvement, since one-size does not fit all, and also more studies should be performed in order to establish the optimal wavelength and exposure time.

References 1. Liu, B., Ma, Y., Wang, D., Bai, S., Li, Y., Li, K.: Kinematic design of a seven-bar linkage with optimized centrodes for pure-rolling cutting. Math. Probl. Eng. 2017, 1–11 (2017) 2. Daivagna, U.M., Balli, S.S.: Synthesis of a seven-bar slider mechanism with variable topology for motion between two dead-center positions. In: Proceedings of the World Congress on Engineering 2010, pp. 1454–1459, UK (2010) 3. Gadad, G.M., Ramakrishan, H.V., Srinath, M.S., Balli, S.S.: Dyad synthesis of planar sevenlink variable topology mechanism for motion between two dead-centre positions. J. Mech. Civil Eng. 3(3), 21–29 (2012) 4. Gadad, G.M., Balli, S.S., Daivagna, U.M.: Triad and dyad synthesis of planar seven-link mechanisms with variable topology. In: Proceedings of the 12th National Conference on Machines and Mechanisms, pp. 67–73, India (2005) 5. Wei, G., Dai, J.S.: Geometric and kinematic analysis of a seven-bar three-fixed-pivoted compound-joint mechanism. Mech. Mach. Theory 45(2), 170–184 (2010) 6. Tadalagi, P., Balli, S.: Two FSP synthesis of seven bar slider mechanism using variable topology. J. Scholast. Eng. Sci. Manag. 1(4), 38–54 (2021) 7. Tadalagi, P., Balli, S.: Limiting positions synthesis of seven bar slider automated fiber placement mechanism for motion generation using variable topology. Int. J. Mech. Prod. Eng. Res. Dev. 10(3), 13297–13308 (2020) 8. Kütük, M.E., Artan, M., Dülger, L.C.: Hybrid seven-bar press mechanism: link optimization and kinetostatic analysis. Tehniˇcki glasnik 12(3), 181–187 (2018)

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ˇ c, M., Penˇci´c, M., Rackov, M., Zlokolica, M.: Dynamic optimization of the pulse continu9. Cavi´ ously variable transmission. In: 5th International Conference on Power Transmission – BAPT 2016, pp. 123–131, Macedonia (2016) 10. Tulcan, E.-G., Sticlaru, C., Lovasz, E.-C., Gruescu, C.M., Sandu, M.O.: Design of a folding mechanism for a mobile robot used for medical disinfection. Facta Universitatis, Series: Mechanical Engineering (in press) 11. Freudenstein, F., Dobrjanskyj, L.: On a theory for the type synthesis of mechanisms. In: Görtler, H. (eds.) Proceedings of the 11th International Congress of Applied Mechanics, Applied Mechanis, pp. 420–428, Springer, Heidelberg (1966). https://doi.org/10.1007/9783-662-29364-5_57 12. Luck, K., Modler, K.-H.: Getriebetechnik. Analyse – Synthese - Optimierung, AkademieVerlag, Berlin (1990) 13. Florescu, F., Popescu, I.-E., Moldovan, C.E., Lovasz, E.-C.: Type synthesis of the mechanisms with linear actuation useful for orientation modules. In: The Joint International Conference of the 13th IFToMM International Symposium on Science of Mechanisms and Machines (SYROM) and the XXV International Conference on Robotics (ROBOTICS), Romania (2022) 14. Demjen, T., Lovasz, E.-C., Ceccarelli, M., Sticlaru, C., Luput, i, A.-M.-F.: Analytical Synthesis of Five-Bar Linkage used for 3D Printer Structure. In: Niola, V., Gasparetto, A., Quaglia, G., Carbone, G. (eds.) The International Conference of IFToMM ITALY, Mechanisms and Machine Science, vol. 112, pp. 105–113, Springer, Cham (2022). https://doi.org/10.1007/ 978-3-031-10776-4_13 15. Diab-El Schahawi, M., et al.: Ultraviolet disinfection robots to improve hospital cleaning: real promise or just a gimmick? Antimicrob. Resist. Infect. Control 3(33), 1–3 (2021)

Design of a Novel Medical Rolling Walker for Use in Hospital Environment Ángela Alonso Ortuzar(B) and Saioa Herrero Villalibre Department of Mechanical Engineering, Faculty of Engineering in Bilbao (UPV/EHU), Plaza Ingeniero Torres Quevedo 1, 48013 Bilbao, Spain [email protected], [email protected]

Abstract. This work presents a novel medical rolling walker (or rollator) intended for use in hospital environment. It is designed to fit the largest number of patients without forcing the hospitals to purchase different size rollators, for both outdoor and indoor usage. It is adjustable in height by discrete positions, it includes a width adjusting system, also adjustable by discrete positions, lockable/unlockable swivel wheels and braking system with both pressure brake system and lever brake system. The principal structure is manufactured in Aluminum 6061 T6. Finally, to verify the resistance of the rolling walker structure, a static strength analysis following the standard UNE-EN ISO 11199-2-2021 has been done by using the Finite Element Method. It focuses mainly on SDG3, SDG10: the rollator will offer support and stability when walking to increase mobility, safety and prevent falls, but also offers an improvement in self-esteem as the person recovers autonomy and encourages the person to go for a walk. Keywords: SDG3 · SDG4 · SDG9 · SDG10 · SDG 12 · Rolling Walker · Rollator · Width Adjusting System · Swivel wheels

1 Introduction Today, one of the most significant social changes taking place in developed countries is demographic ageing [1]. Spain is one of the most ageing countries in the European Union. According to a study carried out by the National Statistics Institute (INE), the population pyramid will be completely inverted over the next few years, with the highest population density concentrated in the 85-year-olds [2]. One of the problems suffered by older people is lack of mobility or mobility problems. In Spain, in the year 2014, more than 40% of people aged between 75 and 80 years old reported experiencing movement difficulties [3]. Therefore, this work is aimed at that large part of society that suffers from these mobility problems and could benefit from an improvement in the quality and customization of orthopedic products. The aim of this work is to design a rollator as versatile as possible in order to fit the largest number of patients and improve the features that the commercialized models currently offer. Nowadays, almost all rollators on the market are adjustable in height, but most of them lack the adjustment in width [4–7], which makes the product not versatile © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 181–188, 2023. https://doi.org/10.1007/978-3-031-32439-0_21

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for patients of different sizes. Because of that, the commercialized four wheeled models vary in width from 48 to 79 cm for each user to choose the most adequate one according to their dimensions. As a result of this situation, hospitals have to purchase different size rollators in order to fit the patients properly or give the patient a rollator that may not have the most comfortable fitting. The novel design also includes four lockable/unlockable swivel wheels, not included on many commercial models. In addition, outdoor and indoor rollators are often presented as two solutions for different applications due to the lack of flexibility to function in both situations [8]. The users are often required to purchase a rollator for interior use due to the lack of adapted households or elevators. Although the rollator is designed towards hospital usage, it can also be used outside of the hospital environment such as nursing homes and households. The term user in this document refers to hospital patients or people in their households or nursing home, focusing mainly on hospital users. This design meets the following Sustainable Development Goals (SDG), it is mainly focused on the ones bolded: – SDG3, SDG10: the rollator will offer support and stability when walking to increase mobility, safety and prevent falls, but also offers an improvement in self-esteem as the person recovers autonomy and encourages the person to go for a walk [9] and therefore their mental and social health is also improved. – SDG4: this is an educational end-of-degree project. – SDG9: this rolling walker contributes to innovation since a novel medical rolling walker is proposed. – SDG12: this work contributes to sustainable production as most of the parts are designed to be interchangeable in case of deterioration. It also contributes to responsible consumption as hospitals will need to purchase fewer rolling walkers.

2 Description of the Design In order to carry out the design, Solid Edge 2022 CAD software has been used and the standard UNE-EN ISO 11199-2-2021 has been followed. The design is divided into subassemblies as shown in Fig. 1. The principal structure, manufactured in Aluminum 6061 T6, consists of the handles (4), upper (5) and lower tubes (6) joined by the connecting acrylonitrile butadiene styrene (ABS) plastic parts (7), forming one body. The two bodies are then joined by the width adjusting system (3) shown in Fig. 3. The handles (4) are cylindrical parts with an outside diameter of 21 mm and a thickness of 3.5 mm with holes 25 mm apart (determined by standard UNE-EN ISO 11199–2-2021) to adjust height by discrete positions with a shaft. Then is inserted into the upper tubes (5) with a diameter of 26 mm and a thickness of 2.5 mm. The lower tubes (6) have an outside diameter of 25 mm and a thickness of 1.5 mm. The tubes are connected by the ABS plastic union parts (7) that have a 6 mm stiffening rib, and it enables the walker to be folded. The subassemblies (1) and (2) shown in Fig. 1 refer to the whole system of parts forming the wheel assembly, not just referring to the actual wheel. The front wheel has a diameter of 180 mm, as the standard UNE-EN ISO 11199-2-2021 indicates for outdoor rollators, and the rear wheel has a diameter of 80 mm.

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Fig. 1. Adjustable rolling walker

3 Rear Wheel Both the rear wheel (2), shown in Fig. 2, and front wheel (1) are swivel wheels that can be locked into the walking position and unlocked to rotate freely. This locking/unlocking system is meant to be manipulated by the hospital staff, it is meant to be easy and fast to manipulate for the purpose of the staff arranging the rollator wheel configuration most suitable for the patient in a short amount of time. The wheel blocking system consists of a shaft (15) passing through the main parts (10) and (11), so it holds the system blocked. To free the system, the shaft must be lifted 3.5 mm and rotated 180°. When it lifts, it compresses a spring (16). To achieve this, the main part (11) has a hollowed out at different heights (3.5 mm height difference) for the shaft (15) to be fixed in place and avoid it from moving unintentionally. The spring (16) is designed to be activated when a vertical 10 N force is applied on the plastic handle and to compress at least 3.5 mm. The rotation of the wheel remains unlocked until the shaft (15) is rotated again and placed back into the locked position with help of the spring (16). This system is also used for the front wheel (1). The pressure brake system is activated when the patient applies a minimum force of 60 N on each handle (4) [10]. This makes the springs (8) compress and the guided bush (9) slides in the main part (10), making the structure descend 3.5 mm vertically, also guided by guiding shafts, until the rubber tip (12) touches the floor, thus braking by friction against the ground. The rubber tip is a commercial component. The springs (8) are designed so they can compress 3.5 mm. A separation is left between the wheel (13) and the lever (14) of the lever brake system, for the lever (14) not to interfere with the pressure brake system when this is activated. The parts of the lever brake system are commercial components.

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Fig. 2. Exploded view of rear wheel

4 Adjustable Width System The adjustable width system (Fig. 3) is intended to be easy and fast to manipulate by the hospital staff, so they can fit the rollator to the size of the user in a short amount of time. The minimum width is 48 cm and the maximum 76 cm. The adjustable width system consists of a carriage (17), a guideway (18) and a shaft (15) inserted into the holes on the guideway (18). These holes are located 25 mm apart from each other to keep the desired width fixed. The locking/unlocking system is the same one presented previously for both rear and front wheel. Both the carriage and the guideway have stops beneath them so when the maximum width is reached, the stops contact each other avoiding the carriage to leave the guideway.

Fig. 3. Exploded view of width adjusting system

Design of a Novel Medical Rolling Walker

185

5 Static Strength Analysis In order to validate the design, the static strength of the system is analyzed by applying the Finite Element Method. The software used is Ansys 2021 R2. The rollator is tested on the most adverse position, at the highest and widest configuration. Taking into account that the specified maximum user mass is 100 kg, the following tests are performed: – Analysis I: 600 N applied at 30 mm on the end of each handle (4) [10] (Fig. 4a). – Analysis II: 490 N distributed on the gripping surface of each handle (4) (Fig. 4b).

Fig. 4. (a) 600 N force applied on each handle; (b) 490 N force applied on each handle.

6 Analysis I This first analysis has been done with 600 N applied at 30 mm of the end of each handle. This is the most adverse analysis, and although this will not be a real situation, the standard UNE-EN ISO 11199-2-2021 requires this test done with 1200 N (for a user mass of 100 kg) at 30 mm of the end of the handle. Therefore, a force of 600 N will be applied to each handle (4). The design will be valid if no parts break. This analysis is intended to be done on a real prototype. As explained before, the materials used for the analysis are Aluminum 6061 T6 and ABS plastic. In the model, plastic parts are shown in yellow and aluminum parts in green. The simple parts such as the upper (5) and lower (6) tubes are meshed with multi zone method using quadratic hexahedral elements. The parts that have a more complicated geometry in which a hexahedral mesh could not be generated, tetrahedral quadratic elements have been used. For the boundary conditions, cylindrical support has been applied to the front wheel as shown in Fig. 5a indicated in purple, keeping the radial and axial directions fixed and the tangential direction free, allowing the model to rotate around that axis. Then, a frictionless support has been applied to the flat face of the main part (10) of the rear wheel as shown in Fig. 5b, fixing the vertical displacement. The 600 N loads are applied as stated before on the handle (4) as shown in Fig. 4a previously.

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Fig. 5. (a) Cylindrical support front wheel; (b) frictionless support rear wheel.

The results are obtained and equivalent Von Mises maximum stress is shown (Fig. 6a, 7b) as well as the security factor (Fig. 6c). The maximum stress is where the handle meets the upper tube. The safety factor is calculated with the maximum equivalent stress and ultimate yield strength.

Fig. 6. (a) Maximum equivalent stress; (b) maximum equivalent stress close up; (c) safety factor close up

7 Analysis II This second analysis has been done with 490 N distributed on the gripping surface of each handle. This analysis has been performed under the same material, geometry, mesh and boundary conditions. However, the loads change: the maximum user mass has been distributed equally on the gripping surface of both handles. Thus, a 490 N load has been applied on each handle (as shown in Fig. 4). Once again, the results are calculated and equivalent Von Mises maximum stress is shown (Fig. 7a) as well as the security factor (Fig. 7b) and vertical displacement (Fig. 7c). The safety factor is calculated with the maximum equivalent stress and tensile yield strength. Again, the maximum stress is where the handle meets the upper tube.

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Fig. 7. (a) Maximum equivalent stress close up; (b) safety factor close up; (c) maximum vertical displacement

8 Conclusions In this work, a novel rollator for hospital usage has been presented. This rollator is adjustable in height by discrete positions, it includes a width adjusting system, also adjustable by discrete positions, four lockable/unlockable swivel wheels and braking system with both pressure brake system and lever brake system. This works meets the following SDG: SDG3, SDG4, SDG9, SDG10, and SDG12. Regarding SDG3 and SDG10 the rollator improves the mental and social health of the user, offering support and stability when walking to increase mobility, safety and prevent falls, but also offering an improvement in self-esteem. In relation to SDG4, this is an educational end-of-degree project. In connection with SDG9, this work contributes to innovation since a novel medical rolling walker is proposed. And finally, with respect to SDG12 this work contributes to sustainable production as most of the parts are designed to be interchangeable in case of deterioration. It also contributes to responsible consumption as hospitals will need to purchase fewer rolling walkers. Analyzing the results, in the 600 N analysis it can be observed that the ultimate tensile strength of Aluminum is passed (310 MPa). However, this occurs very locally at the sharp edge on the model that is not going to exist in reality, and the stress value is increased at that point, therefore the result can be accepted. In the 490 N analysis, the tensile yield strength of Aluminum (276 MPa) is not reached, therefore there will be no plasticization of the material. And observing the vertical displacement, the handle descends 1.8 cm, which is acceptable considering the patient will not put all of the weight into the rollator. For future lines of this project, a roll-up seat is intended to be included so that the patient can sit down to rest and at the same time the seat can be compatible with the width adjustment of the rolling walker. Also, for future lines it is intended to build a prototype and perform the previously described Analysis I.

References 1. United Nations: https://www.un.org/es/global-issues/ageing. Last accessed 23 Feb 2023

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2. Nada es gratis: https://nadaesgratis.es/j-ignacio-conde-ruiz/espana-camino-de-ser-el-paismas-envejecido-de-europa. Last accessed 23 Feb 2023 3. Statista, https://es.statista.com/estadisticas/631836/dificultades-de-movimiento-en-per sonas-mayores-espana-por-grupo-de-edad, last accessed 2023/02/23. 4. Farmagranada: https://www.farmagranada.com/ortopedia-andadores-rollators/6342-mobicl inic-escorial-andador-ancianos-aluminio-plegable-frenos-asiento-respaldo-ruedas-burdeos. Last accessed 26 Jan 2023 5. Farmagranada: https://www.farmagranada.com/ortopedia-andadores-rollators/6384-mobicl inic-prado-andador. Last accessed 26 Jan 2023 6. Ortoespaña orthopedics: https://xn--ortopediaortoespaa-30b.es/andadores-de-cuatro-ruedas/ 2027-andador-de-4-ruedas-con-frenos-en-las-manetas-four-light-.html?gclid=CjwKCAiA5 sieBhBnEiwAR9oh2lePEVToPwUsNmn6FAUdHKRHckqxnpaubfNbdUpHmn64_jc5Zvq iahoCNM4QAvD_BwE. Last accessed 26 Jan 2023 7. Queraltó: https://www.queralto.com/22763-andador-para-adultos-plegable-aluminioasiento-y-respaldo-burdeos-paterna-clinicalfy.html?gclid=CjwKCAiA5sieBhBnEiwAR 9oh2rI_cpNO8G8UtMjjpoOf6V7e3c0RuwosEk7vAZhDSw9pTLaGYwuwJxoCyhYQA vD_BwE. Last accessed 26 Jan 2023 8. Mimas orthopedics: https://www.ortopediamimas.com/blog-de-ortopedia/como-elegir-elmejor-andador-para-mayores/. Last accessed 26 Jan 2023 9. Cuideo: https://cuideo.com/blog/andadores-personas-mayores/#:~:text=Algunos%20de% 20los%20beneficios%20de,al%20que%20se%20agarra%20constantemente. Last accessed 22 Feb 2023 10. UNE-EN ISO 11199-2-2021 (Assistive products for walking manipulated by both arms. Requirements and test methods. Part 2: Rollators)

Linkages, Gearing, Transmissions and Actuators

Influence of Design Parameters in Energy Lost for Eccentric Cam Mechanisms with Translational Roller Follower P. Català1(B) , L. Jordi2 , and J. M. Veciana2 1 Department of Mechanical Engineering, Universitat Politècnica de Catalunya, EPSEM, Av. de

les Bases de Manresa 61-73, 08242 Manresa, Spain [email protected] 2 Department of Mechanical Engineering, Universitat Politècnica de Catalunya, ETSEIB, Av. Diagonal 647, 08028 Barcelona, Spain {lluisa.jordi,joaquim.maria.veciana}@upc.edu

Abstract. The evaluation of energy efficiency, and not only the cost, is becoming a relevant issue when choosing among different solutions that allow a machine to fulfil with the required task. The aim of this study is to analyze the influence that the basic design parameters for eccentric cam mechanisms with translational roller follower have in the evaluation of energy lost per cycle. The problem formulation is carried out by using the kinematic equivalence with a slider-crank mechanism and considering a viscous friction model for the quantification of the energy lost at lower pairs. The study provides recommendations to choose design parameters for minimizing energy lost per cycle, while respecting the typical rules of the thumb when designing cam mechanisms. This study concludes that to increase the roller radius and to avoid the usage of an offset in the follower are the main recommendations for reducing energy lost per cycle. Keywords: SDG9 · SDG4 · Cam Mechanism · Energy Lost · Energy Efficiency · Viscous Friction

1 Introduction Cam mechanisms with translational followers are a common solution in automated production machinery to transform a full rotation input motion into a complex output motion with or without dwells segments. Depending on the required output motion, there are other mechanical transmissions that can be an alternative to cam mechanisms, such as non-circular gears combined with a linkage mechanism [1] or a Geneva mechanism, if an indexing output motion is required [2]. If the required output motion is a single rise and fall motion law per each cam revolution, this can be provided by an eccentric cam mechanism with translational follower, which is kinematically equivalent to a slidercrank mechanism [3–6]. The known advantages of cam mechanisms are that can be more compact and easier to design for a specific output motion than the equivalent linkage mechanism [4]. The © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 191–198, 2023. https://doi.org/10.1007/978-3-031-32439-0_22

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disadvantages are inherent to their manufacturing processes, which are more difficult and expensive. Since the outer profile is circular, these disadvantages are minimal for eccentric cam mechanisms. At early stages of the design process, when evaluating a mechanical transmission or a complete machine, it is common to have the possibility of choosing among several functional solutions. For each one, the evaluation of energy consumption or the lifecycle assessment is a dimension that is gaining importance. Within the Sustainable Developments Goals (SDG), Goal 9 contemplates the promotion of sustainable industrialization [7]. Consequently, people involved in machine design, such as engineering students and their professors, have a key role to reach this specific Goal 9. Therefore, it is a good practice to disseminate the culture of evaluating designs from a sustainable perspective [8, 9], instead of only evaluate cost reduction. Pabiszczak and Kowal [10] study an alternative to a gear transmission, which is a novel eccentric rolling transmission that reduces power losses. Furthermore, it exits the political commitment to implement the SDG at any educational level. Educators are being pushed for linking the content of their subjects with specific SDG, so students acquire specific learning outcomes and educational competences related with SDG. In fact, SDG 4 is dedicated to quality education. As an example, there is the reformulation of the new curriculum for higher school education approved by the Catalan Government on September 2022 [11], where many subjects are related with SDG. This paper focuses on the influence that the basic design parameters for eccentric cam mechanisms with translational roller follower have in the evaluation of energy lost per cycle, compared, as alternative design approach, to their equivalent slider-crank mechanisms. The kinematic equivalence is also valid for analyzing other types of cam mechanisms [6], so the proposed study can be adapted. The eccentric cam and slider-crank mechanisms are normally analyzed at bachelor’s degree in mechanical or industrial engineering level and even at high school. Therefore, the authors with this study also want to: i) facilitate the culture of comparing equivalent solutions in terms of energy consumption; ii) disseminate among students and professors the central role that mechanical engineering content syllabus has to reach some targets specified within SDG.

2 Problem Formulation Figure 1 shows an eccentric cam mechanism with a translational roller follower, which consist of three mobile solids –an eccentric cam (solid 1), a roller (solid 2) and a follower (solid 3)– with three lower pairs and one higher pair (point J). In red line it is depicted the kinematic equivalent slider-crank mechanism [3–5]. This equivalence helps to study the energy lost per cycle for any eccentric cam mechanism with translational roller follower. Geometric parameters used in Fig. 1 are described in Table 1. Figure 1 helps to show the geometric relations existing between some of the eccentric cam geometric parameters (rp , rr , rb , ε, ρc , ρp ) and the slider-crank geometric parameters (lOG , lGB and ε). Cam design handbooks [4, 5] present Eq. (1) to obtain the linear displacement function imposed on the roller center d (ϕ1 ) and Eq. (2) to define the prime circle radius rp ,

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Fig. 1. Eccentric cam mechanism with translational roller follower

Table 1. Definition of the required geometric parameters. Parameter

Parameter

Offset between the fixed guide and the rotation center of the eccentric cam, ε

Instantaneous rotation center between the eccentric cam (solid 1) and the follower (solid 3), assuming no sliding at contact point J, I13

Eccentricity of the circular cam. Equivalent crank length, lOG

Distance between points O and I13 , d  (ϕ1 )

Equivalent rod length, lGB

Base circle radius, rb

Angular displacement of the eccentric cam, ϕ1

Prime circle radius, rp

Angular displacement of the roller, ϕr

Radius of the eccentric cam, ρc

Linear displacement function imposed on the roller center, d (ϕ1 )

Radius of the cam pitch curve, ρp

Motion law defined with its minimum value equal to zero (smin = 0), s(ϕ1 )

Pressure angle, φ

Radius of the roller follower, rr

as a function of the design parameters cam base circle radius, rb , and roller radius, rr . Besides, a motion law s(ϕ1 ) defined with its minimum value equal to zero (smin = 0) is needed, defined with Eq. (3), where dmin is the minimum value of d (ϕ1 ) at the lowest

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dead point configuration. According to Fig. 1 and using the kinematic equivalence with the slider-crank mechanism, dmin is calculated with Eq. (4). Then Eq. (5) is obtained combining Eq. (1), Eq. (3) and Eq. (4). Additionally, it can be observed in Fig. 1 that the cam pitch curve for an eccentric cam is constant and equal to rod length, ρp = lGB .  (1) d (ϕ1 ) = s(ϕ1 ) + rp2 − ε2 rp = rb + rr

(2)

s(ϕ1 ) = d (ϕ1 ) − dmin

(3)

 dmin =

(lGB − lOG )2 − ε2

rp = (lGB − lOG )

(4) (5)

Therefore, by fixing the design parameters lOG , lGB and ε for a slider-crank mechanism, the design parameters for the equivalent eccentric cam are defined, as well. If a roller follower is used, the design parameter radius of the roller, rr , is also required. To include a roller follower allows the assumption of no sliding velocities in the contact between the cam and the roller. Hence, the energy lost in this higher pair is neglected in front of the energy lost in the lower pairs. The distance d  (ϕ1 ) between points O and I13 depends only on geometric parameters and is independent of the angular velocity of the cam [3–5]. It is obtained as the first derivate of Eq. (1) with respect to ϕ1 . The linear velocity d˙ (ϕ1 ) of the follower is obtained with Eq. (6) d˙ (ϕ1 ) = d  · ϕ˙1

(6)

If the rotation of the roller follower is blocked, there will be a sliding velocity at the cam-roller contact point J. The modulus of the sliding velocity vslid is calculated with Eq. (7), and can be deducted from Fig. 1.     2 2    d + (d − ε) − rr ϕ˙1 (7) vslid = I13 J ϕ˙1 = While the roller rotates freely through the revolute pair B, the roller will rotate with an angular velocity ϕ˙r = vslid /rr if the sliding velocity at the cam-roller contact point is supposed null. Using Eq. (7), ϕ˙r is calculated with Eq. (8).   d 2 + (d  − ε)2 − rr ϕ˙ r = ϕ˙1 (8) rr The quantification of the total energy lost per cycle is carried out using a viscous friction model approach at the lower pairs of the transmission and, hence, only the resolution of the kinematics is needed. The total energy lost per cycle Elost is calculated

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with Eq. (9), where cO , cB and c3 are the viscous damping friction coefficients in the revolute pair O, the revolute pair B and the prismatic pair between the follower and the fixed guide, respectively. According to Eq. (9), Elost does not depend on the mass and the inertia of solids. This is considered an advantage at initial stages of a design, where the aforementioned parameters can be modified within a wide dimensional range, or even study different equivalent transmission alternatives. 

(9) cO ϕ˙ 1 · ϕ˙ 1 + cB ϕ˙ r · ϕ˙ r + c3 d˙ · d˙ dt Elost =

3 Results Numerical simulations in MATLAB® are carried out with the expressions defined in Sect. 2. A representative workspace of the energy lost per cycle is obtained, for a wide range of eccentric cam mechanisms, as a function of the design parameters, by using its equivalence with a slider-crank mechanism. This workspace is limited in the ranges defined by constraints (10)–(14). 10 mm  lOG  400 mm

(10)

2lOG  lGB  10lOG

(11)

0  ε  0.75lOG

(12)

lGB  2lOG + ε

(13)

lGB /3  rr  2lGB /3

(14)

The length of the crank lOG is defined as the input design parameter with constraint (10). The length of the rod lGB and the offset of the slider ε are defined proportional to lOG with constraint (11) and constraint (12), respectively. These dimensions are considered representative for eccentric cam mechanisms, which are normally implemented in automated production machinery. Constraint (13) ensures a full rotation of the crank, as well as that the pressure angle is limited to φ  30◦ , to accomplish the design recommendations for this angle [4, 5]. The radius of the roller rr is defined with constraint (14) and ensures that the cam pitch curve fulfils the recommendation 1.5rr  ρp  3rr , for ensuring an acceptable level on the local surface stresses [4]. Table 2 shows the parameters used to evaluate the energy lost per cycle with Eq. (9). A set of experimental tests were carried out to obtain the values of the presented viscous damping friction coefficients from commercial bushings and bearings. The first test consisted in the measurement of the torque versus the angular velocity to determine cO , using of a dynamometer attached to a string enrolled to the input rotation axis, supported with two row angular ball bearings. The second test consisted in the use of a pendulum system, following the methodology explained in [12] to obtain cB . The third

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Parameter

Value

ϕ˙1 [rad/s]

36.65

ϕ¨1 [rad/s2 ]

0

cO [N·m/(rad/s)]

0.17

cB [N·m/(rad/s)]

0.026

c3 [N/(m/s)]

24.40

test consisted in obtaining the frequency response of the slider system with auxiliary springs and adjusting it to the theoretical one to obtain c3 . This last test has been carried out with a shaker test device. The energy lost per cycle Elost obtained for the defined workspace is represented in Fig. 2a. The two-dimension surfaces depicted are the boundary cases imposed with constraint (12) and constraint (14). The region 1 of Fig. 2a has been enlarged to better show the differences in Fig. 2b. The following conclusions can be derived from Fig. 2: • The most favourable cases in terms of reducing Elost are obtained when using the biggest roller radius (rr = 2lGB /3) and null offset (ε = 0). This can be observed because the blue line two-dimension surface is always at the bottom position. By increasing the roller radius, the angular velocity of the roller ϕ˙r is reduced. Thus, the Elost associated to revolute pair B is also reduced. • The bigger the offset of the follower ε is, the higher the energy lost per cycle Elost is. The lines of the two-dimension surfaces that correspond to non-null offset (ε = 0.75lOG ) predict more Elost than the ones without offset (ε = 0), for both rollers radius: the smallest (black dashed line) and the biggest roller radius (cyan dashed line).

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Fig. 2. Energy lost per cycle workspace for eccentric cam mechanisms

4 Conclusions This study shows the influence of the design parameters in the total energy lost per cycle for eccentric cam mechanisms with translational roller follower. The analysis has been carried out by comparing a cam mechanism with a kinematically equivalent slider-crank mechanism, and applying a viscous friction model for the quantification of the total energy lost per cycle. According to the results presented in Sect. 3, the major contributor to the energy lost per cycle is the roller radius, after the offset of follower and finally the ratio between the length of the equivalent rod and the equivalent crank. Therefore, the main environmental design guidelines for obtaining an eccentric cam mechanism that reduces the energy lost per cycle are to increase the roller radius and avoid the usage of an offset of the follower. The aim of this study is to give tools to understand the gross influence that each design parameter has in the evaluation of the sustainability or environmental impact, when there is the possibility to choose between several functional solutions, as it is the case at early stages of the design process. The evaluation of the sustainability domain is gaining relevance when choosing the final solution as it is contemplated in the scope of SDG 9.

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The presented approach can be somehow adapted for the study of other cam mechanisms. However, the eccentric cam mechanism is proposed because it facilitates the comparison with another kinematically equivalent mechanism, such as the slider-crank. Both mechanisms are widely used as examples at bachelor’s degree in mechanical or industrial engineering level and even at high school. Therefore, the authors believe that this study serves as a good educational baseline for facing energetic comparison of equivalent functional solutions. Relating the syllabus of courses, learning outcomes or educational competencies with SDG is a nowadays educational trend at any level.

References 1. Ottaviano, E., Mundo, D., Danieli, G.A., Ceccarelli, M.: Numerical and experimental analysis of non-circular gears and cam-follower systems as function generators. Mech. Mach. Theory 43(8), 996–1008 (2008) 2. Figliolini, G., Rea, P., Angeles, J.: The pure-rolling cam-equivalent of the Geneva mechanism. Mech. Mach. Theory 41(11), 1320–1335 (2006) 3. Cardona, S., Clos, D.: Teoria de Màquines, 2nd edn. Edicions UPC, Barcelona (2009) 4. Norton, R.L.: Cam Design and Manufacturing Handbook, 1st edn. Industrial Press Inc., New York (2002) 5. Rothbart, H.A.: Cam Design Handbook, 1st edn. McGraw-Hill Inc., New York (2003) 6. Lanni, C., Carbone, G., Ceccarelli, M., Ottaviano, E.: Numerical and experimental analyses of radial cams with circular-arc profiles. Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 220(1), 111–125 (2006) 7. United Nations, Sustainable Development Goals. Goal 9: Build resilient infrastructure, promote sustainable industrialization and foster innovation. https://www.un.org/sustainabledeve lopment/infrastructure-industrialization. Last accessed 10 Jan 2023 8. Boscariol, P., Caracciolo, R., Richiedei, D.: Does inertia matching imply energy efficiency? In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 282–289. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-87383-7_31 9. Marchis, V.: Beyond the mechanical engineering education. new frontiers for a sustainable growth. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 635–640. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-873837_68 10. Pabiszczak, S., Kowal, M.: Efficiency of the eccentric rolling transmission. Mech. Mach. Theory 169, 104655 (2022) 11. Departament_d’Educació, “Nou currículum batxillerat.” DOGC núm. 8758, Decret 171/2022 20.9.2022. https://portaldogc.gencat.cat/utilsEADOP/PDF/8758/1927851.pdf. Last accessed 21 Feb 2023 12. Veciana, J.M., Jordi, L., Lores, E.: Residual vibration reduction in back-and-forth moving systems driven by slider-crank mechanisms working through a dead point configuration. Mech. Mach. Theory 158, 104239 (2021)

Friction Models for a Sustainable Design: Friction Coefficient in Lubricated Conformal Pairs Enrico Ciulli(B) University of Pisa, Pisa, Italy [email protected]

Abstract. Tribological aspects must be taken into account for a sustainable design of new components and materials developed to obtain weight reduction and greater efficiency. Reducing friction and wear produces energy and material savings, both connected with several Sustainable Development Goals. To limit the time consuming expensive experimental tests on new materials and components, simulations can be performed for which reliable values of the friction coefficient are necessary. In this work, some basic aspects of the lubrication regimes are firstly reviewed with the related friction coefficient trends represented with the Stribeck and Lambda curves, also evidencing the reasons of the similarity between the two curves. Formulas and diagrams are then reported for the friction coefficient of full lubricated conformal pairs. For thrust bearings the friction coefficient f can be expressed as a function of the parameter m and is related to the Kingsbury number K. For tilting pads f is proportional to K the power of 0.5. For plain journal bearings f is a function of the dimensionless eccentricity ε and is related to the the Sommerfeld number S to powers ranging roughly from 0.5 to 0.8 depending on the ratio between the axial length and the diameter for S smaller than 0.1, and tending to 1 for higher values of S. The reported formulas and diagrams can be used for design purpose. Keywords: SDG12 · Green Tribology · Friction Coefficient · Lubrication · Stribeck Curve · Sommerfeld Number · Thrust Bearings · Journal Bearings

1 Introduction Tribological aspects must be taken into account for a correct design of new components and materials. Reductions of friction and wear are connected to greater efficiency and material saving. This means less pollution and therefore a more sustainable life, strictly connected with the Sustainable Development Goals, where efficiency is mentioned several times [1]. Particularly Goal 12 (Responsible Consumption and Production) mentions sustainable consumption and production, efficient use of natural resources, environmentally sound management of chemicals and all wastes, and the significant reduction of release to air, water and soil. There is a trend today to weight reduction and more power density of the mechanical components. New materials, surface treatments, coatings and textures can be used and their tribological behavior under lubricated conditions © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 199–208, 2023. https://doi.org/10.1007/978-3-031-32439-0_23

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must be investigated. Experimental tests are necessary due to the complexity of the tribological phenomena, but they can be extremely energy- and time-consuming. Theoretical/numerical simulations of the mechanical components are very useful for reducing the number of the expensive experimental tests. A reliable value of the friction coefficient is necessary for an appropriate simulation of the behavior of the pairs. Unfortunately there are a lot of factors that influence friction, as the lubrication regime, the behavior of the lubricant and the geometry of the contact (e.g. conformal or non-conformal). Due to the vastness of the problem, this work is necessarily focused only on some aspects, in particular on friction in lubricated conformal contacts. After a recall to some basic aspects, friction coefficient formulas and diagrams under full lubricated conditions for conformal pairs with Newtonian lubricants are reported that can be used for a sustainable tribological design.

2 Friction Coefficient Trends: Stribeck and Lambda Curves The values of the friction coefficient in lubricated contacts can vary a lot depending on the level of occurrence of contacts between the roughness asperities of the bodies’ surfaces. Three different regimes are commonly identified: boundary lubrication, when the lubricant film is reduced to molecules absorbed on the solids’ surfaces, mixed lubrication, when the load is shared between the locally contacting surfaces and the pressurized lubricant film, and full fluid lubrication when the lubricant film completely separates the solids. The transition among the different regimes is well depicted by two similar curves, the Stribeck and Lambda curves, Fig. 1.

Fig. 1. Qualitative trend of the friction coefficient in Stribeck and Lambda curves.

As reported in [2], in the Stribeck curve the friction coefficient is usually plotted as a function of a service dimensionless parameter S P proportional to the lubricant viscosity μ and to the body’s surface velocity u, and inversely proportional to the load per unit length W /L, SP ∝ (μu)/(W /L). This kind of friction trend was firstly experimentally observed in journal bearings by Stribeck in 1902, as reported in [3]. Different expressions

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and names can be found in literature for S P , mainly depending on the kind of lubricated contact [2]. Different curves can be obtained by varying the surface roughness. The roughness effect is instead included in the Lambda () curve, where the friction coefficient is plotted as a function of the ratio of a representative value of lubricant film thickness and the equivalent root mean square roughness Rq of the surfaces of the two

bodies in contact,  = h/ R2q1 + R2q2 . There is a connection between S P and  and this explains the similarity between the two curves as reported below. A comprehensive expression of the friction coefficient f can be found by using the ratio between the tangential (friction) and the normal force acting between two contacting bodies including both the effect of the solids’ contacts and of the viscous action of the lubricant. By indicating with f b the friction coefficient under boundary lubrication conditions and with f h the friction coefficient for full lubrication conditions, the total friction force can be expressed as T = fb Wb + fh Wh , being W = Wb + Wh the total load, which leads to the total friction coefficient formula [3]: f =

Wb Wh T = fb + fh W W W

(1)

with W b /W and W h /W ranging from 0 to 1. When the ratio W b /W = 1 (W h /W = 0) boundary lubrication conditions occur and when W b /W = 0 (W h /W = 1) full lubrication conditions occur. Different expressions can be found in literature for the ratio W h /W as a function of the dimensionless film thickness . By indicating this load sharing function as g(), Eq. (1) can be put in forms such as   (2) f = fb 1 − g() + fh g() The values of g() range from 0 for  = 0 up to 1 when  reaches the value corresponding to the boundary between mixed and full lubrication conditions; g () maintains the value of 1 for  > 1. Expressions for g() can be found for instance in [4]. Regarding with the values of the friction coefficients, f b is usually considered constant (typical values range from 0.08 to 0.1), while f h has to be evaluated from the friction force generated by the fluid action on the body’s surface. Actually things are more complicated: in boundary and mixed lubrication regimes wear can occur that affects f b ; the effect of roughness on the film thickness under mixed lubrication conditions depends on additional aspects rather than Rq only, as the orientation of the machining marks; the calculated lubricated friction depends on the lubricant’s constitutive behavior that for non-conformal contacts is often non Newtonian, depending on the contact geometry and on the working conditions. Every aspect needs specific studies. The results reported in the following are specifically addressed to friction for conformal contacts under full fluid lubrication conditions with Newtonian fluids. In this case the friction force is the integral of the tangential stress τ: τ =μ

∂v = μγ˙ ∂y

(3)

where μ is the dynamic viscosity, v the velocity of the fluid and γ˙ the shear strain rate. As it can be also noted from Fig. 2, ∂v/∂y is variable with x (in addition than along y).

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To estimate the action on a body, τ must be evaluated at the surface level (e.g. y = 0 for the moving body in the figure).

Fig. 2. Generic lubricated contact.

A rough estimation of the friction coefficient f h can be obtained as the ratio between approximated mean values of shear stress and pressure p: fh =

τ∗ pm

(4)

where τ * is the value of the tangential stress in the position x* where the pressure is maximum and the film thickness is h* (Fig. 2): τ∗ = μ

u h∗

(5)

and pm is the mean contact pressure. For the full lubricated contacts, the film thickness is always a function of the viscosity, the body’s velocity, a significant geometrical dimension L and the load: h∗ ∝

μc1 uc2 Lc3 W c4

(6)

The values of the exponents c1 , c2 , c3 and c4 depend on several factors as the kind of lubrication and the shape of the contacting bodies. The mean pressure is related to the normal force W and to the pair’s dimensions (let’s indicate them with a generic R): pm ∝

W c5 Rc6

By combining Eqs. (4), (5), (6) and (7), we obtain:  1−c1 1−c2  Rc6 u τ∗ μuW c4 Rc6 μ fh = ∝ c c c = c −c pm μ 1 u 2 L 3 W c5 (W /L) 5 4 Lc3 +c5 −c4

(7)

(8)

The necessary constant that must appear in an equality is generally dimensional. The expression in the square brackets contains the same quantities present in S P and in

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the film thickness formulas, but with different exponents. This explains the similarity between Stribeck and Lambda curves. In fact, under full lubrication conditions we have:  c1 c2  1 μ u Lc3 −c4  ∝ (9) (W /L)c4 2 R + R2 q1

q2

If for instance c1 , c2 , c3 and c4 are equal to 0.5, c5 = 1 and c6 = 2, as for the thrust bearings described in the next section, we obtain (the necessary constants for the equalities have the dimensions of an inverse of a length and of a length respectively):   √ μ0.5 u0.5 R2 R2 μ0.5 u0.5 1 SP   ∝ SP ,  ∝ fh ∝ ∝ (10) 0.5 0.5 L L 2 2 2 (W /L) (W /L) Rq1 + Rq2 Rq1 + R2q2

3 Thrust Bearings Expressions for W and T acting on a single rectangular pad (a parallel-surface slider bearing, Fig. 3) as a function of the significant quantities of the lubricated contact can be found in several papers and books. The friction coefficient f h can then be evaluated by dividing T and W. Analytical expressions can be found for the different functions when b  a, while they can be numerically evaluated in the other cases. For the sake of brevity, only the relevant formulas for the evaluation of f h are reported in the following, while for instance [5] and [6] can be seen for the additional expressions. The Kingsbury number K is commonly used as S P for the pads of thrust bearings: K=

μub μu = pm a W

(11)

with pm = W /ab the mean pressure acting on the pad. By using the dimensionless quantities (refer to Fig. 3 for the symbols used): hi − ho ,  = b/a (12) ho the following expression can be found for the friction coefficient: √ T = Kφ(m, ) (13) fh = W For a given tilting pad, λ can√be calculated from the dimensions a and b, while m is fixed. Therefore f h depends on K. Expressions for the function φ are reported below. m=

3.1 Infinitely Wide Slider Bearing In the case of b  a the side-leakage along the z direction can be neglected and the flux is one-dimensional. Analytical expressions can be found for the main quantities as a function of the parameter m only. Rearranging the formulas reported for instance in [5], the friction coefficient function can be expressed as:

2 (4 + 2m)ln(1 + m) − 3m φ(m) = (14) √ 3 (2 + m)[(2 + m)ln(1 + m) − 2m] The trend of this function is shown with a dashed line in Fig. 4.

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Fig. 3. Parallel-surface slider bearing.

3.2 Finite Width Slider Bearing Curve-fitted functions based on numerically calculated results are available in [7] for the quantities of interest for the design of hydrodynamic bearings. The Reynolds equations is numerically solved for certain values of the input parameters, so that the expressions found for the rectangular tilting pad thrust bearing are valid in the domains 0.8 < m < 5 and 0.5 < λ < 6. By rearranging the formulas of T and W the following expression can be obtained for the friction coefficient function:  fθ mgθ 2 + mfψ (15) φ(m, ) = 1 − 1 + 2m gψ mkψ where fθ = 0.7095 + 0.2873e− , gθ = 1.1964 + 0.0715e− , fψ = 1.621 − 0.5 0.0105 0.5e−1.996 , gψ = 0.4607 − 1+ 1.490 and kψ = 0.6709 +  . Some trends of φ (m, λ) are shown in Fig. 4. It’s worth noting that values for b/a = 4 are very close to those obtained with Eq. (14) for the infinitely wide slider bearing.

Fig. 4. Trends of the friction function φ for slider bearings.

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4 Plain Journal Bearings The Sommerfeld number S is normally used as S P for plain journal bearings, Fig. 5:   2 μ D μLD D 2 S= = (16) 2πpm 2C 2πW 2C where Ω is the rotational speed of the shaft, D and L the bearing’s diameter and axial length respectively, pm the conventional mean pressure W /(DL), C the radial clearance. It is worth noting that, as reported in [8], the original dimensionless Sommerfeld number was in reality the reciprocal of the one commonly used shown in Eq. (16). Results are usually presented as a function of the dimensionless eccentricity (being the eccentricity e the distance between the centers of shaft and housing): ε = e/C

(17)

The friction coefficient is evaluated as the ratio of the friction torque M f and the product between the load and the bearing’s radius: fh =

Mf WD/2

(18)

Both S and f h can be evaluated as a function of the dimensionless eccentricity ε. Expressions are available for long (with different boundary conditions) and short bearings, while tabulated numerical results are available for intermediate values of the ratio L/D. In fact, when the dimension (in this case the axial length L) along the direction perpendicular to the one of the motion is much bigger or much smaller than the other dimension, an analytical solution can be found.

Fig. 5. Plain journal bearing.

4.1 Long Journal Bearing The solution for long bearings, usually valid for L/D ≥ 4 [6], is found when the side leakage along the bearing’s axis direction can be neglected. Different boundary conditions can be used that produce different expressions for the main quantities. The expressions reported below were obtained by rearranging the ones reported in [6].

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Sommerfeld’s Boundary Conditions. The so called Sommerfeld’s boundary conditions only consider the periodicity conditions that the pressure p is the same for ϕ = 0 and ϕ = 2π, where the film thickness is maximum (see Fig. 5). This produce an anti-symmetrical pressure distribution respect to the position with ϕ = π. If p(0) = p(2π ) = 0, p < 0 for π < ϕ < 2 π. The following expressions are found for both S and f h :

√ 2 + ε2 1 − ε2 2C 1 + 2ε2 , fh = (19) S= 2 12π ε D 3ε Gümbel’s or Half Sommerfeld’s Boundary Conditions. By using the Sommerfeld’s boundary conditions and simply putting to zero the pressure for π < ϕ < 2π, we obtain:

  √

2 + ε2 1 − ε2 2C π 4 + 2ε + 5ε2 + 4ε3 1 − ε2   S= (20)

 , fh = D

 6πε 4ε2 + π2 1 − ε2 6ε(1 + ε) 4ε2 + π 2 1 − ε2

4.2 Short Journal Bearing Analytical expressions can be also found when the axial length of the bearing is much smaller compared to its diameter (for L/D ≤ 1/8 according to [6]). This is the so called Ocvirk and Dubois solution. The half Sommerfeld’s boundary conditions are also applied. By rearranging the formulas reported in [6], it is found:    2  2 D (1 − ε2 )2 2C D 2 π (2 + ε)(1 − ε) 1 − ε   S= , fh =

 L πε π2 − ε2 π2 − 16 D L ε π 2 − ε2 π 2 − 16 (21) It’s worth noting that in this case f bearing but also to the ratio (D/L)2 .

h

is not only related to 2C/D as for the long

4.3 Finite Length Journal Bearing For 0.25 < L/D < 4 the numerical solution of the complete Reynold’s equation is necessary. Tabulated numerical results for the main design quantities can be found in [6] for L/D = 0.25, 0.5, 1 and 2 for some values of ε between 0.1 and 0.95. Values are reported for the friction coefficient function: f  = fh

D 2C

(22)

Values for L/D < 1/8 and L/D ≥ 4 are also reported in the table, corresponding to the short and long bearing solutions respectively. In the first case S and f  are reported multiplied by (L/D)2 in order to obtain a function of ε only. In the second case the same results can be obtained with the solution for long bearings by imposing the so called Reynold’s boundary conditions p(0) = p(ϕ 0 ) = 0 where the angle ϕ 0 can be evaluated with the additional condition dp/dϕ|ϕ=ϕ0 = 0.

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Fig. 6. Trends of the friction function f  for plain journal bearings.

In Fig. 6 f  is plotted a function of S for the different L/D ratios together with the results for long and short bearings. Values of f  increase by decreasing L/D with an increasing value of the exponent of S. For a value of S lower than 0.1 f  ∝ S n , with n depending on L/D and roughly ranging from 0.5 for the long bearing solution up to 0.8 for the short one. For greater values of S the trend of f  tends to become linear. It can also be noted from its irregular trend for S < 0.03 that the full Sommerfeld solution can be used only for very light loads (high values of S).

5 Conclusions The friction coefficient trend is well represented by the Stribeck and Lambda curves. In both diagrams the friction coefficient is plotted as a function of dimensionless quantities containing viscosity, velocity and load, and this explain the similarity between the two curves. Formulas and diagrams are reported for the friction coefficient of full lubricated conformal pairs with Newtonian fluids. Based on analytical and numerical solutions, trends of the friction coefficient for thrust and plain journal bearings are reported. For tilting pad thrust bearings the friction coefficient is a function of the parameter m and is related to the Kingsbury number to the power of 0.5. For plain journal bearings the friction coefficient is a function of the dimensionless eccentricity ε and is related to the the Sommerfeld number to powers ranging roughly from 0.5 to 0.8 depending on the ratio between the axial length and the diameter, and tending to 1 for high values of S. The formulas and diagrams can be used for a quick estimation of the friction coefficient for design purposes. Acknowledgments. Financed by the European Union - NextGenerationEU (National Sustainable Mobility Center CN00000023, Italian Ministry of University and Research Decree n. 1033 17/06/2022, Spoke 11 - Innovative Materials & Lightweighting). The opinions expressed are those of the authors only and should not be considered as representative of the European Union or the European Commission’s official position. Neither the European Union nor the European Commission can be held responsible for them.

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References 1. Ciulli, E.: Tribology and sustainable development goals. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 438–447. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-87383-7_48 2. Ciulli, E.: Friction in lubricated contacts: from macro- to microscale effects. In: Bhushan, B. (ed.) Fundamentals of Tribology and Bridging the Gap Between the Macro-and Micro/Nanoscales, NATO Sciences Series, vol.10, pp. 725–734. Kluwer Academic Publishers, Dordrecht, The Netherlands (2001). https://doi.org/10.1007/978-94-010-0736-8_54 3. Vogelpohl, G.: Die Stribeck-Kurve als Kennzeichen des allgemainen Reibungsverhaltens geschmierter Gleiflächen. Zeitschrift des vereines Deutscher Ingenieure 96(9), 261–268 (1954) 4. Castro, J., Seabra, J.: Coefficient of friction in mixed film lubrication: gears versus twin-discs. Proc. Inst. Mech. Eng. Part J: J. Eng. Tribol. 221(3), 399–411 (2007). https://doi.org/10.1243/ 13506501JET257 5. Hamrock, B.J.: Fundamentals of Fluid Film Lubrication. McGraw-Hill, New York (1994) 6. Frêne, J., Nicolas, D., Degueurce, B., Berthe, D., Godet, M.: Hydrodynamic Lubrication Bearings and Thrust Bearings. Tribology Series, vol. 33. Elsevier, Amsterdam (1997) 7. Ståhl, J., Jacobson, B.O.: Design functions for hydrodynamic bearings. Proc. Instn. Mech. Eng. 215, 405–416 (2001) 8. Czichos, H.: Tribology. Elsevier, Amsterdam (1978)

Evolution of Gear Machining Technology in a Japanese Manufacturer – Realization of Skiving Method as an Application of 5-Axes Machining Center Daisuke Matsuura(B) and Tsune Kobayashi Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8552, Japan {matsuura.d.aa,kobayashi.t.cs}@m.titech.ac.jp

Abstract. Manufacturing of gears, core components of power transmission systems for automobiles, always needs technological innovation because it should achieve high-speed, mass production and precision machining simultaneously. The cutting-edge technology in this field is the “skiving machining” which utilizes the oblique cutting technique with modern 5-axes CNC machining center (MC) which is capable of achieving synchronous rotation and relative motion in-between a cutting tool and a work piece in high precision. There are some important technological innovations corresponding to the 5-axes MC, but some additional innovation corresponding to the tool design was especially needed to make the innovation happens. This paper introduces above innovations to achieve the machining and resulting impact of this technology by showing some examples in the production of machinery elements for automobiles. Keywords: Skiving machining · 5-axes CNC · Machining center · Machinery elements production · Automobile industry

1 Introduction Generative method is a key technology to achieve accurate machining of complicated shapes that can be described as geometrical functions. One of the major applications of the method is machining of gears which initially done by hob cutting and recently has been extended to “hard skiving” method. Skiving method is one of a kind of oblique cutting method which makes a stagger angle between the rotation centers of a work piece and a cutting tool. This method has originally patent claimed in 1910 in Germany [1], and has been physically implemented in 1960s by using specially modified machine tools which use mechanical chain to connect spindle shaft and work piece’s shaft as shown in Fig. 1 [2]. However, there were some technological difficulties on the practical application of this method, such that (1) as shown in Fig. 2, only a part of the circumferential velocity of a tool contributes to make the cutting happen, and (2) highly precise synchronization of the tool and work axes while achieving high spinning rate is required. Thanks to the advance of numerical control technology and production of 5-axes CNC © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 209–216, 2023. https://doi.org/10.1007/978-3-031-32439-0_24

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Fig. 1. A hard skiving (Hartschälen in german) machine tool made in 1962 which uses a mechanical chain using gears to achieve synchronous motion between the tool and work piece axes [2].

Fig. 2. An illustration showing how the cutting velocity along the tooth line occurs due to the existence of a stagger angle. The vectors #1 and #2 represent a feed velocity and a circumferential velocity, respectively, and their difference agrees with the tooth line (dashed) [2].

Fig. 3. Example of machinery elements for automobile’s power transmission system [3].

machining center, hard skiving has finally been realized and is contributing for mass production of various machinery components having complicated shapes as shown in Fig. 3 [3]. In this paper, the authors will introduce several important technological factors for the realization of this machining method especially on the design and maintenance of tool profiles, and resulting impact of this technology by showing some examples in the production of machinery elements for automobiles.

2 Principal of the Gear Skiving Method and Its Merits As said in the previous section, skiving method is achieved as the result of synchronous rotation of a tool and a work pieces both having basically cylindrical shapes. The most important factor is the existence of a stagger angle, η, as shown in Fig. 2. When this angle exists, a relative velocity between the work and tool pieces on a contact point has both a circumferential element and an axial element. In these two elements, only the axial element contributes to make the cutting happens. From this explanation, it can be said

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that (1) a target shape of the machining, namely the tooth profile of the gear, and the tool’s profile must mesh with each other, and (2) a tool’s profile can therefore be calculated as a conjugate of an objective shape of the gear as shown in Fig. 4. Once this principal is

Fig. 9. Impact of gear skiving method on the size reduction and stiffness increasing of a gear component for power transmission component for automobile [4].

Table 1. Comparison of gear skiving method and other conventional machining methods.

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understood, skiving method looks to be theoretically easy to implement. In addition, this method is able to cut both outside and inside gear teeth and is potentially able to substitute many other conventional machining tools as shown in Table 1. However, there are many technological challenges to make the method be applicable as summarized in Fig. 5. Those challenges can be classified into two groups, one belongs to the development of 5-axes CNC machining centers and the other belongs to the tool development. Although the former problems are relatively well known and counter solutions have been well developed in these days, latter ones still have many opened questions and therefore still need a lot of research and developments. In next section, some R&D results for tool design and maintenance technology in a Japanese industrial company, JTEKT, will be briefly introduced.

3 Practical Tool Development Process for Skiving Method As mentioned in the previous section, a profile, outline, of a cutting tool with respect to a target shape of a work piece must mesh with the target gear profile. However, just calculating a conjugate shape of the objective gear profile is not enough to obtain a practical tool shape because of the lack of blades. Namely, as shown in Fig. 6, many additional parameters such as rake angle, γ , relief angle, σ, and so on must be considered. In addition to that, maintenance process for maintaining the cutting quality with respect to its life time must be guaranteed. Here, it should be noted that (1) maintenance of a cutting tool is done by regrinding its blades at each regularly determined time span, and (2) because of the rake angle, cutting face’s outline changes after each regrinding. Left side of Fig. 7 shows a typical change of a blade after 15 times regrinding process. Since the cutting surface is retreaded 0.2 mm at each regrinding, it will be offset 3 mm away after 15 cycles. When the original profile (dashed line in the figure) and that of after 15 cycles (solid line) are compared, it can be seen that both the addendum diameter and the thickness of the blade are decreased. This will result in the change of the work profile, and therefore should be compensated. Based on the above consideration, the blades’ profile is optimized by choosing a suitable rake angle, and the distance between the tool and work’s rotation axes and feeding position of the blade along the rotation axis are adjusted by using the precise servo control of 5-CNC machining center. In Addition, the cutting blade’s profile on its left shoulder, on which edge the cutting is occur, is rounded by a compensation factor, Δ, along with the tooth line so that the remaining deviation of the work’s profile can be reduced as shown in the right side of Fig. 7. Figure 8 presents how the compensation of the cutting blade’s profile works for reducing the machining error. The two figures on the upper side that are the result in case of the modification with the factor Δ was not applied shows ineligible deviations, −12 µm at most. On the other hand, the two on the lower side, results in case of the factor Δ was a non-zero value, the deviation was −3 µm even after 15-grinding cycles.

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Fig. 6. An example of a skiving tool’s outlook (left) and important design parameters (right).

Fig. 7. Example of a profile change of a cutting surface due to regrinding process (left), and compensation factor, Δ, to minimize the deflection of work tooth profile due to the change of cutting blade’s profile after the regrinding cycle (right).

Fig. 8. Effect of the profile modification on the left shoulder of a cutting blade.

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Fig. 4. An illustration of skiving method as one of a kind of generation methods. The target shape of the work piece (tooth of a gear) can be obtained as the subtraction of the resulting envelope of the tool piece’s motion.

4 Impact of the Gear Skiving Method for the Establishment of Sustainable Automobile Industry Thanks to the research and development effort of which example is explained in the previous section, gear skiving method has become a reliable and effective machining technique which can solve requirements for machinery elements production in today’s automobile industry. Recently, transmission components of automobiles are required to be compact, with less noise and vibration and highly efficient while achieving wider reduction ratio than before due to the proliferation of electric vehicles (EV). Talking about the achievement of compactness, diameter of a skiving tool can become smaller than that of grinding tools, and the machining is done on the edge although it is done at the center rim of the wheel in case of grinding method. This difference contributes not only for the reduction of minimum machinable diameter of the work piece but also the shortening of release groove which is included in the total length of a shaft. As a result, compact and stiff gear shafts can be produced as shown in Fig. 9 [4]. The capability of skiving method for machining both internal and outer gears at a same time, multiple elements that have been separated because of the restriction of conventional machining

Fig. 5. Core technological factors for gear skiving method.

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Fig. 10. The 5-different kind of machining steps by using conventional machine tools (left) that can be executed by a 5-axes CNC machining center having gear skiving function (right) [5].

method can be unified, as shown in Fig. 3. These advantages are making more assertive and innovative design of automobile products possible. In addition to that, a 5-axes CNC machining center having gear skiving function is capable of replacing other conventional machine tools, as shown in Fig. 10 [5]. This means that multiple process can be done just after single chuck of a work piece in this machining center, and the lead time for the production can be greatly reduced, in addition to the save of required resource.

5 Conclusion In this paper, advantages of the gear skiving method and its major technical difficulties both on the development of 5-axes machining center and specially designed cutting tool have briefly been reviewed. Technical challenges regarding the development of 5-axes CNC machining center are relatively well known, and well-developed solutions have recently been obtained. However, latter challenges regarding tool development still have many opened questions and therefore more research and developments are required. The authors have therefore introduced some R&D activities and their results obtained in a Japanese machinery element and machining center company, including (1) how to design the shape profile of a tool which meshes with a target work’s profile, (2) how to arrange the tool’s profile so that it can be used as a cutting tool having blades, and (3) how a practical tool shape can be obtained as the modification of the solution of the step (2) so that change of the tool shape as the result of many regrinding processes can be compensated and machining quality and long life time of the tool can be guaranteed. At last, it has been introduced that impact of such development has resulted in the innovation of automobile machinery components and design of new automobiles.

References 1. Method of cutting van gears using a gear-like cutting tool with cutting edges on the face surfaces of the teeth, Germany patent application DE243514C (1912) 2. Pfauter, H.: Werkzeuge. In: Pfauter-Wälzfräsen: Teil 1 Verfahren, Maschinen, Anwendungstechnik, Wechselräder, pp. 19–20 and p. 81. Springer, Berlin, Heidelberg (1976). https://doi. org/10.1007/978-3-662-12681-3_3

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3. Commercial catalog of Toyota Harrier vehicle, Toyota Motor corp., (2005) 4. Tada, N.: Development of 3D Tooth Surface Creation Processing Technology Using Gear Skiving, JTEKT Engineering Journal English Edition, No. 1018E, pp. 66–72 (2022) 5. Ootsuka, Y.: Development of the GS200H5 Gear Skiving Center, JTEKT Engineering Journal English Edition, No. 1015E, pp. 62–66 (2018)

A Vibration Exciter for Dynamic Testing of Large Structures Renato Brancati1 , Domenico De Falco2 , Giandomenico Di Massa1 , Stefano Pagano1(B) , and Ernesto Rocca1 1 Università di Napoli Federico II, Naples, Italy

{Renato.brancati,giandomenico.dimassa,stefano.pagano, ernesto.rocca}@unina.it 2 Università della Campania Luigi Vanvitelli, Caserta, Italy [email protected]

Abstract. In the context of the periodic monitoring of bridges or other civil artifacts, characterized by low natural frequencies, a vibration excitation system is proposed for the dynamic monitoring. The system is based on a mass suspended on an air spring and excited to vibrate in resonance condition by means of an electrodynamic exciter (EDE). Therefore, the energy supplied by the EDE to the mass is small thanks to the resonance conditions. To perform a sweep excitation, the stiffness characteristics of the spring can be continuously modified, adjusting the air pressure of the spring and, consequently, the frequency and the amplitude of the exciting action provided by the EDE. The paper presents the description of the device and some evaluations based on experimental tests conducted on the air spring. Keywords: SDG9 · vibration exciters · structural monitoring · air springs · vibration transmission · dynamic monitoring

1 Introduction The monitoring systems of structures are used to verify the hypotheses of the design, to update the technical specifications, to check the efficiency of the vibration isolation systems, to check the state of degradation of a structure [1]. Over the years, many structures need to be monitored to verify their efficiency and to schedule any maintenance work; this is the case of artefacts such as bridges, buildings, bulkheads, tunnels, silos, chimneys, etc. which can be observed periodically or continuously in order to evaluate whether some static and/or dynamic parameters undergo variations. Monitoring is carried out by detecting quantities that directly affect the structure such as displacements, deformations, accelerations, etc. and related ones such as temperatures, humidity, wind speed, etc. The greater the number of quantities acquired, the greater the information will be useful for having a complete vision of the state of the structure and for efficiently programming maintenance interventions; in particular cases, the large number of information acquired requires the processing of big data [2]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 217–224, 2023. https://doi.org/10.1007/978-3-031-32439-0_25

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Monitoring can be continuous or periodic; the first type consists in continuously detecting some physical quantities to generate an alert signal if one of these exceeds the threshold value considered admissible. Periodic monitoring, on the other hand, is performed on a scheduled basis for the preventive diagnosis of structural deterioration and the scheduling of any maintenance interventions; periodic monitoring therefore does not have the purpose of providing an alert signal in case a catastrophic event is about to occur. Structural monitoring can be both static and dynamic. In the first case, the deformation behaviour of the structure is investigated to identify any progressive damage; this method provides precise local indications without giving information on the global behaviour of the structure. In the other case, dynamic monitoring is aimed at identifying the modal parameters of the structure (natural frequencies, modes of vibration, damping) which affect the behaviour of the entire structure; a variation of these parameters over time can indicate the onset of damage [3], i.e. a modification of the structure that negatively affects its current or future performance [4]. The dynamic monitoring detects vibrations due to: • an environmental excitation [5, 6], such as vehicular traffic, wind, micro-seism, etc., generally not measurable and of low intensity, and furthermore has the advantage of not requiring the adoption of a specific vibration excitation system; • a forced excitation, generated by a special vibration exciter. In this case it is possible to carry out repeatable tests with more reliable results, as it is possible to compare the characteristics of the motion of some points of the structure as time varies due to a known excitation. This method requires a preliminary theoretical investigation to define the position of the excitation system so that it is possible to excite the first natural modes of vibration of the tested structure. Forced vibrations can be excited by long-stroke electrodynamic shakers [7], electrohydraulic shakers [8] or with devices constituted by counter-rotating unbalanced discs (vibrodyne); • an impulsive excitation due to the application of a force or to the relaxation of an applied force. For example, in the case of offshore structures, the impulsive action can be achieved by pulling the structure with a tug and suddenly releasing it [9]. The impulsive excitation systems are often difficult to implement; the applied force is often difficult to measure. This paper considers the feasibility of realizing a mechanical excitation system to generate a forced excitation useful for periodic monitoring and suitable for large structures characterized by low natural frequencies. The paper represents a contribution to research in the field of Sustainable Development Goals number nine: Industry, Innovation and Infrastructure.

2 Methodologies to Excite Forced Vibrations of a Structure in Absence of a Fixed Point A structure can be excited to vibrate by an actuator if there is a fixed contrast element on which to fix it; in some cases, the contrast element is not available, and the structure can

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be forced to vibrate by moving a mass of a suitable size. This is, for example, the case of vibrodyne (Fig. 1a) which is made up of with two counter-rotating discs supporting two eccentric masses whose relative angular position φ can be modified to adjust the centrifugal force module exerted by each disc. By suitably phasing the two discs, a harmonic unidirectional force is generated. This device provides low excitation force if low frequency excitation is required. The exciting force may be generated even by means of a device consisting of a mass m which is driven to move in reciprocating motion with respect to the device frame that is fixed to the structure; the motion may be actuated in different ways, such as, for example, by a crank mechanism driven by an electric motor, by a hydraulic or pneumatic actuator, etc. (Fig. 1). In this case, neglecting the friction forces exerted by the guides, the power required to drive the mass along the vertical direction is equal to:   mZ 2 ω3 sen2ωt P(t) = mg + mω2 Z senωt Z ω cosωt = mg Z ωcosωt + 2

(1)

Being ω the circular frequency of the harmonic motion and Z the motion amplitude.

Fig. 1. a) Vibrodyne with 2 masses per disc b) mass driven by a crankshaft; c) mass driven by a pneumatic or hydraulic actuator

The power required to excite the motion can be reduced if the mass is placed on a spring and is excited to vibrate under resonant conditions, similarly to what happens with the sensing tubes of mass flowmeters based on the Coriolis effect [10]. In particular, the adoption of the air spring allows to modify the stiffness of the system making so possible to individuate a range of frequencies, excitable in resonance. In this case, indicating with σ the viscous damping coefficient, referring to a linear model in harmonic motion, the exciting force must be equal to the viscous reaction and the power to be supplied must be equal to: P(t) = σ z˙ 2 =

σ ω2 Z 2 σ ω2 Z 2 + cos2ωt 2 2

(2)

With reference to the diagram of Fig. 2a a vibration exciter can be considered, consisting of a mass suspended on an air spring and constrained to translate along the vertical direction; the spring is subjected to the action of an electromagnetic exciter (EME), arranged between the frame and the suspended mass.

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The spring is connected to an auxiliary air reservoir with adjustable volume. The tank consists of a membrane accumulator (Fig. 2b), which can be filled with water, at the bottom, to reduce the volume available for the air. Pressurized air is introduced into the tank by means of a motor-compressor; an on/off valve allows to inhibit the connection between the spring and the tank to allow the spring to operate with constant or variable air mass.

Fig. 2. Vibration exciter based on a mass suspended on air spring.

3 Air Spring Stiffness The classic air spring model is based on the piston-cylinder scheme of Fig. 3, in which it is assumed that the air evolves according to polytropic transformation due to the volume variation. The pressure is therefore p = po (V o /V)γ , where Vo and Po are respectively the initial volume and pressure. The exponent of the polytropic is chosen equal to 1.4 if the volume varies rapidly, and it is therefore possible to neglect the heat exchanges with the environment (adiabatic transformation). In this specific case the transformation can be considered almost adiabatic, and the value of the exponent γ can be chosen equal to 1.38 [11]. By indicating with P = pS the load acting on the spring, the following formula can be written (Fig. 1): γ  γ   γ V0 h0 1 = P0 = P0 (3) P = P0 V h0 − z 1 − z/h0 By deriving Eq. (4), the axial stiffness k of the spring and the natural frequency of the system can be obtained: γ mg γ P = ; h0 − z h0 − z   γ g 1 kz 1 fz = = 2π m 2π h0 − z kz =

(4)

(5)

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From (4), considering that: p = P/S; ho = V/S it can be seen that stiffness also depends on the area S: kz =

γ pS γ pS 2 γ P = V = h0 − z V − zS S −z

(6)

The natural circular frequency varies with the spring height z, which depends on the weight of the suspended mass m.

Fig. 3. Simple air spring

Fig. 4. Effective area diameter of a lobe spring

Commercial air springs are characterized by deformable rubber elements for which the reaction force to the load to be balanced is given by the gas pressure for the area of the section orthogonal to the load. However, unlike springs made with a piston-cylinder mechanism, the latter depends on the deformation of the spring itself (ie on the load itself). The effective area is determined experimentally as the ratio between the load acting on the spring and the internal pressure. Depending on the type of air spring, this area can increase or decrease with the deformation of the spring itself. In the lobe springs the effective area increases with the crushing as qualitatively indicated in Fig. 4. The stiffness of the air springs can still be defined by (6) if, instead of the constant area S, the value of the effective area S e , variable with the crushing, is considered. Equation (6) also indicates that it is possible to reduce the stiffness of the spring by increasing the volume V, which can be achieved by connecting the spring to an auxiliary reservoir of suitable capacity. In this case it is also possible to vary the damping of the component, by suitably adjusting the outflow section of the orifice located in the connecting duct between the spring and the tank. It should be noted that, if the spring operates at a constant load, the variation of the pressure corresponds to a variation of the height of the spring z and of the effective area S. From a theoretical point of view, therefore, the pressure variation cannot be immediately correlated with the stiffness of the spring. Therefore, this correlation can be well established experimentally.

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4 Natural Vibration of the Suspended Mass on Air Spring In the following it is assumed to use a Firestone mod. 25 two-lobe spring (Fig. 5a), for which laboratory tests were carried out to evaluate its stiffness under different operating conditions, using an instrumented press able to measure the force impressed and the displacement between the end plates of the spring [12, 13].

Fig. 5. a) Firestone mod.25 air spring; b) Test on air spring

The tests were carried out by connecting the spring to a motor compressor equipped with a 24-L tank. The connection duct between the spring and the tank is equipped with a valve which can be closed, so that the air mass in the spring is constant, or open. By imposing a load cycle (Fig. 5b), the diagrams of Fig. 6 were so obtained; they show that the restoring force varies with the height of the spring and undergoes a jump at the end of each stroke due to the change of sign of the friction force in the press guides.

Fig. 6. Axial force vs spring height: a) valve fully opened; b) valve completely closed. Initial conditions: Fz = 1400 N, h = 140 mm, pressure indicated in the graph

The results obtained in the case of a fully opened valve (variable air mass) are shown in Fig. 7a for three different initial pressure values. In this case the pressure remains almost constant during the entire stroke. The two branches of each curve have a gradient which slightly varies with the spring height; the average value of the axial stiffness of the spring is: 12 N/mm @2 bar; 18 N/mm @3 bar; 27 N/mm @4 bar.

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The test was repeated with an initial pressure of 2 bar, with the valve closed (constant air mass); Fig. 7b shows the corresponding curve, compared with that obtained with the same initial pressure value but with the valve opened. In the case of constant air mass, the spring shows a progressive behavior; the stiffness increases with the spring height, varying continuously in the range of values 12–100 N/mm. The spring can operate in the 1–8 bar range; considering the possibility of regulating the volume of the auxiliary tank, it is therefore possible to obtain a sufficiently wide range of excitable frequencies. For example, adopting a Firestone mod.25 spring, with a suspended mass of 250 kg it is possible to have a frequency range of about 1.5-5.5 Hz, as represented in Fig. 7. In the same diagram, it is reported the transmitted force for a motion amplitude of 20 mm. The force can assume larger intensity for larger amplitude of the motion; to broaden the range of excitable frequencies, it would be possible to adopt air springs whose geometry allows a greater variation of stiffness as its height varies or through the adjustment of the suspended mass by adopting a rapid mass selection device similar to the one adopted for gym machines.

Fig. 7. Natural frequency and transmitted force vs spring stiffness k

5 Conclusions The paper evaluates the possibility of developing a vibration exciter to be used for the dynamic monitoring of large structures for which, in general, there is no contrast element to which an actuator can be fixed. The proposed vibrating system has the advantage of working in resonance conditions and therefore of requiring low power to excite vibrations along the vertical direction, compared to other types of excitation devices. By varying the air pressure, it is possible to adjust the stiffness of the system modifying the natural frequency and so the excitation frequency. Although the frequency may vary over a not very wide range of frequency values, it may be suitable for some types of structures which typically exhibit the first natural frequency in a narrow frequency range. The proposed solution is simple from a constructive point of view, as it does not require precision machining working but needs of a simple assembly of a welded frame with elements to be chosen from catalogues (spring, guides, sensors, etc.).

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Furthermore, the excitation system could be installed on a trailer, equipped with lifters, so as to be easily transported and positioned at the excitation point, without requiring fastening operations to the structure under test. Acknowledgments. The authors are grateful to Giuseppe Iovino, and Gennaro Stingo for their collaboration during the setup construction and the execution of laboratory tests.

References 1. Fujino, Y., et al.: Research and implementations of structural monitoring for bridges and buildings in Japan. Engineering 5(6), 1093–1119 (2019) 2. Jianga, Y., et al.: Knowledge driven approach for smart bridge maintenance using big data mining. Autom. Constr. 146 (2023) 3. Choi, S., et al.: Periodic monitoring of physical property changes in a concrete box-girder bridge. J. Sound Vibr. 278, 365–381 (2004) 4. Farrar, C.R., Worden, K.: An introduction to structural health monitoring. Philos. Trans. A (2006) 5. Zhang, X., et al.: Structure damage identification based on regularized ARMA time series model under environmental excitation. Vibration 1(1), 138–156 (2018) 6. Nichols, J.M.: Structural health monitoring of offshore structures using ambient excitation. Appl. Ocean Res. 25(3), 101–114 (2003) 7. Shabbir, F., Omenzetter, P.: Forced vibration testing of a thirteen-story concrete building. In: New Zealand Society for Earthquake Engineering Annual Conference (NZSEE), Wairakei, New Zealand (2008) 8. Diaferio, M., et al.: Identification of the modal properties of a squat historic tower for the tuning of a FE model. In: IOMAC 2015, 6th International Operational Modal Analysis Conference, Gijón, Spain, 12–14 May 2015 (2015) 9. Mangal, L., et al.: Structural monitoring of offshore platforms using impulse and relaxation response. Ocean Eng. 28(6), 689–705 (2001) 10. Adiletta, G., et al.: A twin rigid straight pipe Coriolis mass flowmeter. Measurement 11, 289–308 (1993) 11. Harris, C.M., Piersol, A.G.: Harris’ Shock and Vibration Handbook, 5th edn. McGraw-Hill (2002) 12. Di Massa, G., et al.: Cabinet and shelter vibration isolation: numerical and experimental investigation. Eng. Lett. 22(4), 149–157 (2014) 13. Di Massa, G., et al.: Stability analysis of air springs subjected to lateral loads. In: Proceedings of the World Congress on Engineering WCE 2017, 5–7 July 2017, pp. 970–975 (2017)

Low Cost 3D Printed Pneumatic Linear Actuator Daniela Maffiodo(B)

, Terenziano Raparelli , and Walter Incardona

Politecnico di Torino, Turin, Italy [email protected]

Abstract. 3D printing has become increasingly widespread in recent years, but a few pneumatic application were developed up to now. A linear pneumatic actuator was designed with the aim of obtaining a low cost actuator, almost completely 3D printed with biological or recyclable material and customized dimensions. Various prototypes were then printed with different materials and printing machines. Experimental tests on three prototype are here presented and compared. A final prototype with low leakage and good performance is finally presented, with PLA cylinder, piston and head and a net force of 40 N at 0,2 MPa of supply pressure. Keywords: SDG9 · Additive Manufacturing · Pneumatic Linear Actuator · 3D printing

1 Introduction The purpose of this project is to investigate the feasibility of creating a low cost doubleacting linear pneumatic actuator with non-traditional manufacturing methods, in particular with the aid of additive manufacturing. The choice falls on this technology since its diffusion of use in recent years has become increasingly widespread and the presence of a 3D printer (of any technological nature) in a studio, a laboratory, an operational headquarters is increasingly essential, which makes this project potentially replicable in any situation and environment. The advantages that would be obtained from an actuator thus constructed are many. First of all, the use of polymers instead of ferrous alloys introduces a series of possibilities not considered until now such as for example that of using this actuator in environments hostile to metals or in the presence of electromagnetic fields that interfere with ferromagnetic materials, e.g. the medical health field. For example [2] proposes the use of an actuator in polymeric material as a one-shot solution, i.e. its cycle of use is linked to a single operation at the end of which the piece is removed and suitably disposed of, making room for a new identical actuator just printed and that is not contaminated. Secondly, polymers generally have a lower specific weight than metals and therefore it is possible to obtain a much more interesting weight/power ratio. Moreover, it is crucial to underline that most of the polymers used in this project are derived from biological substances and are recyclable, such as PolyLactic Acid (PLA) and PolyEthylene Terephthalate Glycol (PETG). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 225–232, 2023. https://doi.org/10.1007/978-3-031-32439-0_26

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All of this is reasonably related to a matter of scale and power, it is legitimate to think that for a heavy-duty application, the use of polymers is certainly disadvantageous compared to metal. However, the idea that drove this project forward is to instill awareness that it is possible to replicate your own pneumatic linear actuator at home, completely customized according to your needs. Furthermore, we want to obtain a system that can be used once extracted from the machine with the least possible number of post-processes. In a very forward-looking vision, we want to be able to print the whole assembly in a single solution, without the need for subsequent assembly. Following an in-depth bibliographic search, little material on the subject was found and each of the studies concluded that there is still much to explore by proposing different starting points for experimentation. However, the choice of commercial pneumatic actuators is limited by the strong standardization of size, material and output power. This is exactly where the potential of 3D printing comes into play, which allows the instantaneous creation of complex geometries and the use of light and eco-sustainable materials. The major applications of 3D printing for pneumatic systems are found in the robotics field and mainly involves the use of flexible materials for the construction of the so-called soft actuators [7]. The flexible material allows the actuator to fully adapt to the object to be manipulated thus making the robot capable of handling objects that are profoundly different from each other or very delicate objects. On the other hand, attempts to create pneumatic linear actuators using additive manufacturing are not so common. In [3] Krause and Bhounsule performed a series of measurements on an actuator where the cylinder is molded in PLA, but the piston is a steel bar with the cylinder head fitted with a magnet. The actuator has a cylinder thickness of 1.15 mm and an internal diameter of 30 mm and a pressure of around 4 bar was used to carry out the measurements. In [1] Grgi´c et al. made a 3D printed pneumatic actuator to implement it in the grasping system in a 10 kN Shimadzu tensile testing machine for the characterization of muscle ligament tissues. The problem was that, with the original grips, the tissue was drastically torn, and the test also had to be conducted with the specimen immersed in a fluid. Taking advantage of 3D printing, a double-acting linear actuator was created that respects the dimensions of the machine, which can be immersed in fluid without corroding and which manages not to tear the tissues to be tested. Moreover, Nall and Bhousule [6] created a pneumatic cylinder molded in ABS with FDM technology. It is a very small size actuator, in fact the internal diameter is 15 mm and the piston performs a maximum stroke of 20 mm. The authors concluded that a 3D printed actuator combines the high performance of pneumatics with the lightness of polymers and the stiffness provided by metal elements suitably inserted into the different elements, thus providing the main characteristics that a linear actuator must have for robotic applications. In the project here presented we want to take the further step of obtaining a functioning system where each of its components is completely 3D printed with a low cost 3D printer machine, overwhelming the main problems for this goal that are the friction due to rough surface finish and the air leaks.

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2 Prototypes The choice was to create a very simple double-acting linear actuator, which can be completely made in low cost 3D printing. The designed linear actuator, shown in Fig. 1, has the following characteristics: bore 37 mm, stroke 72 mm, weight about 150 g. It consists of an external cylinder with one piece rear head (1), a piston (2) on which two sealing elements (3) are inserted. The head (8) is connected to the body by means of 4 M4 bolts (4) with the gaskets on the head cylinder (5) and head (6). Piston sealings (3) have a cross section with a C profile, so that the pressurized air pushes laps against the piston and against the cylinder, for greater efficiency.

Fig. 1. Side view and sectional view of the pneumatic linear actuator

A first design phase saw the creation of several prototypes (see Table 1) with different materials, including PolyEthylene Terephthalate Glycol (PETG), PolyLactic Acid (PLA), Nylon and two different 3D printing techniques, Selective Laser Sintering (SLS) and Fused Deposition Modeling (FDM). PLA is the most common in the world of 3D printing in desktop format; it is a polymer derived from corn starch, therefore of a biological nature; PETG is the same polymer used in plastic bottles, but with the addition of glycol to make the material more fluid and extrudable at high temperatures; NYLON is a polyamide, a polymer with excellent mechanical and anti-corrosive characteristics. Tetra polyurethane (TPU), an elastomer polymer with good properties which give it resistance to corrosion was used to print sealings of the piston. SLS machines methodically fire a laser to sinter the particles of a polymer-based powder to build parts layer-by-layer. FDM machines, on the other hand, melt and extrude a polymer filament through a nozzle, depositing it along a prescribed path to form parts layer-by-layer. The printing of the components required various preliminary evaluations. By way of example, some observations following this phase are reported (see Fig. 2).

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Prototype

Cylinder

Piston

Head

1

FDM, PETG

FDM, PETG

FDM, PETG

2

SLS, Nylon

SLS, Nylon

FDM, PETG

3

FDM, PETG

FDM, PLA

FDM, PETG

4

SLS, Nylon

SLS, Nylon

FDM, PETG

5

FDM, PLA

FDM, PLA

FDM, PLA

6

SLS, Nylon

SLS, Nylon

FDM, PLA – SLS, Nylon

7

SLS, Nylon

SLS, Nylon

FDM, PLA

8

FDM, PLA

FDM, PLA

FDM, PLA

Printing the piston in the vertical direction (layers along the axis of the piston itself) allows obtaining better dimensional tolerances, while printing in the horizontal direction (layers perpendicular to the axis of the piston) could give advantages in terms of mechanical resistance. The first solution was chosen as our goal was the assembly of the component without post-printing operations. Also for the cylinder printing, the best results in terms of geometric tolerances are obtained with vertical printing, with layers deposited along the axis of the cylinder and, to avoid generating a layer start line which would cause loss of air, a machine setting was used which causes each layer to start from a random position with respect to the previous one. Furthermore, the work is set up so that the thickness of the wall is created by means of concentric circumferences which overlap each other (overlap) to obtain high radial compactness and to avoid leaks when the cylinder is placed in pressure.

Fig. 2. Technological solutions: from left to right each layer starting from the same point; each layer starts from a different point; PETG cylinder with threaded metal insert, PETG piston with TPU sealings

Finally, three prototypes (3, 5 and 8, see Fig. 3) were chosen for the measurement phase. These prototypes are all made using the FDM technique, chosen because it is

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more widespread and cheaper; moreover each 3D printed part of these prototypes do not underwent any post processing treatment. Piston sealings are made of TPU 85A. Prototype (3) has the cylinder and its head in PETG, while piston is made of PLA. Sealings on the head of the cylinder and the scraper gasket are made of TPU 85A. Prototype (5) is completely made of PLA, with O-ring sealings at the head of the cylinder and scraper gasket. Prototype (8) is the same of (2), but the front head has the seat for two O rings, unlike the (2) which has only one, for a better guide of the rod and a better performance of the actuator.

Fig. 3. Some of the realized prototypes (from left to right: prototype 3, 5 and 8)

A Fem analysis of the model was carried out to have an estimation of the resistance of the prototype (Fig. 4). In order to conduct a numerical simulation on the model, it is first of all necessary to know the material characteristics [4, 8]. The components made with 3D printing are, by their nature, non-continuous bodies and more or less isotropic based on the technology used. Numerous parameters influence the behavior of the molded parts: technology, material, process parameters, printing direction. Yu et al., [5] carried out a research to analyze the mechanical properties of specimens made of PLA with FDM printing by evaluating the influence of 6 different parameters on the tensile and compression test. Based on the results obtained from these, the study was conducted, obtaining a safety coefficient equal to 1.8 in the whole range of normal supply pressures ( 1. The multiplying coefficient ensures the avoidance of the singularities in the dexterous workspace as a result of imposing the synthesized five-bar linkage 5-RPRPR to reach all the points inside the imposed workspace while avoiding the folded and elongated configurations.

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The substituted equation system is: s03 + h3max

 2 = k · (xM 3 + l1 /2)2 + yM 3

(11)

k · s03 = yM 1

(12)

k · l1 = 2 · s03

(13)

s03 = yM 1 /k,

(14)

2 · s03 , k

(15)

with the solutions:

l1 =  h3max = k ·

  l1 2 2 −s . xM 3 + + yM 03 3 2

(16)

The similar parameters s04 and h4max of the second loop can be computed with the corresponding relationships (14) and (16).

4 Singularities Analysis of the Five-Bar Linkage 5-RPRPR Let us consider the matrix equation of the five-bar linkage 5-RPRPR expressed as: ˙ + Jx · X˙ = 0 Jq · Q

(17)

˙ = [˙s3 s˙4 ]T , ˙ = [˙xM y˙ M ]T , Q X

(18)

X = [xM yM ]T , Q = [s3 s4 ]T .

(19)

with:

where:

The values of the determinant of the inverse kinematic Jacobian matrices Jq with the values zero give the singularities of type I, which shows the positions where the mobile platform does not move inside the dexterous workspace by actuation of the drive elements [14–16]:   (X ,Q) ∂F3 (X ,Q)     ∂F3∂s  ∂s 3 4 (20) det Jq =  ∂F4 (X ,Q) ∂F4 (X ,Q)  = 0,   ∂s ∂s 3

4

where: ∂F3 (X , Q) ∂F3 (X , Q) = −2 · (s03 + s3 ), = 0, ∂s3 ∂s4

(21)

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∂F4 (X , Q) ∂F4 (X , Q) = 0, = −2 · (s04 + s4 ). ∂s3 ∂s4 By replacing (21) and (22) in (20), results the following equation:   det Jq = 4 · (s03 + s3 ) · (s04 + s4 ) = 0

(22)

(23)

By considering that s03 + s3 and s04 + s4 , the total stroke length of both prismatic actuators are positive real values, the value of the determinant of the inverse kinematic Jacobian matrices Jq is never 0, resulting that the reachable workspace is free from singularities of type I. The determinant values of the direct kinematic Jacobian matrices Jx with the values zero give the singularities of type II, when non-actuated drives allow an infinitesimal motion of the mobile platform inside the dexterous workspace:    ∂F3 (X ,Q) ∂F3 (X ,Q)    ∂xM (24) det(Jx ) =  ∂F4 (X ,Q) ∂F4∂y(XM,Q)  = 0,   ∂x ∂y M

M

where: ∂F3 (X , Q) ∂F3 (X , Q) = 2 · xM + l1 , = 2 · yM , ∂xM ∂yM

(25)

∂F4 (X , Q) ∂F4 (X , Q) = 2 · xM − l1 , = 2 · yM . ∂xM ∂yM

(26)

By replacing (26) and (25) in (24), results the following equation: det(Jx ) = 4 · yM · l1 = 0.

(27)

But considering that l1 , the distance between the centers of the two fixed revolute joints id non-zero, the value of the determinant of the inverse kinematic Jacobian matrices Jq is 0 only for position of the characteristic point where the yM coordinate is 0, resulting that the reachable workspace is free from singularities of type II completely above or below the X axis.

5 Numerical Example The chosen numerical example gives the results of the proposed analytical synthesis for the five-bar linkage 5-RPRPR. The considered dexterous workspace is a square with the corner points coordinates M1 , M2 , M3 and M4 given in the Table 1: The parameters computed with the relationships (14), (15) and (16) for a multiplier coefficient k = 1.3 are given in the Table 2. Figure 3 shows the five-bar linkage 5-RPRPR with the computed parameters in the three considered critical positions. The links of the linkage do not allow extended or folded positions in the critical positions, that means the five-bar linkage does not show any singularities in the above-mentioned positions. All other positions inside of the dexterous workspace are singularities-free positions.

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Table 1. Coordinates of the square corner points of the dexterous workspace Corner point

xM [mm]

yM [mm]

M1

−100

130

M2

100

130

M3

100

330

M4

−100

330

Table 2. Computed parameters of the five-bar linkage 5-RPRPR Number of the link

Symbol

Length [mm]

1

l1

154

3

s03

100

3

h3max

274

4

s04

100

5

h4max

487

M4

C=M3

y C=M i M1

C=M 0

A0 2

M2

E0 1

l1

5

x 4

3

Fig. 3. Computed five-bar linkage 5-RPRPR in the three critical positions

The analytical method for verifying the singularities in the dexterous workspace involve the computation of the direct and inverse kinematic Jacobian matrix determinants of the synthetized five-bar linkage as presented in the following flowchart diagram (Fig. 4).

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Fig. 4. Flowchart diagram used for the implementation of the validation process

By implementing the previous validation process, the following results for the determinants of the Jacobian matrices were obtained:

  Fig. 5. Values of det Jq for the synthetized five-bar linkage 5-RPRPR

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Fig. 6. Values of det(Jx ) for the synthetized five-bar linkage 5-RPRPR

5 shows that the type I singularities are avoided, because all the values of  Figure det Jq are positive non-zero values inside the imposed workspace. In Fig. 6 is shown, that the singularities of type II are present among the X axis of the cartesian coordinate system as presented in Eq. (27).  Figure 5b and Fig. 6b illustrate the values of det Jq and det(Jx ) inside the imposed workspace used in the synthesis of the five-bar linkage and by observing that all values are non-zero values it can be concluded that the imposed workspace is dexterous.

6 Conclusions The paper shows the direct and inverse kinematic relationships and the analytical synthesis method for a five-bar linkage with the structure 5-RPRPR in order to avoid singularities in the imposed dexterous workspace inside of the total workspace. The synthesis method is verified in two ways by considered a numerical example. The computed parameters allow the graphical representation on scale of the five-bar linkage in the critical positions, where it is shown that the elements are not folded or extended. Also, by computing the direct and inverse kinematic Jacobian matrix determinants it is found that, the values are different from zero, which means the whole dexterous workspace is singularities of type I and II free. The five-bar linkage 5-RPRPR is suitable to be used for 3D-printing, pick-and-place operations, engraving etc.

References 1. Tempea, I., Neac¸sa, M., Livadariu, A.: A new acting solution of a double SCARA robot. In: Proceedings of the 3rd International Conference on “Computational Mechanics and Virtual Engineering”, COMEC 2009, Brasov, pp. 765–770 (2009) 2. Campos, L., Bourbonnais, F., Bonev, I.A., Bigras, P.: Development of a five-bar parallel robot with large workspace. In: Proceedings of the ASME 2010 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2010, Montreal, Quebec, pp. 917–922 (2010)

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3. Tsetserukou, D., Hosokawa, S., Terashima, K.: LinkTouch: a wearable haptic device with five-bar linkage mechanism for presentation of Two-DOF force feedback at the fingerpad. In: Proceedings of IEEE Haptics Symposium 2014, Houston, pp. 307–312 (2014) 4. Marzouk, W.W., Ahmed, A.R.: Analytical model for novel design of five-bar polycentric knee joint. In: Proceedings of Conference: International Conference on Pure and Applied Sciences (ICPAS 2015) Luxor, pp. 1–13 (2015) 5. Sun, K., Ge, R., Li, T., Wang, J.: Design and analysis of vegetable transplanter based on five-bar mechanism. IOP Conf. Ser.: Mater. Sci. Eng. 692, 012029 (2019) 6. Jian, S.: The research of five-bar robot for pressurized autosampling for enhanced oil recovery research. Master degree thesis, St. John’s, Newfoundland, Canada (2016) 7. Kiper, G., Dede, M.I.C., Uzunoglu, E., Mastar, E.: Use of hidden robot concept for calibration of an over-constrained mechanism. In: The 14-th World Congress, Taipei Taiwan (2015). https://doi.org/10.6567/IFToMM.14TH.WC.OS13.095 8. Tivadar, D., et al.: Design of the symmetrical five-bar linkage 5-RRRRR(a). Robotica (2023, in press) 9. Alici, G.: Determination of singularity contours for five-bar planar parallel manipulators. Robotica 18(6), 569–575 (2000) 10. Alici, G.: An inverse position analysis of five-bar planar parallel manipulators. Robotica 20, 195–201 (2002) 11. Zhou, H., Ting, K.-L.: Path generation with singularity avoidance for five-bar slider-crank parallel manipulators. Mech. Mach. Theory 40, 371–384 (2005) 12. Fallahi, B., Lai, H.Y., Naghibi, R., Wang, Y.: A study of the workspace of five-bar closed loop manipulator. Mech. Mach. Theory 29(5), 759–765 (1994) 13. Luck, K., Modler, K.-H.: Getriebetechnik, Analyse - Synthese - Optimierung, AkademieVerlag, Berlin (1990) 14. Gosselin, C., Angeles, J.: Singularity analysis of closed-loop kinematic chains. IEEE Trans. Robot. Autom. 6(3), 281–290 (1990) 15. Oarcea, A., Luputi, A.M.F., Cobilean, V., Stan, S.-D., Lovasz, E.-C.: Kinematic performance analysis of a 3-R(RPRGR)RR planar parallel robot. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 461–470. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-87383-7_50 16. Demjen, T., Lovasz, E.-C., Ceccarelli, M., Sticlaru, C., Lupu¸ti, A.-M.-F.: Analytical synthesis of five-bar linkage used for 3D printer structure. In: Vicenzo, N., Gasparetto, A., Quaglia, G., Carbone, G. (eds.) IFToMM Italy 2022. MMS, vol. 122, pp. 105–113. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-10776-4_13

Technical Developments for Sustainable Engineering

An Automatic Measurement System for Shape Memory Alloys’ Wire Resistivity Characterization Marco Siciliano1 , Francesco Lamonaca1 , Domenico Luca Carn`ı1 , Stefano Rodin` o2 , Elio Matteo Curcio2 , Giuseppe Carbone2(B) , Domenico Mundo2 , and Carmine Maletta2 1

DIMES University of Calabria, Arcavacata, Italy [email protected] 2 DIMEG University of Calabria, Arcavacata, Italy {stefano.rodino,giuseppe.carbone}@unical.it

Abstract. Nowadays, Shape Memory Alloy (SMA) wires are commonly used in industrial, medical, research fields. Recently they are used also for sensing, an accurate model for their behaviour in different operative condition is missing. To fulfill this lack, this work proposes an automatic measurement system for SMA wires characterization. In particular, the variation of the wire resistivity is evaluated during heating and cooling cycles achieved by the Joule effect. This achievement positively impacts on the sustainable development goal (SDG) 9. Keywords: SMA SDG9

1

· Shape Memory Alloy · NiTiNOL · Resistivity ·

Introduction

Shape Memory Alloys are metallic materials able to return to a predetermined shape provided through a thermal treatment [1]. This property is known as shape memory effect and consists on heating the material above a specific temperature known as transformation temperature. This behavior depends on the thermo-elastic martensitic transition which implies the existence of austenitic phase (A) at high temperatures and martensitic (M) at low temperatures. These temperature values mainly depends on the applied stress and they are known as martensite start/finish and austenite start/finish. SMAs have attracted significant attention, both in the scientific and commercial sector. In applications including aerospace [2,3], robotics [4,5] and constructions [6], as well as biomedical applications [7]. In particular, SMA appear very promising for developing smart airless tyres and for improving the rolling resistance performance or the passengers comfort. SMAs can be also used as replacement of traditional c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 253–261, 2023. https://doi.org/10.1007/978-3-031-32439-0_29

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linear actuators, by providing a joule heating activation using a suitable amount of electrical current. One of the recent challenges is using SMAs for sensing, i.e. to monitor their deformation through the measurement of their resistance at known conditions. In this context, self-sensing resistance techniques are particularly promising [8–12]. These techniques allow to evaluate the resistance of a SMA during use. For example, a feedback circuit can be used to maintain the deformation of the material at a predetermined value statically or in autonomous cyclic movement [13,14]. However, to make the sensing possible it is necessary an accurate model of the SMA wire behaviour and the literature shows a lack in the automatic measurement systems for the SMA wires characterization. In order to fill this lack, a suitable measurement system for the characterization the SMA wire resistance during the thermo-elastic martensitic transition is proposed.

2

Design Requirements and Specifications

The material used during the experimental characterization is a NiTi alloy purchased from SAES Getters Company. For our purpose a NiTi wire with a diameter of 480 µm from the SmartFlex series has been chosen [15]. The requirements of the characterization come from the existing standards ASTM F2516 [16], ASTM F2082 [17], ASTM F2004 [18] and from several analyzed papers such as Table 1. Resolution and accuracy of the measurement involved parameters Parameter

Expected value

Desired resolution (r) and accuracy (a)

Notes

wire length (Δ l)

10 cm ± 3%

r = 0.1 mm a = ± 0.1 mm

Parameters declared by the manufacturer, as stated by the product datasheet [15] (SAES Getters Smartflex NiTiNOL 480 µm

Environmental temperature TEnv

20–24 ◦ C

r = 0.1 ◦ C a = ±0.1 ◦ C

As stated by the ASTM F2516 [16] standard, the room temperature during the test shall be 22.0 ±2.0 ◦ C

Sample Temperature TSample

20–150 ◦ C

r = 0.1 ◦ C a = ± 0.1 ◦ C

As stated by the ASTM F2082 standard [17], any thermocouple and indicator with resolution of 0.1 ◦ C or better must be used to measure the temperature of the specimen. ASTM F2004 standard [18] must be also considered when conducing calorimetry tests

Hanging Mass

14.30 to 5314.5 g r = 1 g a = ±1 g

Electrical Resistance

Around 100 mΩ

r = 0.01 mΩ a = ±0.01 mΩ

As declared by the manufacturer in [15], the wire resistivity can range from 85 µΩcm up to 105 µΩcm. Moreover, similar values can be found in the literature. Expected resistance magnitude in the order of mΩ for a wire sample of some centimeters [24]

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[19,20]. Since the ASTM F2516 provides the guidelines for conducting a standard tensile test method for NiTi super elastic materials and both ASTMF 2082 and F2004 provide specifications for the determination of transformation temperature, the experimental tests are conducted following these standards while considering that there is no specific standard for the electrical characterization of SMA wires. The most significant requirement comes from the ASTM F2004, which suggests the control of the heating and cooling procedure during the whole duration of the test. Table 1 reports a summary of all the specifications taken into account during the design phase of the automatic measurement system.

3 3.1

Measurement System Design Existing Methods and Instrumentation

A multitude of systems for resistivity measure and/or resistance of SMA wires have been analyzed, with the aim to evaluate critical points and necessary improvements. Some examples are the systems proposed in [21–23]. Abdullah et al. [21] used a metal frame to keep the SMA wire in place and horizontally oriented, the wire is loaded by weights through the aid of some pulleys. The proposed setup in Fig. 1a, is intended to mainly measure the wire length variation but the authors also retrieved the voltage measurements during the speciment elongation. Another similar setup is the one schematized in Fig. 1b proposed by Song et al. [22], it is another horizontal setup using pulleys to apply the mechanical load to the wire. The resistance values are collected during the heating phase only. A third example of measuring method is the one schematized in Fig. 1c, proposed by Antonucci et al. [23], where the wire is placed inside a thermostatic chamber used for cooling and heating the sample at a constant rate (Table 2).

Fig. 1. (a) Abdullah et al., (b) Song et al. and (c) Antonucci et al.

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M. Siciliano et al. Table 2. Comparison table

Existing Setup

Voltage/Current Measure

Abdullah al.

et cDAQ 9174 Data Acquisition System, using a NI 9201 managed by LabVIEW

Song et al.

Temperature sure

Mea- Additional Info

Thermocouple connected to NI 9213 module for data collection.

Further information retrieved from datasheet: 8-channel acquisition board with a 12-Bit resolution. ADC resolution of 12 bits. Typical accuracy (when T = TEnv ) of ± (0.04% of reading + 0.07% of range)

Wheatstone bridge Thermocouple and Quanser MultiQ PCI data acquisition interface

Wire activation by PWM current pulse. Any further information regarding the Wheatstone bridge realization are not reported in the Paper

Antonucci et Custom 4 probes set- Thermocouple al. up.

Wire supply 478 µA + 0.1% through self-built generator, temperature variation less than 0.1 ◦ C. Data acquisition by NI DAQPAD 6052E and LabVIEW. Absolute accuracy at full scale of 20V equal to ±4.737 mV and up to ±0.059 mV with a full scale of 10 mV

3.2

Proposed Measurement System

The proposed system allows to carry out several heating and cooling cycles of the wire by the Joule effect, simultaneously measuring the variation of the wire resistivity. The system is composed by a Keithley 2002 multimeter, an Agilent E3631A power supply, a GW Instek GDM9061 multimeter, a Flir E60 thermal camera and a Keysight E5810B LAN/GPIB/USB gateway. The Keithley 2002 multimeter is used to measure SMA wire voltage, the Instek multimeter is used to measure the current across the SMA wire, the thermal camera is responsible for the contact-less measurement of the temperature and the Agilent programmable power supply is responsible for the control of the current used to heat the wire. The Keysight gateway is instead necessary in order to link the two GPIB instruments (Keithley multimeter and Agilent power supply) on the system network. The wiring of the system is described in Fig. 2b.

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Fig. 2. Experimental setup (a), Experimental setup schematic (b)

Fig. 3. Voltmeter-Ammeter method schematic (a) Voltmeter-Ammeter method implementation on the experimental setup (b)

3.3

Data Acquisition and Processing

Because the resistance value offered by the wire is small and the temperature of the wire needs to be modified through the control of the current, the most suitable measurement method is the Voltmeter-Ammeter method, which is schematized in Fig. 3. Using the Voltmeter-Ammeter method, the resistance is evaluated on the basis of the measurement of the voltage VR on the unknown resistance Rx and the current IR flowing through it. In particular, the resistance is evaluated using the Ohm’s law: VR (1) Rx = IR Once the resistance Rx is evaluated, the resistivity can be expressed through the Eq. 2. Where l is the specimen length measured between the two points of measure and S is the specimen section. ρ = Rx

S l

(2)

In fact, the resistance Rx is now known, and the length l is fixed by imposing a fixed distance between the two probes. The section S of the wire is instead considered constant because its variations are negligible.

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The management of the entire system, which is able to perform multiple measurement cycles comprehensive of the management of the heating and cooling of the wire, is done by means of a specially built software platform in the LabView development environment. The realized VI, which is schematized in Fig. 4, includes a first section dedicated to setting up the instruments, followed by enabling the power supply and performing an initial temperature acquisition, which is necessary to acquire the starting temperature of the wire. A second section of the VI is demanded to managing the sample heating phase, taking temperature, voltage and current measurements, and evaluating resistance. Next is a section similar to the second, but dedicated this time to the cooling phase of the sample.

Fig. 4. Block diagram of the working principle

4

Results

The SMA wire resistance was measured according to the specified parameters, and multiple tests were conducted on different wire samples to ensure experiment repeatability. Tests were conducted with an applied stress of σ = 11 MPa, a probe distance of 38 mm, and a constant wire diameter of 0.181 mm2 . Each test consisted of 10 measurement cycles, with 180 points acquired during each heating and cooling phase. The number of acquisition points was set at 180 to calculate current steps during heating and cooling, which were determined by the maximum current value divided by the number of acquisitions. After several

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Fig. 5. (a) Temperature variations of the specimen heated by using different maximum values of the electrical current,(b) resistance-temperature plot of SMA wire over 10 activation cycles (c), resistance-temperature plot of the 10th activation cycle and (d) resistivity values calculated on the basis of the 10th cycle

tests, a maximum current of 1.8 A was chosen, which can bring the wire temperature up to about 150 ◦ C and complete the phase transformation even under high applied stress (Fig. 5a). The change in resistivity and resistance mainly depends on the volumetric fraction of austenite and martensite, and the value of the electrical resistance measured during the 10th activation cycle is shown in Fig. 5b. The experimental tests have been carried out multiple times with mostly identical results that demonstrate a high repeatability of the proposed procedure. In Fig. 5d, resistivity is calculated using Eq. 2, with the values of electrical resistance Rx taken from the 10th activation cycle in Fig. 5c. Figure 5d shows the resistivity variations, indicating that the material has resistivity values of ρM = 93 µΩcm for martensite and ρA = 78 µΩcm for austenite. These values can be compared with the resistivity values reported by the manufacturer in [15] to validate the proposed setup and methodology.

5

Conclusions

This paper proposes an automatic measuring system for characterizing the physical characteristics of Shape Memory Alloy (SMA) materials, with a focus on SMA wires. The system incorporates a power supply, two multimeters, and a thermal camera, enabling the characterization of wire resistance at different working

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temperatures while minimizing contact effects of probes. To ensure the system’s accuracy, relevant standards, recent literature, and existing techniques were considered during development. Several heating and cooling cycles were conducted using the Joule effect to measure the variations in influence quantities involved in the measurement process. The results confirm existing literature for similar materials and provide insight into resistivity variation during the martensitic phase transition. Future work aims to evaluate the effect of different mechanical stress levels on electrical resistivity. Acknowledgements. This work was supported by the project “FASTire (Foam Airless Spoked Tire): Smart Airless Tyres for Extremely-Low Rolling Resistance and Superior Passengers Comfort” funded by the Italian MIUR “Progetti di Ricerca di Rilevante Interesse Nazionale (PRIN) call 2017 - grant 2017948FEN.

References 1. Lagoudas, D.C.: Shape Memory Alloys: Modeling and Engineering Applications. Springer, New York (2008). https://doi.org/10.1007/978-0-387-47685-8 2. Bellini, A., Colli, M., Dragoni, E.: Mechatronic design of a shape memory alloy actuator for automotive tumble flaps: a case study. IEEE Trans. Ind. Electron. 56(7), 2644–2656 (2009) 3. Hartl, D., Lagoudas, D.: Aerospace applications of shape memory alloys. Proc. Inst. Mech. Eng. Part G J. Aerosp. Eng. 221(4), 535 (2007) 4. Amalraj, J.J., Bhattacharyya, A., Amalraj, J.J., Faulkner, M.G.: Finite-element modeling of phase transformation in shape memory alloy wires with variable material properties. Smart Mater. Struct. 9(5), 622–631 (2000) 5. Zhang, J., Cong, M., Liu, D., Du, Y., Ma, H.: A lightweight variable stiffness knee exoskeleton driven by shape memory alloy. Ind. Robot. 49(5), 994–1007 (2022) 6. Wilson, J., Wesolowsky, M.: Shape memory alloys for seismic response modification: a state-of-the-art review. Earthq. Spectra 21, 569 (2005) 7. Duerig, T., Pelton, A., St¨ ockel, D.: An overview of nitinol medical applications. Mater. Sci. Eng., A 273, 149–160 (1999) 8. Guan, J.-H., Pei, Y.-C., Wu, J.-T., Wang, B.-H., Sui, W.-C., Li, S.-R.: A selfsensing and robust resistance phase transition detection method for the displacement estimation of shape memory alloy wires. Mech. Syst. Signal Process. 170, 108862 (2022) 9. Pei, Y.C., Wang, B.H., Wu, J.T., Wang, C., Guan, J.H., Lu, H.: A machine learning empowered shape memory alloy gripper with displacement-force-stiffness selfsensing. IEEE Trans. Ind. Electron. (2022) 10. Stano, G., et al.: One-shot additive manufacturing of robotic finger with embedded sensing and actuation. Int. J. Adv. Manuf. Technol. 124(1–2), 467–485 (2022) 11. Maffiodo, D., Raparelli, T.: Resistance feedback of a shape memory alloy wire. In: Borangiu, T. (ed.) Advances in Robot Design and Intelligent Control. AISC, vol. 371, pp. 97–104. Springer, Cham (2016). https://doi.org/10.1007/978-3-31921290-6 10 12. Raparelli, T., Zobel, P.B., Durante, F.: SMA-wire position control with electrical resistance feedback. In: Proceedings 3rd World Conference on Structural Control, pp. 391–398 (2002). ISBN 0-471-48980-8

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13. Lee, S.H., Kim, S.W.: Self-sensing-based deflection control of carbon fibrereinforced polymer (CFRP)-based shape memory alloy hybrid composite beams. Compos. Struct. 251, 112544 (2020) ´ et al.: Position control of a shape memory alloy actuator using a 14. Villoslada, A., four-term bilinear PID controller. Sens. Actuators A: Phys. 236, 257–272 (2015) 15. Smartflex brochure. https://www.saesgetters.com/sites/default/files/brochures/ pdf/BROCHURE%20SMARTFLEX 2020.pdf. Accessed 17 Nov 2022 16. ASTM F2516, 2022 Edition, June 1, 2022 - Standard Test Method for Tension Testing of Nickel-Titanium Superelastic Materials 17. ASTM F2082, 2015 Edition, May 1, 2015 - Standard Test Method for Determination of Transformation Temperature of Nickel- Titanium Shape Memory Alloys by Bend and Free Recovery 18. ASTM F2004, 2017 Edition, October 1, 2017 - Standard Test Method for Transformation Temperature of Nickel-Titanium Alloys by Thermal Analysis 19. Mohan, S., Banerjee, A.: Modelling of minor hysteresis loop of shape memory alloy wire actuator and its application in self-sensing. Smart Mater. Struct. 30(5), 055011 (2021) 20. Rizzello, G., Mandolino, M.A., Schmidt, M., Naso, D., Seelecke, S.: An accurate dynamic model for polycrystalline shape memory alloy wire actuators and sensors. Smart Mater. Struct. 28(2), 025020 (2019) 21. Abdullah, E.J., Soriano, J., de Bastida, F., Garrido, I., Abdul Majid, D.L.: Accurate position control of shape memory alloy actuation using displacement feedback and self-sensing system. Microsyst. Technol. 27(7), 2553–2566 (2021) 22. Song, H., Kubica, E., Gorbet, R.: Resistance modelling of SMA wire actuators. In: International Workshop Smart Materials Structures & NDT in Aerospace, pp. 2–4 (2011) 23. Antonucci, V., Faiella, G., Giordano, M., Mennella, F., Nicolais, L.: Electrical resistivity study and characterization-during NiTi phase transformations. Thermochimica Acta 462(1–2), 64–69 (2007) 24. Bhargaw, H.N., Ahmed, M., Sinha, P.: Thermo-electric behaviour of NiTi shape memory alloy. Trans. Nonferrous Met. Soc. China 23(8), 2329–2335 (2013)

Fault Detection in Induction Machines of Air Handling Units Christian Saab and Bechara Nehme(B) Electrical and Electronics, Telecommunication, and Computer Engineering Department, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon [email protected]

Abstract. Air Handling Units (AHU) are considered one of the main parts of the HVAC (Heating Ventilation and Air Conditioning) system. They are commonly used in residential, commercial, health care, and industrial buildings. Systems related to health care units must be applied for an intensive type of maintenance to avoid sudden shutdowns and exposing the patient to serious health issues. For that, we present in this paper a predictive maintenance system to monitor and predict faults that might occur in the induction machines of the AHU. The two main features that we focused on were the misalignment and the looseness faults. Experiments were conducted using a vibration sensor and a temperature sensor. Vibration amplitude and frequency were recorded and analyzed. The Fast Fourier Transform (FFT) was applied. Experimental results show that we can detect misalignment and the looseness faults that occurs to machines. Ensuring reliable hospitals supports good health and well-being SDG. In addition, the solution developed in this paper can be deployed in industry for a more reliable technology. Keywords: SDG3 · SDG9 · Air Handling Units · Fault Detection · Vibration Analysis · Fast Fourier Transform · Predictive Maintenance

1 Introduction At hospitals, managers primarily focus on the operation theatre where mistakes are not allowed to occur especially when it is in occupied mode. They are classified as positive pressure zones, since they are at a higher pressure level then the surrounding. This ensures that the air entering this zone through supply ducts won’t be kept inside the room or even circulate back in, this relies on the rate of air change per hour. Any pollutant particle or germ spread into the zone will be exhausted out through return ducts to ensure the comfort and safety needs of patients against infections and disease during or after the surgery [1]. One of the major technological advancements that have been applied to the AHUs is the variable-speed drive. In the past, HVAC systems had only two optional speeds where fans could be activated at the full speed or shutten down completely by direct online control (DOL). Because of that, their performance was limited. To solve this problem, variable frequency drivers (VFDs) where used to adjust the exhaust and the fresh air © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 262–269, 2023. https://doi.org/10.1007/978-3-031-32439-0_30

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fans speed to meet the required air change flow per hour and the desired room pressure [2]. For a long time, preventative maintenance has been used in industrial applications to maintain the strength and robustness of the induction machine. This kind of maintenance overcomes with higher budgets to cover the maintenance staff service and the changed equipment. It was also reported in the literature that 90% of the induction machines are overserviced, and most of the parts have been changed even if they may last longer or were in a healthy condition [3]. In [4] Fardin et al. detected bearing faults by analyzing the Instantaneous Frequency of Motor Control, since impulsive forces can be generated due to improper bearings. These forces are generated in the rotor magnetic field that is affected by the angular speed of the rotor and the current frequency of the bars. The global kurtosis and crest factor of the voltage are used to detect bearing faults. In [5] Nipuna et al. recorded acoustic sounds of induction machines. Different features from the recorded signals were used: Mean, Variance, RMS, Peak Value, Skewness, Kurtosis, Shape Factor, Impulse Factor, Crest Factor and Clearance Factor, Cepstrum and Fast Fourier Transform (FFT). Supervised Machine learning algorithms were used: Support Vector Machine (SVM), K-Nearest Neighbour (KNN), and Linear Discriminant Analysis (LDA) showed the best results. In [6] Bechara et al. developed a regression model to detect faults that can occur to PV panels. Faults were classified as increase in the series resistance, decrease in the shunt resistance, and bridging inside PV modules. Applying the findings of this paper will help contribute in the SDG3 targeting Good Health and Well-Being. In fact, it ensures a reliable operation of operation rooms. In addition, it contributes to SDG9 targeting Industry, Innovation, and Infrastructure. In reality, predictive maintenance is crucial for industry development an innovation. Using predictive maintenance lower the expenses that the owner pays for unnecessary replacement parts or excessive services applied by the maintenance team. In this paper we will start by detailing the experimental set used to detect misalignment and the looseness faults that occurs to machines in Sect. 2. Then we will extract boundaries and thresholds from experiments and results in Sect. 3. At the end we will explain the Fault detection algorithm in Sect. 4.

2 Experimental Set When it comes to industrial environments, motors are often used everywhere. Keeping it running at its peak performance is a huge challenge due to its complex technicality. Generally, motor failure would be usually caused by winding insulators or bearing problems. They arise after many different reasons related to both mechanical and electrical features. According to some industrial manufacturers, i.e. Fluke company [7], different causes arise in motor failure, and they are mostly related to transient voltage, voltage imbalance, harmonic distortion, reflections on drive output pulse width modulation (PWM) signals, sigma current, operational overloads, misalignment, shaft imbalance, shaft looseness, bearing wear, soft foot, external stresses, and shaft voltage. Delorenzo DL 30115 is an induction machines with a power of 370 W, It can be connected in Delta or Y and can operate at a voltage of 220 V, 50 Hz. Throughout the

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experimental tests, the induction machine was monitored by acquiring a single vibration signal coming from an accelerometer that was mounted on the motor carter. We consider the single measurement method as able to properly monitor the electric motor under investigation. To do that, accelerations were determined by using the GY-87 sensor. The sensor was mounted as shown in Fig. 1. Misalignment and the looseness faults will lead to different vibration of the machine since it is not well mounted. The MAX6675 thermocouple was also used to record temperature. Reading the temperature in addition to the vibration could be also taken into consideration by monitoring the health of the industry machinery. The GY-87 Arduino module chipset supports the I2C communication bus. The chipset was configured at the full g-force scale of 16 g. The Arduino IDE was used to write the configuration code for the GY-68 and the MAX6675 thermocouple. It was also used to analyze the data and plot it at the same time.

Fig. 1. Delorenzo DL 30115 induction machine and the GY-87 Sensor Installation.

Two methods of analyses were used to determine three different states that arises in the machine related to misalignment, looseness, and well condition. – Vibration Limits: In the industrial plants’ induction machines are classified into classes according to their rated power. Each of these classes has a definite vibration limit according to ISO 10816 and ADASH limits. So, by doing several tests on the machinery we will be able to identify the maximum and the minimum vibration limits that could be detected for each of the different faults. – Spectrum analysis: When applying the FFT to the signal a list of signals will appear in the complex form each corresponding to its frequency index. So, the first signal

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will correspond to the zero frequency and the last one will correspond to the sampling frequency.

3 Experiments and Results After applying several tests to the equipment set, we had successfully generated our own vibration and FFT limits related to the DL 30115 machine. During the first experiment, the machine operates with normal conditions. Recordings of the vibration and the temperature were made. Then we added the nominal load of the machine with proper alignment. At a later stage we applied a misalignment between the shafts of the motor and the load as shown in Fig. 2 (a). And the last experiment was applied with a looseness condition on the screws of the chassis of the motor as shown in Fig. 2 (b).

Fig. 2. Machine experimentation in (a) misalignment condition and (b) looseness condition.

The findings were reported in Table 1 for the vibration. In fact, we are interested in the amplitude of the vibrations for that we reported the maximum and minimum values for each axis. Minimum values are negative because the machine is vibrating in both directions. For that, later on we will have to use the absolute value of these amplitudes. We apply the FFT of the recorded values and we report the two maximum peaks and their frequencies in Table 2. As we can see in the reported results, peaks are happening for the same frequency for a given condition. The FFT spectrum can be checked visually. In Fig. 3 we represent the FFT of the normal condition. We can see peaks around the 9 Hz and the 20 Hz frequencies.

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Normal Condition With load

Misalignment condition

Looseness Condition

MaxACCX

0.09

1.22

1.39

2.92

MaxACCY

0.09

1.1

0.97

1.62

MaxACCZ

0.19

0.77

1.14

4.15

MinACCX

−0.12

−1.02

−1.23

−2.33

MinACCY

−0.09

−0.76

−0.76

−3.13

MinACCZ

−0.15

−0.68

−1.08

−2.32

Table 2. Highest peak values and their corresponding frequency (Value/Frequency) for the FFT of vibration records in g-force/Hz. Normal Condition

Normal Condition With load

Misalignment condition

Looseness Condition

X1

6.22/9.02

75.10/9.75

63.44/2.89

204.54/9.75

X2

6.22/20.23

75.10/19.49

107.18/29.20

204.54/19.49

Y1

3.22/9.02

46.21/9.75

59.76/14.58

175.76/9.75

Y2

3.22/20.23

46.21/19.49

59.76/14.67

175.76/19.49

Z1

6.08/9.08

59.59/9.75

63.03/7.36

225.05/9.75

Z2

6.08/20.23

59.59/19.49

63.03/21.89

225.05/19.49

4 Fault Detection Algorithm The fault detection algorithm can be easily determined from the results detailed in Sect. 3. In fact, the pattern is repeating for a certain condition. Vibration limits are low for normal conditions without load (lower than 20 g-force) and normal conditions with load (higher than 20 g-force). When a misalignment condition occurs, the vibration limits increase. During looseness conditions we can see a high increase in vibration limits. Regarding the FFT results, the vibration occurs always (with load and without load) on the same frequencies around 9.75 Hz and 20 Kz for normal conditions. For the misalignment conditions the peaks are happening at different frequencies. For the looseness condition high value peaks are being recorded. A value of 80 is considered as threshold for looseness condition. In Fig. 4 we can see the raw recording of the looseness condition. The temperature signal is always the same. For different recordings the temperature changed but it is mainly related to the operation period of the machine. For that we will not include it in or algorithm (Fig. 5).

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Fig. 3. FFT of the normal condition.

Fig. 4. Vibration signal for the three axis and temperature recordings for the looseness condition.

From the above results we can develop our fault detection algorithm. By analyzing both the vibration limits and the FFT we can detect the fault that is happening to the motor. In fact, vibration limits which are lower than 1.26 g-force are considered as a sign of normal condition. Vibration limits that are between 1.26 and 1.5 g-force are

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Fig. 5. Fault detection algorithm applied to the motor.

Fig. 6. FFT of looseness condition.

considered as a sign of misalignment condition. Vibration limits that are higher than 1.5 g-force are considered as a sign of looseness condition. The FFT analysis is carried in parallel to the vibration limits. When the peaks happen at 9 Hz and 20 Hz the system is considered operating in normal condition. When the peaks magnitude is higher than 20 g-force, the system is with a load. If the peak values exceed 80 g-force the system is in looseness condition.

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If the peak frequencies vary between the three axes, a misalignment condition is detected. We can see clearly how the algorithm detected a normal condition with load in Fig. 3 and a looseness condition in Fig. 6. An additional misalignment condition is detected in Fig. 6 because the looseness of the machine lead to a misalignment. Compared to algorithms developed in literature our paper presents a less complex system where only one sensor is required.

5 Conclusion Modern HVAC systems are more progressive and complex than the older type. In healthcare centers they should be designed with high standards, any malfunction in the system would affect the patient health. For that, these systems should be monitored carefully and more specifically. They should be applied to predictive maintenance systems capable to track fault signs and predict faults before happening. We have developed a fault detection system that records the vibration of induction machines and according to their values and the FFT analysis detect normal condition of operation, misalignment condition and looseness condition. Future works can be carried out to detect more faults.

References 1. Negative and Positive Pressure Rooms 101—Hospital Infection Control, 1 March. https://air innovations.com/blog/negative-positive-pressure-rooms-hospital-infection-control/ 2. Trzynadlowski, A.M.: Control of Induction Motors. Academic Press, San Diego (2000) 3. Tavner, P., Ran, L., Penman, J., Sedding, H.: Condition monitoring of rotating electrical machines. IET (2008) 4. Dalvand, F., Kalantar, A., Shokoohi, S., Bevrani, H.: Time-domain bearing condition monitoring in induction motors using instantaneous frequency of motor voltage. In: 2014 Smart Grid Conference (SGC), pp. 1–7 (2014) 5. Rajapaksha, N., Jayasinghe, S., Enshaei, H., Jayarathne, N.: Supervised machine learning algorithm selection for condition monitoring of induction motors. In: 2021 IEEE Southern Power Electronics Conference (SPEC), pp. 1–10 (2021) 6. Nehme, B., Msirdi, N.K., Namaane, A., Akiki, T.: Analysis and characterization of faults in PV panels. Energy Proc. 111, 1020–1029 (2017). https://www.sciencedirect.com/science/art icle/pii/S1876610217302989 7. 13 common causes of motor failure. https://www.fluke.com/en-gb/learn/blog/motors-drivespumps-compressors/13-common-causes-of-motor-failure. Accessed 21 Oct 2022

Development of a Remote-Controlled Scaled Multi-actuated Vehicle Stefano Lovato , Giovanni Righetti, Alice Canton, Basilio Lenzo(B) , and Matteo Massaro Department of Industrial Engineering, University of Padova, Via Venezia, 1, Padua, Italy {basilio.lenzo,matteo.massaro}@unipd.it

Abstract. This work illustrates the development of a remote-controlled (RC) scaled four-wheeled vehicle for the experimental implementation of torque vectoring (TV) control strategies. A commercial 1:12 scale model equipped with four electric motors driving the four wheels and one electric motor controlling the steering is selected. The commercial product is modified to allow independent control of each motor torque. On-board instrumentation is also added to monitor the vehicle motion. Ramp-steer manoeuvres in quasi-steady-state conditions are performed to experimentally characterize the cornering response of the vehicle, which will then be used within TV developments. Keywords: SDG9 · Scaled vehicle · Torque vectoring response · Understeer · Vehicle dynamics

1

· Cornering

Introduction

Scaled vehicles allow to perform physical tests related to vehicle dynamics, while reducing costs and allowing easier and safer implementation compared with fullscale experimental platforms. This is also in line with the sustainable development goal (SDG) 9, when it comes to supporting the development of technology, research and innovation. In [1] an experimental platform was developed within the reducedsize unManned buggy (RUMBy) project, with the objective of executing autonomously different manoeuvres. The systems consists of a remote-controlled (RC) 1:6 scale model. It is powered with a two-strokes engine, connected to the powertrain by means of a centrifugal clutch, and is equipped with four disk brakes. It is subsequently modified with the necessary on-board instrumentation. More recently, [2] presented the eRUMBy, a 1:8 rear wheel drive (RWD) scaled vehicle provided with a DC motor, based on a commercial chassis. An evolution of this platform is described in [3], characterised by an all wheel drive (AWD) c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 270–277, 2023. https://doi.org/10.1007/978-3-031-32439-0_31

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powertrain, which is obtained using a single three-phase brushless motor together with three differentials. However, the vehicle is used in a RWD configuration in the paper. During the experimental tests, the position and orientation of the eRUMBy are tracked by an OptiTrack system mounted inside the arena where the tests are performed. This highlights one big advantage of these reduced-size experimental platforms: they indeed require relatively small spaces for carrying out physical tests, allowing to exploit simple external tracking systems. The optimal control of autonomous 1:43 racing cars is investigated in [4]. A Kyosho dNaNo RC race car models is employed. The work focuses on controlling the car at its friction limits, by using a single-track model and a nonlinear tyre model. A similar contribution is described in [5], which discusses the implementation of nonlinear model predictive control (MPC) strategy for real-time control of autonomous vehicles, with the objective of minimum lap time. The experimental validation is performed using the 2008 Kyosho dNaNo FX-101 scale model. The position, speed, orientation and yaw rate of the plant is obtained by an infrared sensing system mounted above the small test track. A RC reduced-size vehicle model was also employed in [6] for experimental validation of a hierarchical-coordinated control distribution strategy for a sixwheel independent-drive unmanned ground vehicle. The model is equipped with six in-wheel motors, that can be controlled individually through an electronic control unit (ECU). Furthermore, experimental results are compared to virtual simulations using ADAMS and MATLAB [6,7]. A RC 1:12 scaled model of a four-wheeled vehicle is presented in this work, with the final goal to experimentally investigate torque vectoring (TV) control strategies. For this purpose, a commercial product was modified to allow independent torque control of the four electric motors (one for each wheel). On-board sensing instrumentation was employed to monitor the vehicle motion. Experimental tests were performed to determine the vehicle cornering response, hence the understeer gradient. The tests carried out consist of several ramp-steer manoeuvres in quasi-steady-state conditions at different vehicle speeds. The work is organised as follows. In Sect. 2 the architecture of the vehicle model and the instrumentation adopted are presented. Section 3 describes the experimental tests, while in Sect. 4 the results are discussed. Finally, conclusions are given in Sect. 5.

2 2.1

Vehicle Commercial Model Selection

A low-cost experimental prototype for TV applications has to meet five main targets. – Compactness: the model must have small dimensions to allow easy and safe implementation for testing. – Dynamic relevance: the vehicle architecture needs to allow for a dynamic behaviour resembling that of a real car.

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– Fitness for purpose: four independently controlled motors are necessary to fully investigate TV control strategies. – Flexibility: the model should allow fast adjustment and tuning, without compromising its integrity. – Affordability: the overall system should have low cost. The RC car selected is the 1:12 scale model RB1277A of RBRC (see Fig. 1), which has overall length 39.5 cm, width 26 cm and height 14.5 cm. The commercial model is equipped with a 7.4 V-1800 mAh LiPo battery, which guarantees a using time of approximately 10 min, a servo motor for the steering actuation and four brushed DC motors (one for each wheel), controlled by pulse width modulation (PWM). The ECU has sixteen MOSFETs (four for each motor) for the voltage control of speed and direction of rotation of the motors, a receiver for the input commands given by a joystick, a voltage regulator and a driver for the steering servo motor.

Fig. 1. Commercial 1:12 scale model RB1277A employed for the development of the experimental platform.

2.2

Modifications

The commercial version of the model is modified in order to meet the desired requirements. The model is equipped with four TB9051FTG drivers which control the DC motors via PWM and provide feedback motor current, in order to be able to control each motor torque (i.e. each motor current) independently. DC motors are controlled via four digital PI controllers (one for each motor), which manipulate the motor voltage to control the current. The tuning of the PI gains is performed by trial-and-error by evaluating the performance of the step response, the target being the minimum settling time without overshoot. The original receiver is replaced, since it does not allow simple modifications. The steering servo motor is also replaced with a similar one, but with the driver integrated inside (while the original one had an external driver on the ECU).

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The original wheels (Fig. 1) are replaced by wheels with standard (i.e. not solid) tyres (Fig. 2). The on-board sensing instrumentation consists of a 9-axis inertial measurement unit (IMU), which is used for the measurement of the vehicle accelerations, angular velocities and magnetic field. The IMU employed is a BNO085 and is able to estimate the vehicle yaw, pitch and roll angles using a sensor fusion algorithm. In addition, 3144LUA-S Hall effect sensors are installed on each wheel to measure its angular velocity, which is related to the motor speed by a known gear ratio. A Teensy 4.1 microcontroller logs all sensors signals and deals with the execution of the control loop. The platform in its final configuration is shown in Fig. 2.

Fig. 2. Vehicle prototype with (1) Hall effect sensors, (2) IMU, (3) receiver, (4) microcontroller, (5) motor drivers, and (6) brushed DC motors.

3

Experimental Tests

The experimental tests consist of ramp-steer manoeuvres at two (nominal) speeds, namely 2.8 and 4.4 m/s, turning both left and right and with 3 repetitions for each test. The steer angle (measured at the steering servo motor) is increased from 0◦ to 20◦ with a steering rate of 2 ◦ /s, to give a total manoeuvring time of 10 s. A wheel-to-servo-motor steering ratio of 0.85 is found experimentally, therefore the steering angle at the wheels varies up to 17◦ . The AWD configuration is selected, with the overall torque demand equally distributed among the four driving motors.

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Fig. 3. Data logged during a ramp-steer manoeuvre at nominal speed 2.8 m/s after the low-pass filtering and decimation: vehicle speed (top left), front-left motor current (bottom left), steering angle (top right), and yaw rate (bottom right).

Signals from the sensors are logged with a sampling rate of 1 kHz. Data are then filtered offline using a finite-impulse-response third-order low-pass digital filter with cutoff frequency 5 Hz and decimated, to give a final sampling rate of 100 Hz. The vehicle velocity V is estimated as the mean value of four wheel speeds as follows 4 1 ri ωi , (1) V ≈ 4 i=1 with ωi the wheel angular velocities and r the wheel radius (assumed equal for all wheels). Figure 3 shows the speed (top left), front-left motor current (bottom left), steering angle (top right), and yaw rate (bottom right) of a ramp-steer manoeuvre at nominal speed 2.8 m/s while turning right, after low-pass filtering and decimation. The PI controller is able to keep the motor current approximately constant and close to the reference value; see the reference (solid line) and measured (dotted line) currents in the bottom-left plot in Fig. 3. The turning starts at around 1 s and the steering angle increases reaching the final value of 17◦ after 10 s, with a final yaw rate of approximately 1.7 rad/s. The torque on wheels is kept almost constant along the manoeuvre: the speed slightly increases up to around 4 s (steering angle below 5◦ ) then slightly drops.

4

Results and Discussion

One of the most used metrics employed to characterise the steering response of vehicles is the understeering gradient [8–11]. Indeed, many TV strategies use it to modify and enhance the vehicle cornering response [12,13]. The steady-state

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steering characteristics can be built experimentally by plotting the dynamic steering angle δd as a function of the lateral acceleration ay , with δd given by δd = δ − δk ≈ δ −

w w = δ − 2 ay , R V

(2)

where δ is the actual steering angle at the wheels, δk = w/R is the kinematic steering angle, w is the vehicle wheelbase, and R is the cornering radius. The steady-state lateral acceleration ay is estimated using the standard formula ay = rV,

(3)

where r is the yaw rate measured by the IMU. The understeer gradient Kus is defined as  ∂δd  (4) Kus = ∂ay ay =0 A positive Kus is associated to an understeering behaviour, a negative one to an oversteering behaviour while a null Kus is related to neutral characteristic. In practice, the understeer gradient Kus can be computed as the slope of the linear region (i.e. at small lateral accelerations) of the steering characteristics.

Fig. 4. Experimental steady-state steering characteristics obtained for a nominal vehicle speed of 2.8 m/s (a) and 4.4 m/s (b). Three tests are performed (squares, circles, and crosses) for each steering direction. The experimental data are down-sampled by a factor 20 only for plotting purposes.

The diagrams obtained for a nominal speed of 2.8 m/s are shown in Fig. 4(a) for the three tests in both steering direction (squares, circles, and crosses). The scaled model mainly exhibits an understeering behaviour, with a linear response

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up to around 3.0 m/s2 . The maximum steady state lateral acceleration is about 4.1 m/s2 —at this point an increase of the steering input is no more related to an increase of ay ; see the vertical dashed lines in Fig. 4(a). Due to some backlash in the steering system not all curves pass through the origin (see e.g. the left turns in Fig. 4(a) at small lateral accelerations), yet the manoeuvres are generally consistent. Similar results are obtained for nominal vehicle speeds of 4.4 m/s; see Fig. 4(b). Again, the curve exhibits a linear behaviour up to 3 m/s2 , with slightly higher lateral accelerations reached at the limit conditions; see the vertical dashed lines in Fig. 4(b). For each nominal speed, the understeer gradients are estimated from the corresponding steering characteristics using a linear fitting of the linear region, i.e. with lateral acceleration below 3 m/s2 ; see the solid lines in Fig. 4. The estimated understeer gradients are 0.74 and 0.76 ◦ /(m/s2 ) for a nominal speed of 2.8 and 4.4 m/s, respectively.

5

Conclusion

In this work the development of a remote-controlled (RC) scaled model of a fourwheeled vehicle from a commercial product is presented, with a special focus on the modifications performed to make it suitable for investigating torque vectoring (TV) techniques. The commercial model employed is a 1:12 RC scaled vehicle, adapted for TV applications by allowing the independent control of the four electric motors that drive the wheels and by adding on-board instrumentation to monitor the vehicle motion. Experimental tests consisting of ramp-steer manoeuvres at two nominal speeds in both steering directions are performed to assess the cornering response of the vehicle and evaluate its understeer gradient in quasi-steady-state conditions. The vehicle mostly exhibits an understeering behaviour and the limit steady state lateral acceleration is found. The consistency of the test results suggests that the RC scaled model developed is a suitable platform for the experimental investigation of TV, with additional benefits related to the simplicity of implementation and the reduced costs as compared to a one-to-one scale vehicle.

References 1. Bertolazzi, E., Biral, F., Bosetti, P., De Cecco, M., Oboe, R., Zendri, F.: Development of a reduced size unmanned car. In: 2008 10th IEEE International Workshop on Advanced Motion Control, pp. 763–770 (2008) 2. Piscini, D., Pagot, E., Valenti, G., Biral, F.: Experimental comparison of trajectory control and planning algorithms for autonomous vehicles. In: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society, vol. 1, pp. 5217– 5222 (2019) 3. Pagot, E., Piccinini, M., Biral, F.: Real-time optimal control of an autonomous RC car with minimum-time maneuvers and a novel kineto-dynamical model. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2390–2396 (2020)

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4. Liniger, A., Domahidi, A., Morari, M.: Optimization-based autonomous racing of 1:43 scale RC cars. Optim. Control Appl. Methods 36, 628–647 (2015) 5. Verschueren, R., De Bruyne, S., Zanon, M., Frasch, J.V., Diehl, M.: Towards timeoptimal race car driving using nonlinear MPC in real-time. In: 53rd IEEE Conference on Decision and Control, pp. 2505–2510 (2014) 6. Prasad, R., Ma, Y., Wang, Y., Zhang, H.: Hierarchical coordinated control distribution and experimental verification for six-wheeled unmanned ground vehicles. Proc. Inst. Mech. Eng. Part D J. Automobile Eng. 235(4), 1037–1056 (2021) 7. Ma, Y.: Dynamics and Advanced Motion Control of Unmanned Ground Off-Road Vehicles. Emerging Methodologies and Applications in Modelling, Identification and Control. Academic Press (2020) 8. ISO 4138. Passenger cars - Steady-state circular driving behaviour - Open-loop test methods (2012) 9. Limebeer, D.J.N., Massaro, M.: Dynamics and Optimal Control of Road Vehicles. Oxford University Press, Oxford (2018) 10. Guiggiani, M.: The Science of Vehicle Dynamics. Springer, Dordrecht (2014). https://doi.org/10.1007/978-94-017-8533-4 11. Pacejka, H.B.: Tire and Vehicle Dynamics, 3rd edn. Butterworth Heinemann, Oxford (2012) 12. Lenzo, B.: Torque vectoring control for enhancing vehicle safety and energy efficiency. In: Lenzo, B. (ed.) Vehicle Dynamics. CICMS, vol. 603, pp. 193–233. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-75884-4 4 13. Esmailzadeh, E., Goodarzi, A., Vossoughi, G.R.: Optimal yaw moment control law for improved vehicle handling. Mechatronics 13(7), 659–675 (2003)

Functional Design and Prototyping of a Novel Soft Fingertip with Variable Stiffness Giovanni Colucci(B) , Carmen Visconte, and Giuseppe Quaglia Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy {giovanni colucci,carmen.visconte,giuseppe.quaglia}@polito.it

Abstract. The paper presents a novel soft fingertip for soft robotics application in greenhouses and protected cultivation. The system is designed to be easily adapted to different commercial end-effectors while not compromising their functionalities. The use of auxiliary vessels with combined air and liquid presence allows the adjustment of the fingertip stiffness to guarantee different values of exerted contact force and stiffness when compressed. A simplified design method to evaluate the influence of the membrane shape and the set-up parameters on the system behavior is reported. The method was compared with experimental measurements on a first system prototype.

Keywords: SDG12 Grasping

1

· Assistive Robotics · Soft Fingertip · Compliant

Introduction

Within the last decades, Precision Agriculture (PA) has become a highly productive research field thanks to its significant impact in helping human being for responsible and intelligent crops farming [2,9,12]. The academic research in PA technologies and methods pursues the 2030 Agenda for Sustainable Development, especially the Sustainable Development Goal (SDG) 12 towards sustainable consumption and production patterns. Robotic systems and technologies are nowadays also implemented in protected cultivation, where the crops are preserved from environmental and external factors, e.g. precipitation and pests, and a high level of cultivation control is guaranteed to address the constant worldwide population growth and rise in food demand [4,7]. These scenarios are often exploited for the mass production of highly-valued cultivation, where the process automation and mechanization helps for heavy and repetitive tasks. In protected cultivation, the most time-consuming and intensive activity is usually harvesting [4], and several solutions based on mechanical harvesting, shake-and-catch systems or selective methods have been investigated. Besides, c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 278–289, 2023. https://doi.org/10.1007/978-3-031-32439-0_32

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the target fruit is often too fragile and delicate to be grasped with rigid robotic hand, thus the use of compliant and soft grasping interfaces are often proposed for tomatoes [3], sweet peppers [7,10] and strawberries [5]. Soft materials are widely studied because of their adaptability and to not leave damages or even signs on the grasped object [6]. In [8] an anthropomorphic fingertip made by silicone rubber and distributed internal strain gauges is presented, where the sensors are not calibrated and the grasping model is built on experimental data. In [1] a similar fingertip structure is used to develop a manipulator controller that adjusts the grasping stiffness. In [11] a novel contact model for silicone-made fingertip was presented, where the classical rigid fingertip approach is changed to take into consideration the membrane deformation. In this paper, a novel soft fingertip with variable stiffness for autonomous picking is presented. It is based on a combined hydraulic and pneumatic auxiliary vessels, and it is designed to be adapted to different commercial robotic endeffectors just changing the fingertip mounting base geometry (Fig. 1) without compromising the robotic manipulator functionalities.

2

Functional Design

The novel fingertip under investigation is based on a soft membrane, whose structural stiffness is ideally negligible when pressed, connected to an auxiliary hydraulic/pneumatic system that determines the variable stiffness behaviour. Thus, as presented in Fig. 2, the system functional architecture is based on the following components: – The soft membrane itself; – A rigid mounting base, that is also demanded to connect the membrane volume to the auxiliary system; – Two auxiliary volumes that are respectively under the absolute pressure levels PC1 , PC2 . They are partially filled with the same incompressible liquid that is within the membrane, and the remaining volume, that is respectively VC1 , VC2 is filled with air;

Fig. 1. (a) The proposed soft fingertip mounted on a commercial KinovaGen2 manipulator. (b) Behaviour of the soft fingertip when grasping a generic object.

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Incompressible liquid P(ys), V(ys)

Deformable membrane

Air PC1, VC1

PC2, VC2

ys

Rigid base

Fig. 2. System functional architecture.

– A 3/3 digital valve that regulates the possible connections between the fingertip and the two auxiliary volumes; If the dynamic behaviour of the proposed architecture is neglected, the liquid that fills the fingertip volume V acts as an hydrostatic transmission when the fingertip is compressed of a ys value, and it provokes the compression of the VC1 , or VC2 , air volume. Thus, the resulting fingertip stiffness is mainly related to the compression law of the air volume, that can be adjusted by setting the initial value of the pressure level PC[1,2],i and air volume VC[1,2],i . In particular, this feature would be used to achieve two different behaviour of fingertip stiffness, where the first one should be used to manipulate and grasp soft and delicate objects, while the second one should be used for rigid ones. Moreover, the 3/3 valve also allows to disconnect V from both the auxiliary volumes. In this case, even a low value of ys causes a significant increment of the exchanged contact force F , since the fingertip stiffness is now imposed by the fluid compressibility and the membrane deformability, that are no longer negligible. Regarding the additional components, the two non-return valve connected to the auxiliary reservoirs VC,[1,2] are used to connect the supply pressure source during the set-up procedure. A flow control valve is mounted on the rigid base to allow the correct spillage of air during the filling procedure of the membrane with the incompressible liquid. To complete the basic system architecture, a pressure sensor measures the pressure level P within the fingertip. As it will be presented within the next sub-sections, this value is used to estimate the membrane compression ys while the fingertip is in contact with the target object.

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281

Fingertip Geometry Modelling

The obtain a geometry that is similar to a fingertip, the membrane was modelled starting from the combination of three tangent circle arcs, that lie into the first quadrant of the < x, y > plane of Fig. 3. The membrane shape is then described by the radius lengths r[1,2,3] and arc angles α[1,2,3] . Besides, the design parameters i, h, s respectively impose the fingertip width, length and thickness. It is worth underlining that, while i could be imposed by the specific fingertip application, e.g. its implementation on a robotic manipulator end-effector with specific geometries, h and s can be varied during the design process. As presented in Sect. 3, s mainly affects the fabrication procedures, since it could be difficult to produce excessively thin membrane but the fingertip structural stiffness would increase if a too high value of s is selected. On other hand, the height h changes the maximum compression length ys,max , i.e. it changes the total amount of volume ΔV that can be squeezed while manipulating the target object. To obtain the entire fingertip geometry, the described shape is flipped around the y axis and extruded by the length l along z. The volumes at the extremities that complete the membrane are then obtained as solids of revolution around the same y axis. Please notice how l depends on L according to the following equation: L = l + 2i (1) The geometric constraints, i.e. the vertical displacement of O1 , the tangency between the consecutive arcs and the horizontal displacement of the end point of the arc of radius r3 , reduce the number of geometric parameters down to four values. Thus, a selected number of possible type of shapes were classified by varying four adimensional parameters, that are compared with the two encumbrance parameters i and h, as reported in Table 1. The four selected shapes are also depicted in Fig. 4: r1 P1

s h

α3

r2 α2 O2

L

P2 P3

α1

l 2i

O3

r3

O1 i

(a)

(b)

Fig. 3. (a) membrane axonometric view. (b) Section view of the membrane

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– In Type A case, almost the entire horizontal encumbrance i is reached by the first arc portion of radius r1 , while the third arc presents minimal curvature, i.e. r3 >> r1 . – Type B case has the three arc radius quite similar between them, i.e. r1  r2  r3 . Thus, it represents the shapes that reproduce a spherical membrane within the < x, y > plane. – Type C represents the category of membrane where r1 arc has an high value of α1 , i.e. α1 ≥ π/3, and the remaining arcs with a minimal curvature. – In Type D case, the r1 arc reaches the entire encumbrance , i.e. xP 1 ≈ i, thus producing a bellow-like geometry.

2.2

Fingertip Stiffness Estimation

The selection of a membrane shape among the four presented types produces significant effects on the system properties, especially in terms of grasping force F . Within the present subsection, a simplified model of the fingertip compression while manipulating is presented. To this aim, the following simplifying assumptions are made: – The grasped object is considered as infinitely rigid, then the fingertip is the only part between the two that is subject to deformation; – The grasped object is considered as planar, i.e. it can be modelled as a plane that covers the entire fingertip encumbrance within the < x, z > plane; – The deformed membrane is not subjected to radial deformation, i.e. each < x, z membrane section does not elongate or contract. The last two assumptions lead to a deformed fingertip geometry that is obtained by sectioning the membrane with a plane that is parallel to < x, z >. Thus, as presented in Fig. 5, the two functions of internal volume V and contact area A are only functions of the compression length ys and can be obtained once the membrane geometry is known. The proposed considerations could result as too simplifying when manipulating complex geometries and/or objects that are smaller than the fingertip, also it doesn’t consider the border effect near the contact area and those near the base mounting. Nevertheless it is worth underlining that they were introduced to have an effective design methodology to get Table 1. Adimensional parameters for the shape types presented. xP 1 yP 1 xP 2 yP 2 b= c= d= i h xP 1 yP 1 Type A 0.65 0.9 1.4 0.7 Type

a=

Type B 0.85

0.55

1.02

0.95

Type C 0.57

0.7

1.4

0.5

Type D 0.6

0.95

1.7

0.8

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Fig. 4. Section view of the four types of membrane shapes in the < x, y > plane.

a first estimation of the system behaviour that must be still compared with experimental measurements. When the fingertip is subject to a compression equal to ys , the air volume trapped into the first (or second) auxiliary vessel is therefore equal to: VC1 = VC1,i − ΔV (ys )

(2)

where VC1,i is the initial air trapped volume, that can be adjusted during the system set-up procedure, and ΔV is the amount of liquid that is squeezed from the fingertip into the auxiliary system. By referring to Vi , that is the initial incompressible liquid volume within the fingertip, the adimensional ξC1 parameter can be introduced: VC1,i (3) ξC1 = Vi

F

ΔV(ys)

Contact plane

ys

P(ys), V(ys)

Contact area A(ys)

Fig. 5. Model of the fingertip when compressed by a planar and infinitely rigid object.

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By assuming that the air volume comes under an adiabatic transformation (γ = 1.4), the absolute pressure P inside the fingertip will follow the standard compression rule:  γ VC1,i P (ys ) = PC1,i (4) VC1,i − ΔV (ys ) Thus, the exerted contact force F can be defined as the product between the relative pressure p = P − Patm and the contact area A = A(ys ): F = p(ys ) A(ys )

(5)

and the obtained stiffness can be defined as follows: k(ys ) =

dF (ys ) dA(ys ) dp(ys ) = p(ys ) + A(ys ) dys dys dys

(6)

that highlights how both the geometrical parameters, i.e. the contact area and the compression transformation, affect the overall system stiffness. By taking into account Eq. 2 and Eq. 4, k can be computed as:   γ  dA(ys ) VC1,i PC1,i VC1,i −ΔV (ys ) − Patm + (7) k(ys ) = dys − γ PC1,i

VC1,i γ dΔV (ys ) A(ys ) γ+1 (VC1,i − ΔV (ys )) dys

where the geometric features of the membrane affect k in terms of the squeezed incompressible liquid volume ΔV , the contact area A and their first order derivatives. The two initial values PC1,i and VC1,i can instead be used as set-up parameters to adjust the stiffness curve. The estimated behaviour of F for the four geometrical types was then obtained by assuming the values of the set-up parameters, as presented in Fig. 6. Type A and Type D present a high stiffness for low value of ys due to the first term of Eq. 6. Type C presents the lowest value of F , even though the ending part of its graph presents an increasing value of stiffness due to the second term of Eq. 6 . Nevertheless, the model doesn’t consider the border effects that depend on the base-membrane constraints and the membrane thickness, that don’t allow the total fingertip compression if the membrane folds on itself when compressed. Thus, it is reasonable to assume a maximum compression value that is lower than the total height ys,max < h. In Fig. 6, a maximum value of ys,max = 7.5 mm was used.

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Fig. 6. Contact force F for all types of membrane shape.

3

Prototyping and Experimental Tests

To validate the novel sensing system through experimental tests, a first version of the fingertip was produced in laboratory environment by using standard and affordable technologies and materials for soft robotics applications. The fingertip membrane was both manufactured in addition cure silicone rubber by casting processes but also in thermoplastic polyurethane by FDM (fused deposition modeling) technologies. To this aim, Type A shape was selected for its higher value of contact force F for fixed ys , while Type D shape resulted as too difficult to manufacture. Regarding the silicone membrane, the moulds were realized in plastic material (PLA) with an FDM printer. The membrane internal structure was strengthened with cotton filaments which prevent the membrane expansion when inflated. As showed in Fig. 7 (a), different values of thickness s were tested with the same material in order to evaluate the membrane stiffness. According to the authors’ experience, it is possible to produce these shape with thickness values down to 1 mm while maintaining the procedures quite simple and easy to reproduce. On other hand, even though an higher value of s results into easier manufacturing procedures, the resulting membrane structural stiffness resulted as too high for the specific application. Moreover, due to the thinness of the membrane, it resulted as fundamental the implementation of degassing procedures to avoid the inclusion of air bubbles inside the structure. With regards to the use of a rapid prototyping printer, the use of FDM techniques allows to realize a single-piece fingertip that both includes the membrane and the rigid base itself, but the use of supporting material for the membrane is not allowed due to the closed shape of the fingertip. The authors tested only a TPU 95A material that was printed with s= 1 mm, but it resulted as to rigid. It is worth underlining how a lower value of s was not possible since it resulted into

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Fig. 7. (a) Produced membranes with different materials and thickness. a: EcoFlex 00–50 s = 1 mm, b: EcoFlex 00–50 s = 2 mm, c: EasyComposites AS40 s = 1 mm, d: EasyComposites AS40 s =2 mm, e: TPU 95A s=1 mm. (b) Overview of the entire system with auxiliary components. f: mon return supply-valve, g: ElveFlow microfluidic reservoir, h: pressure sensor.

liquid leakages. The authors don’t prevent the possibility to obtain a proper and soft membrane with the use of different nozzle diameters and different materials. For all the presented shapes and materials, an experimental evaluation of the membrane structural stiffness was carried out and summarized in Table 2 by reporting only the average stiffness kstruct,avg , defined as the ratio between the maximum force and the related compression value that were measured before the start of the border effects: kstruct,avg =

Fmax ys,max

(8)

The auxiliary vessels (in Fig. 7(a) a single-auxiliary-volume VC1 is presented) were realized by using a 50 mL microfluidic reservoir with a custom two-holes cup, where the first is used for the external air pressure supply and the latter to catch the liquid from the middle of the vessel by means of an internal tube. The silicone-made membrane needs a fixing system to mount it upon the rigid base, that was realized with plastic PLA material, and prevents from liquid leakages. In Fig. 8 an exploded view of the fingertip sub-system is presented. Please notice how the sealing functionality is guaranteed by a cone mounting, Table 2. Average structural stiffness for the tested materials and thickness values. Material

Thickness kstruct,avg [N/mm]

EcoFlex 00–50

1 mm

EcoFlex 00–50

0.82

2 mm

1.01

EasyComposites AS40 1 mm

1.56

EasyComposites AS40 2 mm

4.10

FDM TPU 95A

7.35

1 mm

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Clamping ring

Deformable membrane 6x M2 mounting screw

4 mm plastic tube M2 spillage screw

Fig. 8. Exploded view of the fingertip mounting system.

since both the base and the ring sides are inclined of a certain angle, then the mounting screws only guarantee the correct positioning of the ring with respect to the base. On the bottom of the membrane, a screw was added to realize the air spillage during the set-up filling of the fingertip. 3.1

Experimental Evaluation of Fingertip Contact Force

Within the present subsection, the experimental measurements of the contact exerted force between the fingertip and a planar and infinitely rigid object are presented. The membrane made of AS40 silicone rubber and 1 mm thick was

Fig. 9. Model and experimental curves of contact force and internal pressure for a fixed set-up of design parameters.

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selected, since it still presents a relatively low structural stiffness value but also the AS40 material resulted as more resistant to abrasion and wear than the EcoFlex 00–50. The results of the experimental measurements are showed in Fig. 9 for a couple of set-up parameters that are equal to ξC1 = 3.52 and PC1,i = 1.2 bar. The measurements were done up to a compression of ys = 7 mm since the membrane thickness and the clamping ring don’t allow bigger value of ys . The simplified model overestimates the contact force F until the value of ys ≈ 5.5 mm is reached, where a crossing point between the model and the experimental curve occurs. The model underestimates also the fingertip internal pressure for all the compression range, with a final (and maximum) gap of 0.24 bar (17% of relative error). This behaviour is mainly related to the assumption of no membrane expansion within the < x, z > plane. In fact, the membrane undergoes the bending of its sides when compressed (Fig. 10), leading to lower values of P (ys ). Lastly, the crossing point in the exerted force graph is caused by the increase of structural stiffness due to the fingertip border effects.

Fig. 10. (a) Fingertip at the beginning of the compression test. (b) Fingertip under compression.

4

Conclusion

The paper presented a novel deformable fingertip for precision agriculture applications in greenhouses, where an auxiliary system is demanded to adjust the stiffness and exerted contact force behaviour as a function of the fingertip compression. A simplified model, based on the assumption of homogeneous membrane deformation and planar contact, was used to design the membrane geometry and to choose the set-up parameters, i.e. initial pressure and air trapped volume. The employed manufacturing process was described in terms of adopted technologies and materials, underlining how it results as affordable and easy to reproduce even in laboratory environment. Additional details about the thickness value choice, the materials and the fingertip custom-made system were presented, also in terms of resulting membrane structural stiffness.

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Experimental measurements on a selected membrane shape and material were carried out, that proved the effectiveness of the simplified methods for designing purposes but also highlighted how an experimental system characterization is fundamental to not overestimate the membrane internal pressure.

References 1. Biagiotti, L., Tiezzi, P., Vassura, G., Melchiorri, C.: 4 modelling and controlling the compliance of a robotic hand with soft finger-pads. In: Barbagli, F., Prattichizzo, D., Salisbury, K. (eds.) Multi-point Interaction with Real and Virtual Objects. Springer Tracts in Advanced Robotics, vol. 18, pp. 55–73. Springer, Berlin, Heidelberg (2005). https://doi.org/10.1007/11429555 4 2. Bongiovanni, R., Lowenberg-Deboer, J.: Precision agriculture and sustainability. Precis. Agric. 5(4), 359–387 (2004). https://doi.org/10.1023/B:PRAG.0000040806. 39604.aa 3. Chiu, Y.C., Chen, S., Lin, J.F.: Study of an autonomous fruit picking robot system in greenhouses. Eng. Agric. Environ. Food 6(3), 92–98 (2013). https://doi.org/10. 1016/S1881-8366(13)80017-1 4. Davidson, J., Bhusal, S., Mo, C., Karkee, M., Zhang, Q.: Robotic manipulation for specialty crop harvesting: a review of manipulator and end-effector technologies. Global J. Agric. Allied Sci. 2(1), 25–41 (2020). https://doi.org/10.35251/gjaas. 2020.004 5. De Preter, A., Anthonis, J., De Baerdemaeker, J.: Development of a robot for harvesting strawberries. IFAC-PapersOnLine 51(17), 14–19 (2018). https://doi. org/10.1016/j.ifacol.2018.08.054 6. Elango, N., Faudzi, A.A.M.: A review article: investigations on soft materials for soft robot manipulations. Int. J. Adv. Manuf. Technol. 80, 1027–1037 (2015). https://doi.org/10.1007/s00170-015-7085-3 7. van Henten, E.J., Bac, C.W., Hemming, J., Edan, Y.: Robotics in protected cultivation. IFAC Proc. Volumes 46(18), 170–177 (2013). https://doi.org/10.3182/ 20130828-2-SF-3019.00070 8. Hosoda, K., Tada, Y., Asada, M.: Anthropomorphic robotic soft fingertip with randomly distributed receptors. Robot. Auton. Syst. 54(2), 104–109 (2006). https:// doi.org/10.1016/j.robot.2005.09.019 9. Kumar, S.A., Ilango, P.: The impact of wireless sensor network in the field of precision agriculture: a review. Wireless Pers. Commun. 98(1), 685–698 (2017). https://doi.org/10.1007/s11277-017-4890-z 10. Lehnert, C., English, A., McCool, C., Tow, A.W., Perez, T.: Autonomous sweet pepper harvesting for protected cropping systems. IEEE Rob. Autom. Lett. 2(2), 872–879 (2017). https://doi.org/10.1109/LRA.2017.2655622 11. Lu, Q., Rojas, N.: On soft fingertips for in-hand manipulation: modeling and implications for robot hand design. IEEE Robot. Autom. Lett. 4(3), 2471– 2478 (2019). https://doi.org/10.1109/LRA.2019.2906544. Conference Name: IEEE Robotics and Automation Letters 12. Meshram, A.T., Vanalkar, A.V., Kalambe, K.B., Badar, A.M.: Pesticide spraying robot for precision agriculture: a categorical literature review and future trends. J. Field Robot. 39(2), 153–171 (2022). https://doi.org/10.1002/rob.22043

Machine-Learning Based Energy Estimation on a High-Speed Transportation System Paolo Boscariol(B) , Dario Richiedei , Iacopo Tamellin , and Alberto Trevisani DTG, Universit` a degli Studi di Padova, Vicenza, Italy {paolo.boscariol,dario.richiedei,iacopo.tamellin, alberto.trevisani}@unipd.it Abstract. Reducing the energy absorption of automatic machines used in industry is one of the main goals towards the reduction of the carbon footprint, as well of the economic cost, of mass-produced goods. Incorporating energy improvements to existing machines and established technological processes can however be challenging, due to the complexity of estimating with a sufficient level of detail the actual energy consumption of a machine and even more by the difficulty of guessing the required modifications that allow to reduce such energy consumption. This work explores the possibility of using machine learning as a tool that allows estimating the energy consumption of a transportation system from a reduced set of numerical data that represent the main feature of the motion profile, in order to develop a model to be used for planning energy-efficient motion profiles. The investigation is based on experimental data gathered for a high-speed transportation device. Keywords: SDG9 · SDG12 Gaussian Process Regression

1

· machine learning · energy consumption · · energy saving

Introduction

Reducing the energy consumption is one of the main challenge that society has to face, owing to the impact of the use of non-renewable resources has on the environment. The area for improvements in this sense is enormous, considering that current trends reveal that global energy demand is expected to grow at a constant rate over the next decades [11], while the concern for the global warming suggests a total and immediate inversion of this trend. Reducing energy consumption in all sectors is of paramount importance for ensuring energy security, sustainability, to reduce emissions and to support job creation [9]. Industry must embrace this challenge by researching and implementing technologies that allow to reduce the amount of energy involved in each process, allowing to ’do more with less energy’. The call to industry for a greener production is clearly outlined in the SDG12 and SDG9: the latter explicitly suggests to ’upgrade c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 290–297, 2023. https://doi.org/10.1007/978-3-031-32439-0_33

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infrastructure and retrofit industries to make them sustainable with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies and industrial processes’. Researches have been working on the theoretical and technological issues of measuring, estimating, predicting and finally improving the energy consumption of automatic machines [14] and robots [3,12] for many years. A large part of this research has analysed in the review work [5], which lists almost 100 works published between 1993 and 2018. The improvement of the energy efficiency of an automatic machine can happen at any level of its development, but whenever possible, energy efficiency should be tackled at the design stage [2,10] by choosing the appropriate components, but also focusing on just the design of motion profiles can be a rather effective method to reduce energy consumption without sacrificing productivity [1,4] and with a minimal investment. As a result, large part of the literature on the topic has been focused on investigating the relationship between motion profiles and energy consumption, here just a few notable samples are cited. In the work [7] the authors focus on the analysis of the dominant factor that influence energy consumption in a rest-to-rest motion task, providing some general guidelines for the choice of the best profile among standard ones. The work [6] proposed a radically different approach, in which a trapezoidal motion profile is optimized in real-time to achieve minimum energy consumption with limited residual oscillations. Finally, an analytic approach is proposed in [14], by defining a set of analytic relationship that provide a simple but very effective parametrization of the overall energy consumption for any constant inertia system and for any rest-to-rest motion profile. These work proposed three radically different approaches, but they all are based on a somehow detailed knowledge of the physical parameters of the system, and as such, their accuracy and their practicality strongly depend on the possibility of getting such data. This can be difficult - or even impossible - when the data disclosed by the manufacturer are not sufficiently detailed. In order to overcome this frequent issue, the use of machine learning algorithm is proposed in this work as a feasible alternative to the most common physics-based models to develop energy consumption models, using some data collected on the field and without involving any specific physical parameter of the device under investigation. The latter, in particular, is an high-speed transportation system built by B&R, the ACOPOStrack. The aim of the algorithm is to develop an energy estimation model that relies just on some parameter that characterize the reference motion profile to be executed by the machine, that is sufficiently accurate and robust to enhance the energy efficiency of the device under investigation.

2

Machine Learning: Gaussian Process Regression

The model development procedure proposed here is based on the Gaussian Process Regression (GPR). The latter is a probabilistic supervised machine learning framework [13] that is used to predict continuous quantities. The basic idea of supervised machine learning is to provide to the algorithm some input data, as

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Fig. 1. The experimental setup: B&R ACOPOStrack

well as the corresponding outputs, to be used to train the model to be developed. In its most basic implementation, the model is built by fitting a set of data by a non-linear regression form. Unlike a standard non-linear regression, the set of infinite interpolating functions are described, rather than by standard functions, by Gaussian processes. The latter are collections of random variables, any finite number of which have consistent Gaussian distributions. A Gaussian process is uniquely defined by a mean function m(x) and a covariance function K(x, x ), so that the model that fits the data collected in x is represented as: y = f (x) ∼ GP(m(x), K(x, x ))

(1)

The use of Gaussian processes allows to define, in a single object, an infinite set of interpolating function, each one characterized by a mean value and a variance. The method used here, which is based on the software implementation made available by MATLAB, includes also a nonlinear regression term, as in: y = h(x)T β + f (x)

(2)

At the end of the iteration procedure, which strives at the best possible accuracy in reproducing the input/output relationship, a single model is needed rather than an infinite number of models described by some probability functions: the one with the highest probability is chosen as the one best fitting the model. For a more detailed explanation the reader might refer to the classic book [13]. In most cases then, as is the case for this work, the set of available measurements x is split into two parts, so that some measurements are used to train the deeplearning algorithm, the other ones are instead used to evaluate the fitness of the model.

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Fig. 2. Stator and shuttle: section view

Fig. 3. Measured data: cart speed, phase currents and voltages

3

Experimental Data and Model Fitting

The ACOPOStrack (see Fig. 1) is a transportation system which allows to move one or more shuttles along a sequence of stators, that can be arranged to create ’tracks’. Each shuttle can carry a payload up to 1 kg, and each shuttle can be controlled independently from the others. The structure of each element of the ACOPOStrack resembles the one of a Permanent Magnet Linear Synchronous Motor (PMLSM). Each element of the track is a stator, composed in the case under consideration by 42 coils, while the shuttle comprises 5 permanent mag-

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nets in alternate orientations [8], as shown in Fig. 2. When properly excited, the stator coils produce a magnetic field that interacts with the ones of the magnets on the shuttle, therefore exerting some force on it. The shuttle is kept at a fixed distance from the stator by four rollers. The electromechanical modeling of the ACOPOStrack is rather complex, as shown in the very detailed paper [8]. The system is however built by PMSLSMs, which are essentially a linear version of their more common ’circular’ counterparts. As such, they share the same working principle and similar modeling features, hence we can refer to the results developed for traditional motors in terms on the estimation of their power consumption. In particular, we might refer to the work of one of the authors [14], in which a detailed analysis of the electric power consumption of a single axis servoactuated system with constant inertia is carried out. One of the main results of the work is the development of analytic solutions to compute the energy required by a rest-to-rest motion task. In particular, the paper highlights that for a given device (and for a constant payload mass) such an energy consumption is a function of a limited set of variables, namely the total execution time of the motion, T , the overall displacement h, the RMS velocity coefficient, cV rms , and the RMS acceleration coefficient, cArms , of the commanded the motion profile. The other parameters involved in the estimation model are some physical parameters, some of which are however hard to estimate with precision, such as friction forces, the torque constant, the winding resistance, or the back-emf constant of the motor, just to cite some of the most relevant ones. The proposed approach solves the issue of providing precise and robust estimations for such parameters, as they are not directly involved in the model tuning procedure operated by the machine learning approach. The development of the model has been conducted by first running a large set of experiments, by moving one shuttle each time according to a different motion profile: the data set used for the experiments whose results are presented here refer to 200 samples of profiles tuned with displacements ranging from h = 0.05 m to h = 0.10 m, with execution times ranging from T = 0.08 s to T = 0.5 s, and using either a cubic or a quintic function to describe the motion profile. The limitation of the displacement, in this preliminary study, is related to the possibility of measuring the information of just four phases. The data collected for each trial includes the position of the shuttle, the voltage and the current of the four stator phases involved in the motion. One example of this kind of measurement is found in Fig. 3. The voltage-current product for each phase allows then to compute the instantaneous power draw by it, which is then summed over the four coils and integrated over time. Such calculation leads to the estimation of the energy consumption associated with the execution of each motion task, which is displayed in Fig. 4 for the motion of Fig. 3. Half of the 200 samples are used to train the machine learning algorithm, while the other half is used to assess its prediction capabilities. The input to the algorithm include four numeric data: the overall displacement h, the total execution time T , the two RMS coefficients of velocity and acceleration - i.e. the 4 relevant parameters that describe the motion profile. It must be pointed out that the machine learning algorithm does not possess any

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Fig. 4. Measured data: electric power for each coil, total electric power, total absorbed energy

other information. The output of the algorithm is the total energy consumption, E, measured in Joules. The results of the estimation are shown in Fig. 5: the figure shows in the first plot the energy associated with the 100 samples used for the results assessment: the estimated energy data, shown by blue dots, are compared with their values as estimated by the machine learning procedure, which are shown by orange circles. The likeness between the two is then measured by the correlation coefficient R, whose value is found to be equal to R = 0.9983: its proximity to one provides a first confirmation of the very good accuracy of the method. The data are then characterized by the Mean Squared Error (MSE), which is found to be equal to 0.0001248 J: the barplot on the bottom left-hand side of the figure shows that for the vast majority of the trials the prediction error is confined within ±0.02 J. The distribution of the percentage error among all 100 test samples is shown in the last graph: it shows that for 97 among the 100 samples the energy estimation error is with a ±6% range. In all the other three cases the prediction error does not exceed 10%. The overall Mean Absolute Percentage Error (MAPE) is equal to just 1.892%. All these data suggest that the proposed method is very effective in estimating the energy consumption from a limited set of data.

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Fig. 5. (a) Comparison of measured and predicted energy consumptions, (b) correlation chart, (c) prediction error distribution by MSE, (d) prediction error distribution by MAPE

4

Conclusion

This work proposes some preliminary results on the possibility of using machine learning methods to estimate the energy consumption of a servo-actuated system with constant inertia. In particular, the Gaussian Process Regression method has been used to develop a model that allows the prediction of the energy consumption of an high speed transportation system when executing a rest-to-rest motion task. The model has been trained using the data collected from a large number of experimental tests conducted by executing several motion profiles, during which the electric energy consumption of the machine has been measured. As a result of the training procedure, the prediction algorithm has proven to be capable of high accuracy whilst relying on just a simple set of parameters for the description of each experiment, namely the overall displacement, its duration, and the RMS coefficient of velocity and acceleration that characterize the motion profile. Machine learning has therefore proved to be a feasible method for energy estimation purposes, which defies the several challenges imposed by a purely physical modeling.

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References 1. Boscariol, P., Richiedei, D.: Energy-efficient design of multipoint trajectories for Cartesian robots. Int. J. Adv. Manuf. Technol. 102, 1853–1870 (2019). https:// doi.org/10.1007/s00170-018-03234-4 2. Boscariol, P., Richiedei, D.: Energy optimal design of servo-actuated systems: a concurrent approach based on scaling rules. Renew. Sustain. Energy Rev. 156, 111923 (2022) 3. Brossog, M., Kohl, J., Merhof, J., Spreng, S., Franke, J., et al.: Energy consumption and dynamic behavior analysis of a six-axis industrial robot in an assembly system. Procedia CIRP 23, 131–136 (2014) 4. Carabin, G., Vidoni, R.: Energy-saving optimization method for point-to-point trajectories planned via standard primitives in 1-dof mechatronic systems. Int. J. Adv. Manuf. Technol. 116(1), 331–344 (2021) 5. Carabin, G., Wehrle, E., Vidoni, R.: A review on energy-saving optimization methods for robotic and automatic systems. Robotics 6(4), 39 (2017) 6. Chen, H., Mu, H., Zhu, Y.: Real-time generation of trapezoidal velocity profile for minimum energy consumption and zero residual vibration in servomotor systems. In: 2016 American Control Conference (ACC), pp. 2223–2228. IEEE (2016) 7. Hansen, C., Eggers, K., Kotlarski, J., Ortmaier, T.: Task specific trajectory profile selection for energy efficient servo drive movements. In: ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction, vol. 31, p. 1. IAARC Publications (2014) 8. Kr¨ amer, C., Kugi, A., Kemmetm¨ uller, W.: Modeling of a permanent magnet linear synchronous motor using magnetic equivalent circuits. Mechatronics 76, 102558 (2021) 9. Malinauskaite, J., Jouhara, H., Ahmad, L., Milani, M., Montorsi, L., Venturelli, M.: Energy efficiency in industry: EU and national policies in Italy and the UK. Energy 172, 255–269 (2019) 10. Meoni, F., Carricato, M.: Optimal selection of the motor-reducer unit in servocontrolled machinery: a continuous approach. Mechatronics 56, 132–145 (2018) 11. Newell, R., Raimi, D., Aldana, G.: Global energy outlook 2019: the next generation of energy. Res. Future 1, 8–19 (2019) 12. Rankis, I., Meike, D., Senfelds, A.: Utilization of regeneration energy in industrial robots system. Power Electr. Eng. 31 (2013) 13. Rasmussen, C.E., Williams, C.K., et al.: Gaussian Processes for Machine Learning, vol. 1. Springer, Heidelberg (2006). https://doi.org/10.1007/978-3-540-28650-9 4 14. Richiedei, D., Trevisani, A.: Analytical computation of the energy-efficient optimal planning in rest-to-rest motion of constant inertia systems. Mechatronics 39, 147– 159 (2016)

Overturning Stability for the SNAP Cargo Family of Pedal-Assisted Ultralight Vehicles Francesco Passarella1,2 , Giacomo Mantriota2

, and Giulio Reina2(B)

1 SNAP s.r.l., 72100 Bari, Italy

[email protected] 2 Department of Mechanics, Mathematics and Management, Polytechnic University of Bari, Via

Orabona 4, 70126 Bari, Italy {giacomo.mantriota,giulio.reina}@poliba.it

Abstract. Innovation in transportation and mobility is the foundation for sustainable development. This paper provides details of the SNAP family vehicles, four-wheel pedal-assisted electric vehicles that represent a new concept in sustainable mobility that aims to fill the gap between bicycle and automobile. Special focus is given to the study of the overturning problem for this class of microcars that contribute to two Sustainable Development Goals: Affordable Clean Energy and Sustainable Cities and Communities. Keywords: SDG7 · SDG11 · electric-assisted vehicles · quadricycle · mobility · last-mile delivery · overturn stability

1 Introduction Innovation in the transport sector is one of the tools to be able to have sustainable development. The significant reduction in the mass of vehicles is one of the keys that can allow for a significant reduction in the environmental impact of travel in an urban environment. This paper is about SNAP Cargo+, a four-wheel pedal-assisted electric vehicle that represents a new concept in sustainable mobility towards filling the gap between bicycle and automobile. The architecture of the powertrain is hybrid, where the driver pedals are assisted with an electric motor. In this paper we introduce the new model, the Cargo+ and we make a comparative experimental and mathematical analysis of the performance: maximum speed, and travel range at varying operating conditions. An analysis of the vehicle’s cornering behavior as the load conditions vary is also addressed in this paper. It is shown that SNAP Cargo+ can be an answer to address the problem of sustainable transport in the urban environment (Fig. 1).

2 Current Standards and Design Requirements Electrically power-assisted cycles comply with the European standard EN15194. However, the SNAP is not explicitly considered in this standard because it has four wheels © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 298–306, 2023. https://doi.org/10.1007/978-3-031-32439-0_34

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Fig. 1. The drivetrain of the SNAP vehicle: the motor is connected to the rear wheels through a chain drive system

and not two wheels. Based on EN15194 standard [1], cycles must limit their speed to 25 km/h and power to 250 W. If the power rate increases up to 1 kW, the vehicle falls in the L1e-A category, with mandatory insurance that keeps the speed limit of 25 km/h. However, within the European Union there are no specific regulations that address the requirements and specifications of cargo bikes; the only exception is Germany. In fact, with regard only to pedal-assisted cargo vehicles, in Germany there is a specific regulation which is DIN 79010 [2]. This regulation lists the requirements and test methods for this category of vehicles. Another possibility is to fall in the lightweight quadricycles, e.g., L6e category, with mandatory insurance, with a power limit of 4 kW and a maximum speed of 45 km/h.

Fig. 2. The EAV vehicle on the left and the CITKAR vehicle on the right.

Currently, the market for this type of hybrid vehicle is not fully developed. Some of the most interesting vehicles are the EAV vehicle, of the Electric Assisted Vehicles Limited (UK) [3] company and the CITKAR vehicle [4], of the CITKAR GmbH (DE) company (Refer to Fig. 2). This vehicle is currently used by Amazon in the UK, comes with a load volume like that of the SNAP Cargo+ vehicle. The big difference is in the driving position: in the EAV vehicle the driver is seated on a saddle as on a normal bicycle. This driving position, compared to the configuration with a car seat, imposes a very high center of gravity (Cg) on the driver, and cornering can create an unpleasant sensation because tilting is not possible. The CITKAR vehicle has a very high selling price, which starts at e13900 excluding tax for the box version [4]. It has leaf spring suspensions and there is no underbody protection of the vehicle from water and debris.

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3 Introduction of the SNAP Cargo+ Model The SNAP Cargo+ is the model designed to meet the increasingly pressing demand to reduce polluting emissions in urban areas, both in the delivery sector and in the tourism sector. In fact, in the home delivery sector being able to have a vehicle with the practicality of a bicycle, but with a level of safety and comfort comparable to those of a small car, solves considerable problems for last mile deliveries, especially in large cities, which are considerably congested. In the tourist sector, on the other hand, a vehicle of this type can allow tourists to be transported in pedestrian areas and in the narrow historic centers of European cities (Fig. 3 and Table 1).

Fig. 3. The SNAP Cargo model on the left and the SNAP Cargo+ model on the right, they share the same platform.

Table 1. Comparison between Cargo and Cargo+ models SNAP Cargo

SNAP Cargo+

Wheels

24”

20”

Load Volume

350 L

1500 L

Unladen mass

160 kg

130 kg without box

Batteries

2 × 980 Wh (48 V) Li-ion cells

2 × 980 Wh (48 V) Li-ion cells

Range

55 km

60 km

This model starts from the same platform as the previous model, and, with a considerable reduction of parts and mass, it adapts to the purpose. In fact, the pillars have been modified, which stop at the rollbar, creating a considerable available load volume at the rear. The rims have also been reduced from 24” to 20” compared to the previous model, due to issues of commercial availability of spare parts. The elimination of the tailgate made it possible to reduce production costs, as did the elimination of the front doors. The Cargo+ model comes in its basic configuration, with a rear platform on which it is possible to install a box for the transport of goods, or seats for tourist transport.

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4 Cargo+ Longitudinal Dynamics Referring to the scheme of SNAP shown in Fig. 4, the longitudinal dynamics can be obtained as: Fp − (Fr + Fs + Fw ) = Max

(1)

Fig. 4. Longitudinal dynamics of the SNAP Cargo+

• • • • •

M includes the Cargo + vehicle mass (130 kg) and that of one driver (75 kg) Fp: tractive effort developed by the rear axis Fr: rolling motion resistance FS: motion resistance due to gravity FW: aerodynamic resistance, ρ the air density (1.2 kg/m3 ), Cd the aerodynamic resistance (0.64), A the front area of the vehicle (1.32 m2 ), and v the longitudinal speed. Then, the power balance at steady state is   1 2 Pmax = Mg sinα + fvMgcosα + ρCx AVmax Vmax = 250 W 2

(2)

We are going to carry out a study of the longitudinal dynamics of the new Cargo+ model to verify the differences compared to the previous model. Specifically, we will deal with the maximum slope that the vehicle can travel with and without a load. In the previous discussion, a power supplied by the motor equal to 250 W was imposed, but in the EN 15194 standard, the reference to the maximum power is 250 W considered as the “maximum continuous rated power”, which, if measured directly at the wheel, must be divided by 1.10 to account for the measurement interval (as prescribed by the EN 15194), and by a coefficient that takes into account the transmission losses that are not considered explicitly in Eq. (2). Therefore, after having evaluated [5] the overall efficiency of the transmission, we imposed a power equal to 250 W to the wheel, suitably calibrating the maximum current delivery of the motor, and obtaining the following graphs. The efficiency of the entire transmission, in fact, was measured to be equal to 83.5%, taking into consideration the electric motor, the gearbox, the differential, and the

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chain transmissions. The power to the crankshaft will therefore be equal to 299.4 W to be able to guarantee a maximum of 250 W to the wheel. This graph shows the maximum slope that the CARGO+ vehicle can overcome in the hypothetical case in which no power is supplied by the passenger, which however is not possible in reality as the engine only supplies if there is pedaling by the driver (Fig. 5).

Fig. 5. Maximum achievable speed as a function of road slope

In the case of an unladen vehicle, the maximum speed that can be traveled is approximately 22.5 km/h, which reduces to 18.50 km/h when fully loaded, equal to 150 kg on the cargo area. We now face the same aspect but considering the contribution provided by the pedaling of the driver. To quantify this contribution, we have to refer to specific studies relating to the human ability to generate power by pedaling. The human body, understood as a system capable of producing mechanical work, can be compared to a fuel cell vehicle, the chemical energy deriving from food, in fact, is converted directly into mechanical energy. The maximum efficiency with which chemical energy is converted into mechanical energy in humans is generally between 20% and 30%. The substantial difference is that the human body very often operates in conditions of maximum efficiency [6]. However, the mechanical power that the human body can deliver is highly variable, depending on the subject and depending on the duration of the delivery. Furthermore, unlike a vehicle, even in the presence of usable chemical energy, it is said that this cannot be converted into mechanical work. The measurement of the mechanical power produced by man through the pedals can be achieved through a measurement in the laboratory with an ergometer, or through a direct measurement on the moving vehicle. The results relating to the measurements of the mechanical power produced by man present in the literature, made using instruments, vary both with age [7] and of the physical condition of the subjects analyzed. As can be seen from the previous figure, given a certain period of time, the power that a professional subject is able to deliver continuously is much higher than that of an amateur subject. From the graph shown, we will consider the “NASA” curve relating to a “healthy man”, for a duration of 60 min, which supplies a maximum power value of approximately 200 W. At this point we will reduce this value by 50% to consider the case of an average user in a not particularly fit state of health, to add 100W of power supplied by the

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user to the contribution provided by the motor. Considering the pedaling contribution, cautiously set at 100 W, we obtain a maximum speed of 25.5 km/h which is reduced to 21.8 km/h in full load condition (Fig. 6):   1 2 Pmax_motor + Phuman = Mg sinα + fvMgcosα + ρCx AVmax Vmax = 250 W + 100 W 2 (3)

Fig. 6. On the left the man mechanical power as function of the duration of the effort [8]; on the right the maximum speed as a function of road slope with additional human contribution.

5 Static Stability In compliance with DIN79010, the static stability test involves verifying the stability of the vehicle in stationary conditions on an inclined plane under different load conditions and in different conditions. This test is also called “parking stability”, as it would be sufficient to carry it out without the driver. In our case the verification will be carried out both with and without the driver. The Cg is the point where we can consider all the mass of a vehicle concentrated and, consequently, where the resultant of the external forces acting on the vehicle can be considered as applied. In our case, the position of the Cg was identified with CAD design software used to model the entire vehicle, and an initial verification of the veracity of these results was carried out by comparing the data provided with the measurement carried out with 4 scales in the various conditions of load. The weight force acting on the Cg of the vehicle placed on a ramp can be split into two components: a rollover one (parallel to the ground) and a stabilizing one (perpendicular to the ground). The rollover component, multiplied by the height of the Cg, gives the rollover moment, while the stabilizing component, multiplied by the distance b, gives the stabilizing moment. The standard requires that the test is carried out with and without the load, but without the driver (Fig. 7). We will carry out the tests as in Table 2, it is assumed to have a uniformly distributed load in a truck body (1400 mm height, 1100 mm length and 1000 mm width). The purpose of the test is to verify that in all the tilt directions and inclinations envisaged by

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Tilt direction

Gradient (%) - Angle (α)

Longitudinal uphill and downhill

10% - 5,7°

Diagonal left and right

8% - 4,6°

Fig. 7. Static longitudinal stability, uphill on the left and downhill on the right (α = 5, 7°). Vehicle mass is 355 kg, check of the vehicle stability with driver and at full load.

DIN79010 a certain safety margin before rollover is always guaranteed. As an example, a graphical representation of the rollover check of the SNAP vehicle in the condition of 150 kg of load on the body is shown. Once the stability check had been carried out in all operating conditions and for all load conditions, we moved on to analyzing the check of the rollover limit slope. This study, not present in the DIN 79010, will help us to evaluate the limit conditions of use of the vehicle, and how similar these may be in daily use by the average user. In the 150 kg load condition we want to calculate the rollover limit slope, i.e., the slope beyond which the rollover (rear and front) and lateral (left and right) of the vehicle occurs. To calculate the rear rollover limit slope, it is sufficient to write the rotation equilibrium equation around the rear tire-ground contact point P. The rollover component, multiplied by the height hG of the Cg, gives the rollover moment, while the stabilizing component, multiplied by the distance b, gives the stabilizing moment (Fig. 8). If the Cg rises and moves back, hG increases and b decreases, with the consequent increase in the vehicle’s tendency to rollover. mgsenα × hG − mgcosα × b + Za × p = 0

(4)

where • • • •

hG: is the height of the center of gravity (Cg), p: is the vehicle wheelbase; b: is the distance between Cg and rear tire contact point P; Za: is the normal force on the front axle and Zp: on the rear axis; a: is the distance between Cg and the front tire contact point.

So, we can get Za, in order for the overturning condition not to occur, the two front wheels must not lose contact with the ground, so the following condition must be verified:

Overturning Stability for the SNAP Cargo Family

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Fig. 8. Static lateral stability, right and left (α = 4.6°). Vehicle mass is 355 kg, verification of the stability of the vehicle in condition with driver and at full load

Za > 0, from which it is possible to obtain the value of the limit slope (α < arctgb/hG). From this relationship we obtain the rollover longitudinal limit values in fully loaded static condition: α = 28, 0° uphill static stability limit and α = 58, 3° downhill static stability limit. We write the rotation equilibrium around the contact point A between the front tire and the ground: −Zd × t + mgcosα × a − mgsenα × hG = 0

(5)

For the overturning condition not to occur, the following condition must be verified: Zd > 0, from which it is possible to obtain the value of the limit left rollover limit and similarly obtain the value of the right rollover limit: tgα
0, LTres = (10) 0 otherwise. More specifically, the powertrain torque is defined as the sum of the engine and e-machine torque at the gearbox input: Tpwt = Teng + max (Tem τtc , 0).

(11)

Note that the e-machine torque was subject to lower saturation at zero in order to prevent its torque in generator mode being counted while using the powertrain in battery charging mode. Finally, available powertrain torque Tpwt,max was simply defined as (12) Tpwt,max = Teng,max + Tem,max τtc . Since both the engine and e-machine maximum torque are dependent on their speed, they are influenced by the gear engaged in the gearbox. Hence, the torque reserve penalty can be affected by the EMS by changing the gear number.

4

Case Study

In order to assess the effect of driveability constraints on the fuel-optimal control strategy, we implemented the simulation model described in the previous section in MATLAB and we used a dedicated dynamic programming solver called DynaProg [11] to obtain optimal control strategies with the cost functional formulated in Eq. 7. For the driving cycle, a combination of the Artemis Urban, Artemis Rural Road and Artemis Motorway 130 cycles was used as shown in Fig. 1, with a total length of 51 km and duration of 52 min.

Fig. 1. The simulated driving cycle.

With this framework, we developed four different cases by tuning the cost functional. In the first case, we set all driveability penalties to zero, considering

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fuel economy only as our objective. In the remaining three cases, we considered fuel economy and one driveability penalty at a time, disregarding the other two. In the remainder of this section, these strategies will be referred to as: a) b) c) d)

fuel-optimal: no penalty terms for driveability are considered. gear shift-penalty: fuel-optimal with a penalty term for gear shifting. engine start penalty: fuel-optimal with a penalty term for engine starts. torque reserve penalty: fuel-optimal with a penalty term for torque reserve.

The fuel-optimal strategy produced a fuel economy of 4.58 l/100km, an average of 18 gear shifts per minute and 3.1 engine starts per minute, with an average torque reserve of 58.3 %. The penalty factors for the other strategies were tuned with three separate parameter sweeps to obtain a sensible trade-off between fuel economy and each driveability objective. In particular, we aimed at less than one gear shift per minute for strategy b), less than 0.67 engine starts for strategy c) and an average torque reserve of at least 65 % for strategy d). The corresponding fuel consumption increase for each strategy is reported in Table 2. Table 2. Performance of the four strategies.

Fuel economy Gear shifts Engine starts Torque reserve #/min #/min % a) fuel-optimal

4.58 l/100 km 18

3.1

58.3%

b) gear shift-penalty

+1.6%

0.93

2.7

60.7%

c) engine start penalty

+3.2%

14

0.67

55.6%

16.4

3.3

65.8 %

d) torque reserve penalty +2.5%

Figure 2 shows the engine operating points throughout the mission for the four different strategies, color-coded based on the adopted operating mode. As expected, the engine tends to work near the optimal operating line (OOL) for the fuel-optimal control strategy. Introducing the gear shift penalty in b), the most notable difference is that the pure thermal operating points are now concentrated into two distinct and narrower speed ranges. These points are operated with the third and fourth gear engaged; clearly, the unconstrained strategy in a) uses frequent shifting between this two to move more points closer to the OOL. Considering the engine start penalty in c), we can note an increased usage of the pure thermal mode and a decrease in the usage of power-split mode, which is also evident from Table 3. In particular, this strategy makes a wider use of pure electric mode during the Urban phase of the driving cycle, discharging the battery, and uses the Rural Road phase to charge the battery back up; this is clearly visible from the state of charge profiles in Fig. 3. Still, the areas where the engine operating points concentrate remain similar. Finally, the effect of the torque reserve penalty in d) generates a large number of pure thermal points in the low-speed region of the map. These points are

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Fig. 2. Comparison of engine operating maps with four different cost functions.

Fig. 3. Comparison of the battery state of charge profile with the four strategies.

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Table 3. Time shares spent in each operating mode with the four strategies. Pure electric Pure thermal Power-split Battery charging a) fuel-optimal

42.8%

7.91%

26.2%

23.1%

b) gear shift-penalty

43.3%

6.64%

25.9%

24.1%

c) engine start penalty

61.8%

11.4%

8.42%

18.4%

d) torque reserve penalty 40.4%

17.6%

24.5%

17.5%

all points that provide a good trade-off between fuel economy and sportiness, because they are concentrated along the OOL and at the same time they leave the full torque of the e-machine, in its constant torque region, available. We now turn our attention to gear shift behavior in Fig. 4, which shows how the engaged gears relate to the vehicle speed and engine power; this is a typical analysis tool when designing gear shift schedules for automated transmissions. Note that only hybrid modes are represented, i.e. pure electric points are not depicted. Considering the fuel-optimal strategy in a), we observe that a clear shifting pattern emerges as the operating points are neatly separated based on the engaged gear. We also note that the first gear is almost never engaged, as low speed operation is driven almost exclusively in pure electric. Introducing a gear shift penalty in b), however, complicates the shifting behavior. Although it is still possible to identify preferred areas for each gear, there are significant overlays such as the third and fourth gear being engaged in the area previously reserved to the fifth gear at several speeds. This is likely a consequence of the strategy having to sometimes operate in a non-efficient way in order to limit the number of gear shifts. The strategy with a penalty for engine starts in c) instead shows a more regular shifting pattern; the most notable difference with respect to the fueloptimal strategy is a reduced usage of the fifth gear, which is mostly engaged at high power; further inspection revealed that these points were engaged in battery charging mode. Also noticeable is an increased usage of the third gear at higher power; these correspond to the additional pure thermal operating points. Finally, introducing the torque reserve penalty in d) generated a larger concentration of operating points at high power and high speed for the fourth and fifth gear, which correspond to the additional pure thermal and battery charging points that we previously observed in Fig. 2.

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Fig. 4. Comparison of gear shifting patterns with the four strategies. Only hybrid operating modes are represented (pure electric points are not shown).

5

Conclusions

In this work, we implemented dynamic programming to investigate the effect of three different driveability constraints on the optimal energy management strategy for a p2 parallel hybrid. The constraints were implemented by adding three different penalty terms to the base cost of the optimal control problem, which is fuel consumption. By testing each penalty term individually, we were able to assess the impact of each corresponding driveability aspect on a set of relevant features of the control strategy, such as the choice of engine operating points and the gear shift pattern. These considerations provide useful insight for the development of real-time, rule-based control strategy that minimize fuel consumption while preventing unrealistic and potentially damaging gear shifting and engine start/stop behavior, as well as targeting varying levels of sportiness.

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References 1. Anselma, P.G.: Computationally efficient evaluation of fuel and electrical energy economy of plug-in hybrid electric vehicles with smooth driving constraints. Appl. Energy 307 (2022). https://doi.org/10.1016/j.apenergy.2021.118247 2. Anselma, P.G., Biswas, A., Belingardi, G., Emadi, A.: Rapid assessment of the fuel economy capability of parallel and series-parallel hybrid electric vehicles. Appl. Energy 275 (2020). https://doi.org/10.1016/j.apenergy.2020.115319 3. Anselma, P.G., Spano, M., Capello, M., Misul, D., Belingardi, G.: Calibrating a real-time energy management for a heavy-duty fuel cell electrified truck towards improved hydrogen economy. In: SAE Technical Paper Series. SAE International, June 2022. https://doi.org/10.4271/2022-37-0014 4. Guzzella, L., Sciarretta, A.: Vehicle Propulsion Systems Introduction to Modeling and Optimization. Springer, London (2007) 5. Leroy, T., Malaiz´e, J., Corde, G.: Towards real-time optimal energy management of HEV powertrains using stochastic dynamic programming. In: 2012 IEEE Vehicle Power and Propulsion Conference, pp. 383–388, October 2012. https://doi.org/10. 1109/VPPC.2012.6422661. ISSN: 1938-8756 6. Li, L., Yan, B., Yang, C., Zhang, Y., Chen, Z., Jiang, G.: Application-oriented stochastic energy management for plug-in hybrid electric bus with AMT. IEEE Trans. Veh. Technol. 65(6), 4459–4470 (2016). https://doi.org/10.1109/TVT.2015. 2496975 7. Lin, C.C., Kang, J.M., Grizzle, J., Peng, H.: Energy management strategy for a parallel hybrid electric truck. In: Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), vol. 4, pp. 2878–2883, June 2001. https://doi. org/10.1109/ACC.2001.946337 8. Lin, C.C., Peng, H., Grizzle, J., Kang, J.M.: Power management strategy for a parallel hybrid electric truck. IEEE Trans. Control Syst. Technol. 11(6), 839–849 (2003). https://doi.org/10.1109/TCST.2003.815606 9. Mansour, C.J.: Trip-based optimization methodology for a rule-based energy management strategy using a global optimization routine: the case of the Prius Plug-in hybrid electric vehicle. Proc. Inst. Mech. Eng. Part D: J. Automob. Eng. 230(11), 1529–1545 (2016). https://doi.org/10.1177/0954407015616272 10. Miretti, F., Misul, D.: Robust modeling for optimal control of parallel hybrids with dynamic programming. In: 2022 IEEE Transportation Electrification Conference & Expo (ITEC), pp. 1015–1020, June 2022. https://doi.org/10.1109/ITEC53557. 2022.9813982 11. Miretti, F., Misul, D., Spessa, E.: DynaProg: deterministic dynamic programming solver for finite horizon multi-stage decision problems. SoftwareX 14, 100690 (2021). https://doi.org/10.1016/j.softx.2021.100690 12. Miro-Padovani, T., Colin, G., Ketfi-Ch´erif, A., Chamaillard, Y.: Implementation of an energy management strategy for hybrid electric vehicles including drivability constraints. IEEE Trans. Veh. Technol. 65(8), 5918–5929 (2016). https://doi.org/ 10.1109/TVT.2015.2476820 13. Onori, S., Serrao, L., Rizzoni, G.: Hybrid Electric Vehicles Energy Management Strategies. Springer, London (2015). https://doi.org/10.1007/978-1-4471-6781-5 14. Opila, D.F., Wang, X., McGee, R., Gillespie, R.B., Cook, J.A., Grizzle, J.W.: An energy management controller to optimally trade off fuel economy and drivability for hybrid vehicles. IEEE Trans. Control Syst. Technol. 20(6), 1490–1505 (2012). https://doi.org/10.1109/TCST.2011.2168820

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15. Peng, J., He, H., Xiong, R.: Rule based energy management strategy for a seriesparallel plug-in hybrid electric bus optimized by dynamic programming. Appl. Energy 185, 1633–1643 (2017). https://doi.org/10.1016/j.apenergy.2015.12.031 16. Vidal-Naquet, F., Zito, G.: Adapted optimal energy management strategy for drivability. In: 2012 IEEE Vehicle Power and Propulsion Conference, pp. 358–363, October 2012. https://doi.org/10.1109/VPPC.2012.6422678

Torsional Dynamic Performance of a Transmission Test Bench: An Investigation on the Effect of Motors Controllers Parameters Enrico Galvagno(B) , Mauro Velardocchia, Antonio Tota, Luca Zerbato, and Angelo Domenico Vella Department of Mechanical and Aerospace Engineering, Politecnico Di Torino, 10129 Turin, Italy {enrico.galvagno,mauro.velardocchia,antonio.tota,luca.zerbato, angelo.vella}@polito.it

Abstract. Besides in-vehicle testing, automotive powertrains and their subsystems are extensively studied and verified, in the different development phases, through dedicated test benches having various mechanical layouts according to the specific target. The torsional load is typically applied to the transmission by electric motors connected at both ends of the driveline. The electric motors drives allow speed and torque closed-loop control so that the desired combination of speed and torque can be imposed over time during the experiment. The parameters of such controllers therefore play a crucial role in the torsional dynamic behavior of the bench and therefore must be carefully selected and tuned to achieve optimal reference tracking and disturbance rejection performance. This paper aims at proposing a model-based sensitivity analysis of the PID controllers parameters starting from an experimentally validated torsional model of a Dual Clutch Transmission test rig. The methodology here proposed also contributes to achieving the Sustainable Development Goal 11 promoted by ONU. Keywords: SDG 11 · Powertrain · Transmission testing · Electric motors speed control · Dynamic modelling · Experimental model validation · Torsional vibrations

1 Introduction Nowadays, automotive powertrains are experimentally analyzed by performing both invehicle and lab testing. Lab testing of transmission covers many different aspects [1] such as, functional verifications, endurance, shiftability, NVH ([2–4]) and transmission control unit calibration. Modern transmission hardware-in-the-loop (HiL) test benches, like the one used in this study (Fig. 1, [5, 6]), are utilized to test the performance of a transmission as if it were mounted in a real car. The torsional loads are applied at both ends of the mechanical transmission through torque actuators made of electric servo motors which are commanded in a fashion that exactly simulates the loads a transmission encounters in a vehicle [7]. Since the two electric motors are mechanically connected to the input © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 441–447, 2023. https://doi.org/10.1007/978-3-031-32439-0_50

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and output of the same driveline, a mutual influence of the settings of the two motor controllers is expected and will be investigated in this paper. The use of simulation model, e.g. for HiL application, to compute realistic load conditions [8] requires highly dynamic drives for its effective actuation. The dynamic performance of the testing system strongly depends on the calibration of the motor drives, more specifically on the tuning of PID speed and torque controllers. However, the effect of motors controllers tuning on the torsional behavior of the bench, supported by an experimentally validated model, is not extensively studied in the literature. Finally, this paper also contributes to the aims of the SDGs. More specifically, target 11.2 of SDG11 is to “provide, by 2030, access to safe, affordable, accessible and sustainable transport systems for all, improving road safety…”. Since the most recent and innovative powertrains require accurate calibration procedures due to their higher technological level, the methodology here proposed can be also applied to them, fostering the transition towards the zero emission transport systems. Moreover, HIL testing replaces the need of in-vehicle experiments, thus improving safety and reducing the risk of drivers and test engineers injuries. The paper is structured as follows: after a description of the transmission test bench, a model for the simulation of its torsional behavior is proposed including the electric motors PID controllers, followed by a sensitivity analysis of the main controller parameters on reference tracking and disturbance rejection performance. Finally, remarks and conclusions are drawn.

2 Transmission Test Rig Description As depicted in Fig. 1, the test bench is made of two opposing electric motors (M1 and M2), each followed by a torque meter (T1 and T2) and equipped with a speed sensor (EM1 and EM2). Two opposing gearboxes (a manual transmission MT and a dual clutch transmission DCT, both with a locked differential) followed by a half shaft are mounted in the central part of the bench between the two motors. The transmission under test is the DCT, while the other one, the MT, is used as a speed reducer. Therefore, M1 acts as the prime mover (engine), while M2 simulates the vehicle loads (aerodynamics, rolling, grade and inertial). Each electric drive can be set to ensure that the electric motor accurately tracks a torque or a speed profile. For the rest of the paper we assume to work in the common condition in which the electric motor M1 is torque controlled (it applies the engine torque to the transmission input shaft), while M2 is speed controlled (it imposes the wheel speed). Both these controllers are digitally implemented on dedicated processors, located in the electric drive in the cabinet. On industrial drives the controller is typically a PID one; the user can change the parameters, i.e. the proportional, integral and derivative gain, the time constant and the saturation limits but the control algorithm structure cannot be modified. Therefore, it interesting to understand the effect of these parameters on the torsional dynamic performance of the test bench and to define a method to tune them starting from the performance setting.

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Fig. 1. A Picture (top) and a scheme (bottom) of the transmission test bench in the Mechanical Laboratory of Politecnico di Torino.

3 Modelling and Simulation First of all, to predict via numerical simulation the effect of different controller calibrations on system performance, a validated dynamic model of the system is needed. Investigations on the minimum number of torsional degrees of freedom and on the spatial distribution of the lumped inertias were performed to reach a good matching between simulation and experiment up to a maximum frequency of 100 Hz. An appropriate mechanical model of the rotating system installed on the bench was identified and reported in Fig. 2. It features 6 torsional degrees of freedom, and the system compliances are located in the dual mass flywheel (stiffness KDMF ), in the two gearboxes (KGB1 and KGB2 ) and in the half-shafts (KSA1 and KSA2 ). The viscous damping parameters ci in Fig. 2, are identified through curve fitting applied to the system transfer functions that can be directly estimated from measures.

Fig. 2. Mechanical model of the transmission test bench.

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Fig. 3. Experimental model validation in frequency domain.

The experimental validation of the model was performed by analyzing its open-loop behavior. As an example, the modulus and phase of the model transfer function from M2 torque (TM2 ) to M2 speed (ωM2 ) is compared with the one identified from experimental data during a sine sweep test in Fig. 3. The resonance and anti-resonance peaks are pretty well captured by the model, while bigger differences can be seen in the phase plot, which is much more affected by the oversimplified linear damping model. M1 is modelled as an ideal torque actuator able to apply the refence torque T1,ref to the mechanical system (left part of Fig. 2), while the torque applied by M2 is the output of a PID speed controller depicted in the upper right part of the scheme. Alternative solutions exist in literature for the definition of the PID structure, e.g. the proportional and derivative terms can be placed in the feedback signal rather in the feedback error [9]. The state space model of the controlled dynamic system is then derived and used to study the refence speed tracking (RST) and disturbance rejection (DR) performance.

4 Effect of PID Controller Gains Considering the HiL application of the test bench, the task of the M2 speed controller is to track the reference wheel speed calculated by the vehicle load simulation model, corresponding to the degree of freedom nr.4 of the torsional model. This transfer function will be called reference speed tracking (RST). The second relevant transfer function is the Disturbance Rejection (DR) FRF that is used to monitor the M2 speed controller sensitivity to the application of the M1 motor torque. An optimal tuning of the speed controller is presented in [6] with the aim of achieving the desired level of reference tracking and disturbance rejection targets. The performance of the closed loop system can be set by limiting the peaks of the FRF amplitudes of both RST and DR and by requesting a minimum bandwidth for the RST. A sensitivity analysis is also recommended to investigate the influence of main tunable parameters on the aforementioned FRFs.

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As shown in Fig. 4, the proportional gain affects the resonance peaks of the FRFs. Increasing Kp improves the reference tracking performance by increasing the damping of the first peak and by extending the closed-loop bandwidth. However, the system behavior becomes worse in the mid-high frequency range, the peaks outside the bandwidth become more pronounced as the proportional gain increases. Too high proportional gain may provoke excessive oscillations of the internal driveline components leading to NVH issues.

Fig. 4. Effect of the proportional gain Kp on the reference speed tracking GRST and disturbance rejection GDR transfer functions of the closed loop system.

Fig. 5. Effect of the integral gain Ki on the reference speed tracking GRST and disturbance rejection GDR transfer functions of the closed loop system.

The integral contribution (see Fig. 5) can shift the resonance frequency of the first peak since it acts as an additional stiffness in the dynamic system applied to the last

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Fig. 6. Effect of the derivative gain Kd on the reference speed tracking GRST and disturbance rejection GDR transfer functions of the closed loop system.

degree of freedom (motor M2). Increasing the integral gain leads to an extension of the closed-loop bandwidth of RST FRF but associated to a more pronounced peaks amplitude in the whole frequency range. Moreover, it produces a shift of the DR FRF first resonance peak towards higher frequencies, and it reduces the frequency bandwidth around the peak. As can be seen in Fig. 6, the derivative gain affects the peaks amplitude, but not their frequency. The advantage of a high derivative gain is the attenuation of the first peak for the RST, but this also leads to an increment in the peak amplitudes for higher frequencies. The increment of Kd benefits the DR FRF because the vibration amplitude is attenuated in the whole frequency range.

5 Conclusions The paper presents a model-based approach to study the effect of the electric motor controller calibration on the reference tracking and disturbance rejection performance of a transmission test rig. The sensitivity analysis helps to understand the effect of each mechanical and control parameter on the system dynamics thus guiding the calibration process. The torsional dynamics modelling and vibration analysis of the system revealed the presence of underdamped modes that are excited in case of too high PID gains or high frequencies noises related to feedback signals. This suggests a speed controller design that includes the model of the internal dynamics of the whole transmission and driveline to predict potential NVH issues during the normal operation of the bench. Finally, the paper contributions can be summarized by the following novelty points: • a model-based methodology is presented for the controller design by integrating an experimentally validated torsional mechanical model of the transmission with the control loops of the electric motors;

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• the high-frequency torsional modes, included into the mechanical model here proposed, allow the verification of the resonance conditions influenced by the controller parameters tuning.

References 1. Lechner, G., Naunheimer, H.: Automotive Transmissions, Fundamentals, Selection, Design and Application. Springer, Berlin (1999) 2. Galvagno, E., Tota, A., Velardocchia, M., Vigliani, A.: Enhancing transmission NVH performance through powertrain control integration with active braking system. In: SAE technical paper, SAE 2017 Noise and Vibration Conference and Exhibition, Grand Rapids, pp. 1–6. Michigan, USA (2017) 3. Galvagno, E., Guercioni, G.R., Vigliani, A.: Sensitivity analysis of the design parameters of a dual-clutch transmission focused on NVH performance. SAE Technical Paper 2016-01-1127 (2016) 4. Galvagno, E., Dimauro, L., Mari, G., Velardocchia, M., Vella, A.D.: Dual clutch transmission vibrations during gear shift: a simulation-based approach for clunking noise assessment. SAE Technical Paper 2019-01-1553 (2019) 5. Galvagno, E., Velardocchia, M., Vigliani, A.: Torsional oscillations in automotive transmissions: experimental analysis and modelling. Shock Vib. 2016, 1–14 (2016) 6. Galvagno, E., Tota, A., Mari, G., Velardocchia, M.: Model-based calibration of transmission test bench controls for hardware-in-the-loop applications. In: Parikyan, T. (ed.) Advances in Engine and Powertrain Research and Technology. MMS, vol. 114, pp. 309–341. Springer, Cham (2022) 7. Castiglione, M., Stecklein, G., Senseney, R., Stark, D.: Development of transmission hardwarein-the-loop test system. SAE Technical Paper 2003-01-1027 (2003) 8. Schnabler, M., Stifter, C.: Model-based design methods for the development of transmission control systems. Conference Paper, SAE International, 0148-7191 (2014) 9. Leonhard, W.: Control of Electrical Drives. Springer Science & Business Media (2001)

Special Session: Service Systems for Sustainability (coordinated by Maria Cristina Valigi)

Sustainable Design of Machine Guards Luca Landi, Silvia Logozzo(B) , and Maria Cristina Valigi Dipartimento di Ingegneria, Università degli Studi di Perugia, Perugia, Italy {luca.landi,silvia.logozzo,mariacristina.valigi}@unipg.it

Abstract. Promoting sustainable industrialization by fostering safety of machinery is a fundamental and ethical approach. Working in safe conditions is essential to comply with the UN’s Sustainable Development Goals (SDG) and, in particular, with SDG3 and SDG8, therefore making machines safer during their operation becomes a basic aim for a more sustainable society. From this perspective, the influence of certain design or/and physical parameters on machine safety must be necessarily analyzed even if standards do not consider them, with obvious advantages also in terms of industrial innovation, complying with SDG9. The present work refers to the study of machine protection panels to characterize their ability to resist ballistic penetration. In ISO 14120-Annex B, the methodologies and standards for the design and validation of machine guards are described, but the influence of many characteristics and parameters has not been considered to characterize the protection performance. This paper presents some results in the terms of withstanding capacity of polycarbonate panels to ballistic penetration considering the size of the guards and their ageing condition due to solar radiation. The analyses for the inspection of the through-hole cracks and deformation of the panels have been performed with an innovative method by using a metrology grade 3D optical scanner and 3D inspection techniques. Keywords: SDG3 · SDG8 · SDG9 · machine guards · safety of machinery · ejection risk · 3D scanner inspection

1 Introduction In recent years, a safe and integrated management of the production systems is becoming more and more important for the manufacturer companies. According to the regulatory obligations set off by regulations like the EU Directive 2006/42/EC on machinery, or the ISO 45001 regarding occupational health and safety, the risk reduction process can be divided into three main phases: – Application of protective measures integrated into the design. – Application of complementary protections and protective measures. – Use of information to reduce residual risks that cannot be further reduced by other means.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 451–458, 2023. https://doi.org/10.1007/978-3-031-32439-0_51

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With regards to the complementary protection devices, the mechanical designers are in charge of identifying the type of protection tools which are able to adequately reduce the residual risk of accidents. Machine guards fall among those complementary protection systems and they are defined in the standard ISO 14120 [1] as physical barriers, designed as part of the machine for the protection of operators. This paper focuses on this kind of protection systems and experimental tests have been performed to investigate the influence of some physical quantities and parameters on the withstanding capacity to ballistic penetration [2–4]. The design and testing of machine safety guards are performed in agreement with ISO 14120 that oversimplifies the actual conditions that may occur during a machining process as the ejection risk of small parts or tool tips. The standards do not take into account the machine guards’ size and the ageing conditions of the panels due to solar radiation. In this paper, the characterization of polycarbonate machine guards is carried out by ballistic tests in compliance with ISO 14120 with the aim of evaluating their withstanding capacity to penetration due to impacts with ejected tools or particles of material during machining. The analysis of deformation is performed using an innovative method which implies the use of 3D optical scanners and 3D inspection techniques [5, 6], which can have a wide application in several fields to enhance the sustainability of work and processes, as reported in [7–9]. Applications in the field of human health are reported in [10, 11], as well as in robotics oriented to human augmentation [12, 13] and in applications focused on the optimization of machines, components and processes in [14, 15]. Since the topic of the work regards the safety of the machinery and consequently the protection and well-being of human workers, it can help to meet some of the UN’s Sustainable Development Goals (SDG) for achieving a healthier planet. In particular, the topic of this paper is oriented at the achievement of SDG3 (Good health and well-being) promoting health and well-being of human workers due to a safer and decent work, which is also one of the objectives of SDG8 (Decent work and economic growth). Moreover, the effort focused on the realization of safer machinery leads to the development of innovative sustainable solutions in industry and of high quality and reliable infrastructures, which is in agreement with the objectives of SDG9 (Industries, innovation and infrastructure) [16, 17]. The paper is organized as follows: paragraph 1.1 reports some insights about the actual standardization of ballistic tests and ballistic limit evaluation; Sect. 2 focuses on materials and methods employed for the impact tests and ageing process; Sect. 3 deals with the deformation tests reporting the used innovative method, instruments, and results; Sect. 4 reports the conclusions. 1.1 Background Machine guards are both mobile and fixed, with the associated interlocking devices. The combination of such devices makes it possible to protect persons from dangers that can be generated by moving parts or due to an eventual ejection of tools or particles and avoiding the access to dangerous zones. In this paper the guards are considered as a protection against the risk of hazardous impacts due to the ejection of swarf, small parts, or tools of machines (see Fig. 1).

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Fig. 1. Ejection of swarf.

Standard regulations prescribe ballistic tests to be performed by means of compressed air guns, with standardized shapes and sizes of steel projectiles, as described in [1]. The prediction of the guard’s withstanding capacity is evaluated just with a single shot and considering the visual evaluation of the test panel’s damage: if a through-hole crack is generated the machine guard is not safe and it cannot be installed. Machine guards are considered safe if they present just plastic deformations and no through-hole cracks after the impact test. The tests must be performed with the maximum foreseeable tangent spindle speed of the machine. The most reliable theoretical method to forecast the ballistic limit of a machine guard is based on the ballistic penetration theory represented by the well-known Recht and Ipson (R&I) equation [18, 19]. The theory allows to calculate the ballistic limit velocity (V bl ) of a panel, given its thickness, being V bl defined as “the minimum velocity required by a projectile to completely penetrate a target”. The R&I equation proposes two dimensionless parameters, p and a, where p is an exponential parameter which can be determined with regression methods and a is: a = mp /(mp + mpl )

(1)

where mp is the projectile mass, and mpl is the plug mass (a < 1 except when the plug is absent; in that case a = 1). The R&I equation is used to determine the ballistic limit velocity (V bl ) in function of the impact velocity (V i ), and the residual velocity (V r ) of the projectile: p

p

Vr = a (Vi − Vbl )1/p

(2)

2 Impact Tests and Ageing Process 2.1 Materials and Methods for Impact Tests The inadequacy/suitability of the tested materials for machine guards is investigated analyzing the perforation/not perforation of the guard in a standardized impact test. The used equipment for impact tests redrawn from ISO 14120 is showed in Fig. 2 and it consists of a velocimeter (1), a gun barrel (2), the projectile (3), a control panel (4), the test panel which is clamped with an adjustable support frame (5), a compressed air

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Fig. 2. Equipment for impact test: a) test setup (1) velocimeter, (2) gun barrel, (3) projectile, (4) controller, (5) frame, (6) vessel; b) projectile shape.

vessel (6). The shooting tests were performed using the gas cannon of Monte Porzio Inail laboratories in Rome. The velocimeter used in this test to measure Vi and Vr was a high-speed camera Phantom V710 (Vision Research, Ametek, Wayne, NJ, USA) which allowed to study and experimentally evaluate the impact mechanics. Tests were performed at a 10000 fps with a resolution of 912 × 304 pixels. The projectile was fired by the air gun, through the sample guard that was positioned and clamped on a rigid and resilient support system. The standard projectile had a mass of 0.10 kg and a diameter of 20 mm and with a flat impact area equal to 10 × 10 mm [20]. The standardized tests imply a perfect perpendicular impact and for this reason, after some tests using the high-speed camera for the measurement of the impact angle, the distance to achieve a perpendicular impact was evaluated and fixed at 41 cm. The following figures show different result configuration after the impact on different sample guards. In particular, Fig. 3a shows bulging without cracks through the whole thickness that is a valid result for the panel’s safety; on the contrary Fig. 3b and 3c show a though-hole crack and a complete penetration that demonstrate that the panels are not safe.

Fig. 3. Different penetration configuration on different sample guards: a) bulging; b) through-hole crack; b) penetration.

2.2 Materials and Methods for Ageing Tests Solar radiation and temperature influence the ageing of polymers such as polycarbonate since they affect the rate of chemical reactions leading to the degradation of the material. For this reason, a campaign was carried out by accelerating the ageing process of the sample panels during storage to simulate the indoor ageing before their use. Therefore, an artificial system with fluorescent lamps characterized by radiant emission in the ultraviolet (UV) region of the spectrum was used. Figure 4 shows a schematic sectional

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view of the device used as ageing tester to obtain accelerated ageing of the test panels and using different types of fluorescent UV lamps with unique spectral characteristics.

Fig. 4. Schematic section of the accelerated ageing tester.

The adopted ageing cycle involved continuous exposure of the panels to light radiation, with constant temperature and lamp irradiation, without cycles of darkness and/or condensation, so that a substantial reduction of the exposure time for the occurrence of ageing is obtained. The panels’ conditioning simulated the ageing equivalent to one year exposure, for panels placed in a vertical position and stored outdoors but sheltered from the environmental elements. The temperature of the polycarbonate sheets during the accelerated tests was controlled at 52 °C considering solar irradiation conditions typical of the central Italy and in particular of the Umbria region. The equivalence of the expected simulated ageing of one year is based on the equivalence of energy in terms of equivalent exposure (J) and temperature.

3 Deformation Analysis and Results Deformation analyses were performed on 4 samples of polycarbonate panels of 4 mm thickness among a series of samples which underwent ballistic impact tests and the ageing process. The considered samples were two square panels with a dimension of 300 × 300 mm, and two with a dimension of 500 × 500 mm. For each dimension, one of the panels was aged and one was new. Deformation analyses were performed using the optical 3D laser scanner FreeScan UE7 by Shining 3D, and the 3D inspection software by Geomagic with the aim of generating 3D deformation maps displaying the slump and bulging of the guards after the impact tests, highlighting the deformation differences between panels with different dimensions and different ageing conditions. Acquisitions were done with a resolution between 0.2 mm and 1 mm and a volumetric accuracy of 20 µm + 40 µm/m. Being the sample panels transparent, they were coated with a sublimating 3D scanning spray to perform the laser scanning and they were mounted on a clamping support. The support clamps the panel’s edge reducing the free surface of 50 mm for each dimension. Physical circular targets were applied on the support to allow a real-time acquisition with a portable 3D digitizing device (Fig. 5). The 3D scan models were 3D inspected by comparing the guards with different dimensions and same ageing condition and with the same dimensions and different ageing conditions.

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Fig. 5. 3D scanning session of one sample.

3.1 Deformation Analysis for Different Dimensions Results of one of the 3D inspections on two panels with different sizes and same ageing condition is reported in Fig. 6 representing the deformation maps.

Fig. 6. Deformation map comparison for different panel sizes: a) size 500 × 500 mm, V i = 77 m/s, air pressure 10.5 bar; b) size 300 × 300 mm, V i = 79 m/s, air pressure 11 bar.

As envisaged in [20], one can notice that the deformation diameter is not influenced by the panel size, as both the panels present a bulging in diameter of about 300 mm around the impact zone. This means that the withstanding capacity of the studied panels to ballistic penetration is not influenced by the panel’s dimensions for realistic working conditions. 3.2 Deformation Analysis for Different Ageing Conditions The deformation map of the 300 × 300 mm aged and new panels is reported in Fig. 7 with the aim of comparing the ballistic limit of panels with same size and different ageing conditions, to highlight any significant effect in terms of reduced or improved impact resistance caused by ageing. Results show that the deformation range and therefore the withstanding capacity to ballistic penetration of the guards is not affected by the ageing condition, as the deformation diameters are comparable.

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Fig. 7. Deformation map of 300 × 300 mm panels: a) aged; b) new, V i = 79 m/s, pressure 11 bar.

4 Conclusions This paper was focused on the characterization of the resistance of polycarbonate machine guards to ballistic penetration due to the ejection of swarf, small parts, or tools during the machining aimed at a sustainable design of machine guards. The main aim of the work was to determine if the size of the protection panels and the ageing condition due to solar radiation would affect the deformation and withstanding capacity of the guards. The deformation analysis was conducted by 3D optical scanning techniques which demonstrated that, given the same polycarbonate material, thickness, and projectiles, both the panel size and the ageing condition due to the exposure to solar radiation have a neglectable effect on the resistance of panels bigger than 300 × 300 mm size. In fact, the deformation maps showed that there is an equivalent distribution of plastic deformation due to the impact both for panels of different sizes and for different ageing condition, for a minimum panel size of 300 x 300 mm. Results of this work give new insights to enhance the regulations about impact test procedures and safety standards for machines’ protections. Being focused on the enhancement of the machinery’s safety, this paper gives a contribution to sustainability with regards to SDG3, SDG8 and SDG9. In fact, reliable machine guards allow a proper protection of human workers promoting healthy/decent working conditions, as well as the innovation progress of companies in the field of the development of new technological solutions oriented to sustainability in industry and infrastructure.

References 1. UNI: Safety of Machinery Guards: General Requirements for the Design and Construction of Fixed and Movable Guards. UNI EN ISO 14120 (2015) 2. Stecconi, A., Landi, L.: Finite element analysis for impact tests on polycarbonate safety guards: comparison with experimental data and statistical dispersion of ballistic limit. ASCEASME J. Risk Uncertain. Eng. Syst. Part B: Mech. Eng. 6(4) (2020) 3. Landi, L., Mödden, H., Pera, F., Uhlmann, E., Meister, F.: Probabilities in safety of machinery – risk reduction through fixed and moveable guards by standardized impact tests, part 1: applications and consideration of random effects. In: Safety and Reliability - Theory and Applications - Proceedings of the 27th European Safety and Reliability Conference, ESREL 2017, pp. 2155–2164 (2017)

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4. Landi, L., Uhlmann, E., Meister, F., Pera, F., Mödden, H.: Probabilities in safety of machinery – risk reduction through fixed and moveable guards by standardized impact tests, part 2: possible improvements with FE impact simulations. In: Safety and Reliability - Theory and Applications - Proceedings of the 27th European Safety and Reliability Conference, ESREL 2017, pp. 1967–1975 (2017) 5. Valigi, M.C., Logozzo, S., Meli, E., Rindi, A.: New instrumented trolleys and a procedure for automatic 3D optical inspection of railways. Sensors 20(10) (2020). Art. 2927 6. Valigi, M.C., Logozzo, S., Butini, E., Meli, E., Marini, L., Rindi, A.: Experimental evaluation of tramway track wear by means of 3D metrological optical scanners. In: Proceedings of the 11th International Conference on Contact Mechanics and Wear of Rail/Wheel Systems (CM2018), pp. 1007–1012 (2018) 7. Logozzo, S., Valigi, M.C.: Wear assessment and reduction for sustainability: some applications. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 395–402. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-87383-7_43 8. Logozzo, S., Valigi, M.C.: Green tribology: wear evaluation methods for sustainability purposes. Int. J. Mech. Control 23(01), 23–34 (2022) 9. Valigi, M.C., Logozzo, S., Braccesi, C.: Contact models and reduction of instabilities in sealing rings for sustainability purposes. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 412–420. Springer, Cham (2022). https://doi.org/ 10.1007/978-3-030-87383-7_45 10. Affatato, S., Valigi, M.C., Logozzo, S.: Knee wear assessment: 3D scanners used as a consolidated procedure. Materials 13(10) (2020). Art. 2349 11. Valigi, M.C., Logozzo, S., Affatato, S.: In vitro 3D wear characterization of knee joint prostheses. Mech. Mach. Sci. 73, 3855–3863 (2019) 12. Achilli, G.M., Logozzo, S., Malvezzi, M., Valigi, M.C.: Contact mechanics analysis of a soft robotic fingerpad. Front. Mech. Eng. 8 (2022). Art. 966335 13. Logozzo, S., Valigi, M.C., Malvezzi, M.: A methodology to evaluate contact areas and indentations of human fingertips based on 3D techniques for haptic purposes. MethodsX 9 (2022). Art. 101781 14. Valigi, M.C., Logozzo, S., Gasperini, I.: Study of wear of planetary concrete mixer blades using a 3D optical scanner. In: ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE) 15-2015 (2015) 15. Valigi, M.C., Fabi, L., Gasperini, I.: Wear resistance of new blade for planetary concrete mixer. In: 5th world Tribology Congress, WTC 2013, vol. 2, pp. 1208–1211 (2013) 16. Okokpujie, I.P., Fayomi, O.S.I., Oyedepo, S.O.: The role of mechanical engineers in achieving sustainable development goals. In: Procedia Manufacturing (Proceedings of the 2nd International Conference on Sustainable Materials Processing and Manufacturing, SMPM 2019), vol. 35, pp. 782–788 (2019) 17. Nosonovsky, M., Bhushan, B.: Green tribology: principles, research areas and challenges. Phil. Trans. Roy. Soc. A 368, 4677–4694 (2010) 18. Recht, R.F., Ipson, T.W.: Ballistic perforation dynamics. J. Appl. Mech. Trans. ASME 30(3), 384–390 (1960) 19. Børvik, T., Langseth, M., Hopperstad, O.S., Malo, K.A.: Ballistic penetration of steel plates. Int. J. Impact Eng. 22(9), 855–886 (1999) 20. Landi, L., Logozzo, S., Morettini, G., Valigi, M.C.: Withstanding capacity of machine guards: evaluation and validation by 3D scanners. Appl. Sci. 12(4) (2022). Art. 2098

Robotic System for Hand Rehabilitation Based on Mirror Therapy Monica Tiboni(B) , Amici Cinzia , and Bussola Roberto Department of Mechanical and Industrial Engineering DIMI, University of Brescia, Brescia 25085, Italy {monica.tiboni,cinzia.amici,roberto.bussola}@unibs.it

Abstract. The paper presents the study of a system composed by a sensorized glove that could interface with GLOREHA Lite hand exoskeleton. The movement of each GLOREHA’s motor acts on the flexion or extension of the corresponding finger through a cable transmission, allowing the user to carry out robot-assisted rehabilitation therapy for the hand. The combined use of GLOREHA and of the sensing glove allows performing a bimanual therapy using the Mirror Therapy technique, with the effect of increasing the effectiveness of the treatment. A test bench was used for the characterization of the bending sensors inserted into the sensing glove to detect flexion and extension of the fingers. Two sensor gloves were developed; one made of tissue, where the sensors are inserted into appropriate seams, and one made of Silicon, where the sensors were incorporated between two layers of material. Both solutions proved to be adequate. The characterised sensors have shown performances suitable for this type of application, while the tests on the responsiveness of GLOREHA to the command signal are good for both serial and Bluetooth communication. The presented system favors the achievement of the objectives of pillar three of the sustainable development goals (SDG): good health and well-being. An effective rehabilitation activity at home can allow a greater number of people, compared to the current one, to more quickly recover the motor functions of the hand.

Keywords: SDG3

1

· Robotic Rehabilitation · Mirror Therapy

Introduction

In many Western nations, stroke is the primary cause of adult chronic disability. The restoration of motor skills is an essential issue of rehabilitation research, and current study has concentrated on hand recovery. Robotic-assisted therapy has been shown to be useful in hand rehabilitation [1]. GLOREHA (GLOve REhabilitation HAnd) is a neuron-motor rehabilitation device that has been shown to be beneficial for hand recovery [2]. GLOREHA can be used passively or actively. Robot-assisted rehabilitation uses robotic equipment and has the benefit of enabling an endless number of repetitions of a certain c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 459–467, 2023. https://doi.org/10.1007/978-3-031-32439-0_52

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action without the constant active intervention of the therapist, saving a large amount of human effort that can lead to high expenses. These devices enable simple activities, such as passive mobility, as well as complicated ones, such as continuous help across the range of motion [3–6]. Furthermore, robot-assisted rehabilitation can give highly accurate quantitative assessments of performance. It has been shown that robotics can increase rehabilitation accessibility: the patient chooses to utilize the healthy limb in daily activities, so aiding the healing of the damaged limb. Moreover, the option of doing therapy at home with robotic equipment might help the patient become more involved in the recovery process. Mirror Therapy is a technique created to alleviate phantom limb pain, in which patients feel that they still have pain in their limbs even after having them amputated [7]. The Mirror Therapy can improve this condition: the patient places the healthy limb in front of a mirror and the amputated limb behind it. When the patient moves the healthy arm, it is reflected in the mirror and creates the illusion that the amputated limb is moving without pain. Mirror Therapy has been used to treat other pain syndromes, to carry out sensory reeducation, and to improve motor function following brain dysfunction. Mirror Therapy is an excellent tool for improving cognitive as well as physical functions, in fact it is a powerful neuro-rehabilitation technique [8,9]. Today, mirror therapy is combined with innovative therapies, such as robot-assisted therapy: bimanual robot-assisted exercises are performed, that help the neuro-muscular system to improve the use of the diseased limb. This paper presents a rehabilitation system for Mirror Therapy, based on the GLOREHA exoskeleton combined with a sensing glove that allows bimanual exercises. The sensing glove is equipped with sensors that monitor the flexion movement of the fingers of the hand. During operation of the system, the flexion of each sensor is translated into a movement command for the motors of GLOREHA, which operate the various fingers of the exoskeleton. Using this system, patients can perform mirror therapy by wearing the sensing glove in the healthy hand and GLOREHA in the diseased hand. In this way, the user can control the movements of the exoskeleton with the healthy hand, which performs robotassisted therapy on the diseased hand. The advantages of using this system are that it can carry out a rehabilitation routine that is engaging, motivating and both physical and cognitive at the same time, as it actively involves the patient during rehabilitation.

2

The Hand Rehabilitation Robotic System

The proposed system is composed of the two main parts: the rehabilitation and the characterization subsystems, as shown in Fig. 1. The GLOREHA rehabilitation glove, a sensing glove with bending sensors (resistive commercial sensors of Spectra Symbol Corp.), and a software application to control the device are the main parts of the rehabilitation subsystem. The characterization subsystem is based on a test-bench developed by the authors [10] to characterize the bending sensors and an application to collect characterization data. The software

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application is shared by the two parts. A more detailed view on the subsystems is reported in Fig. 2, where the electronic architecture of the system is clarified. The fingers movement with the GLOREHA device are obtained through a cable transmission of the movement generated by five 12 V linear rod actuators (T16-P Miniature Track Actuator by Actuonix). A SparkFun’s ROB-14450 Motor Driver Board can simultaneously control two DC motors in four operating modes: clockwise movement, counterclockwise movement, short brake, stop[z]. Using three Motor Driver Boards it is therefore possible to control the five GLOREHA’s actuators.

Fig. 1. Whole system scheme: test bench, sensing glove, GLOREHA and software application.

The test bench for flexion sensor characterisation is composed of four main parts: the mechanical structure, the flexion or deformation sensor to be characterized, a sensor electronic circuit and the electronic devices necessary for the acquisition of sensor signals and for the external interface for data collection and subsequent data processing. In the test bench for the sensor data acquisition an Arduino Genuino 101 board is used, which is also used to read and control the position of the test bench’s actuator. For the sensing glove, the sensors data acquisition is done via an Arduino Nano 33 BLE Sense which communicates with the PC via Bluetooth or through serial connection. Thanks to its extremely small size, this Arduino can be easily integrated into the instrumented glove, maintaining a high level of comfort for the patient.

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Two variants were considered for the realization of the instrumented glove: a commercial textile glove and a semi-glove printed in silicon material (Fig. 3). The first is a simple textile glove that is worn by the user. The five sensors are located inside seams positioned on the glove, on the dorsal side of the fingers. The second is a semi-glove, made of a silicon base, designed to cover only the back of the hand, thus leaving the palm free to ensure comfort and functionality of the hand. This aspect is very important, because it allows patients to interact more easily with objects and increases the similarity of the instrumented glove to the GLOREHA glove. In addition, this glove is adjustable and customizable, so that it can be used by all patients, regardless of gender and hand size.

Fig. 2. Whole system scheme: exploded diagram.

Fig. 3. Two versions of sensing glove: textile glove and silicon made glove.

The system involves an exchange of data between different devices: one interaction takes place between the sensor test bench and the PC which collects data on the characterised sensors, a second interaction occurs between the sensorised glove and the GLOREHA system. In the latter case, the computer analyzes the movement of the sensors placed on the glove and transmits the information to

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GLOREHA, which performs the same movement. In order to manage the sensor test bench and the sensorized glove - GLOREHA system, a software (SMiTh - ReG) was developed in POWER-KI environment [11]. This software, whose main frame is shown in Fig. 4) has several features: • allows data exchange with the Arduino Genuino 101 and Arduino Nano 33 BLE Sense systems, interfacing with the Arduino program; • during the characterization phase it allows moving the linear actuator; collecting, graphing, interpolating, and saving sensor characterization data; load data relating to previously characterized sensors; • allows setting some parameters of GLOREHA, such as: choice of which fingers to move, range of movement of each finger and working speed; • during the use phase of the instrumented glove, it allows associating a characterized sensor with each finger and, therefore, associating it with the corresponding GLOREHA’s actuator; • allows acquiring and graphically representing the data relating to each sensor on the sensing glove and sending them to GLOREHA for handling.

Fig. 4. Software application interface: sensors data view during system functioning.

3

Results

The characterization tests performed with the test bench demonstrated an acceptable adequacy of the sensors for the developed application. In particular, the results in terms of hysteresis, repeatability and linearity have been analysed and are overall good. An example of results on a tested sensor is shown in Fig. 5.

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Fig. 5. Example of flexion sensor characterization with five repetitions and back and forth movements.

Tests were also carried out on the total opening and closing time of the exoskeleton and on the reaction time between the command signal from the sensing glove and the movement of the GLOREHA’s motors, comparing serial and Bluetooth communication. Also in this case the obtained results are adequate for an application of Mirror Therapy. In order to measure the reaction time between the movement of the sensing glove and the movement of the motors, 20 tests (10 for flexion and 10 for finger extension) were carried out for each sensor considered, always using the same motor pushed at maximum speed (Fig. 5). The tests were repeated both with the Arduino connected to the PC via COM, and via Bluetooth, to assess the delay added by the latter (Fig. 6). Table 1. Average reaction time with Serial and Bluetooth connections. Movement Connection Average Time [ms] Flexion

Serial

460

Extension Serial

450

Flexion

Bluetooth

840

Extension Bluetooth

940

Reaction time tests show similar results between sensors. Calculating the average of all tests carried out with the connection via COM and those carried out via Bluetooth, the reaction time with a connection via serial is approximately 480 ms and 860 ms in the case of connection via Bluetooth (Table 1). Bluethooth communication adds a delay of about 400 ms. The last tests performed measured the reaction time of the motors under the conditions of a rehabilitation exercise,

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Fig. 6. Reaction test for 10 repetitions, with Serial and Bluetooth connections.

i.e. using the motors at 75% of maximum speed. Again, 10 tests were carried out for the flexion movement and 10 for the extension movement of the fingers (Fig. 7). The simulated rehabilitation exercise is the pinch exercise, in which only the thumb and the index finger are moved. A Bluetooth connection is used in this case for the sensing glove - PC communication.

Fig. 7. Pinch movement test with 10 repetitions.

The results on the pinch exercise show that the reaction time is quite good (Table 2). Between the movement of the thumb and the index finger there is a little discrepancy, which is more pronounced in the extension movement. This can be explained by the different hand movements in the two cases. In fact, during the flexion movement starting with the hand completely open, all the fingers are free

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Movement Average Time [ms]

Thumb Flexion

790

Thumb Extension 680 Index

Flexion

Index

Extension 730

780

to move, while during the extension movement starting with the hand closed like a fist, the index finger is blocked in its movement by the thumb, which starts to open slightly earlier than the index finger.

4

Conclusions

The implemented system reads the flexion of the fingers using the sensing glove and sends the information to the GLOREHA control board, which drives the motors following the movement collected by the glove. It allows, therefore, the user to control the exoskeleton using the sensorized glove and perform a bimanual Mirror Therapy, wearing the glove in the healthy hand and GLOREHA in the diseased hand. The results obtained from the characterisation of the sensors have shown that the electrical characteristics of the tested sensors are discrete and suitable for this type of application, whereas the tests on the responsiveness of the system to the command signal are good for both serial and Bluetooth communication. Future developments of the system may involve the implementation of voice commands using the microphone mounted on the Arduino Nano 33 BLE Sense used to control GLOREHA. The commands can be managed by the used programming environment, thanks to an already available application to transform voice commands into text. These commands can be used to Start/Stop the system and to set working settings. In line with the objectives of the SDG3 pillar, the system makes it possible to expand the base of patients who can take advantage of constant and effective home rehabilitation. These further developments may make the use of the system more accessible even to elderly patients.

References 1. Prange, G.B., Jannik M.J.A., Groothuis-Oudshoorn, C.G.M., Hermens HJ, Ijzerman, M.J.: Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J. Rehabil. Res. Dev. 43(2), 171–184 (2006) 2. Bissolotti, L., Villafa˜ ne, J., Gaffurini, P., Orizio, C., Valdes, K., Negrini, S.: Changes in skeletal muscle perfusion and spasticity in patients with poststroke hemiparesis treated by robotic assistance (GLOREHA) of the hand. J. Phys. Therapy Sci. 28, 769–773 (2016). https://doi.org/10.1589/jpts.28.769

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3. Tiboni, M., Borboni, A., V´erit´e, F., Bregoli, C., Amici, C.: Sensors and actuation technologies in exoskeletons: a review. Sensors 22 (2022) 4. Amici, C., Ragni, F., Ghidoni, M., Fausti, D., Bissolotti, L., Tiboni, M.: Multisensor validation approach of an end-effector-based robot for the rehabilitation of the upper and lower limb. Electronics 9, 1–16 (2020) 5. Tiboni, M., Borboni, A., Faglia, R., Pellegrini, N.: Robotics rehabilitation of the elbow based on surface electromyography signals. Adv. Mech. Eng. 10, 1–14 (2018) 6. Amici, C., et al.: Preliminary validation of a device for the upper and lower limb robotic rehabilitation. In: 23rd International Conference on Mechatronics Technology, ICMT 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1–6 (2019). https://doi.org/10.1109/ICMECT.2019.8932139 7. Beom, J., et al.: Robotic mirror therapy system for functional recovery of hemiplegic arms. J. Vis. Exp. 15, 114 (2016). https://doi.org/10.3791/54521 8. Tiboni, M., Legnani, G., Lancini, M., Serpelloni, M., Gobbo, M., Fausti, D.: ERRSE: elbow robotic rehabilitation system with an EMG-based force control. In: Ferraresi, C., Quaglia, G. (eds.) RAAD 2017. MMS, vol. 49, pp. 892–900. Springer, Cham (2018). ISBN: 9783319612751, https://doi.org/10.1007/978-3-31961276-8 95 9. Serpelloni, M., Tiboni, M., Lancini, M., Pasinetti, S., Vertuan, A., Gobbo, M.: Preliminary study of a robotic rehabilitation system driven by EMG for hand mirroring. In: 2016 IE EE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Proceedings, pp. 1–6, Institute of Electrical and Electronics Engineers Inc., University of Sannio, Italy (2016). ISBN: 9781467391726, https://doi.org/10.1109/MeMeA.2016.7533730 10. Tiboni, M., Filippini, A., Amici, C., Vetturi, D.: TestBench for the characterization of flexion sensors used in biomechanics. Electronics 10, 23 (2021). https://doi.org/ 10.3390/electronics10232994 11. Tiboni, M., Aggogeri, F., Pellegrini, N., Perani, C.A.: Smart modular architecture for supervision and monitoring of a 4.0 production plant. Int. J. Autom. Technol. 13, 310–318 (2019). https://doi.org/10.20965/ijat.2019.p0310

Development of Energy Optimization Strategies for Catenary-Free Tramways Alessio Cascino(B) , Gabriele Ciappi, Enrico Meli, and Andrea Rindi Department of Industrial Engineering, University of Florence, Florence, Italy [email protected]

Abstract. The current development trend in the railway field has led to an everincreasing interest for the energetic optimization of railway systems. A strong attention is paid to the mutual interactions between the loads presented by railway vehicles and the electrical infrastructure, including all the sub-systems related to distribution and smart energy management, such as energy storage systems. The use of regenerative braking, already widespread in tramway field, may represent one of the most promising methods to increase energy efficiency, combined with regenerative braking with storage systems of various types (Energy Storage Systems - ESS), placed on the vehicle or along the line. With the aim of correctly estimating energy performances, it is necessary to develop predictive models of entire railway systems. The objective of the present research activity was to develop an energy optimization strategy for a tram system, considering a city line in Florence. Particularly, a model of the tramway line and of the vehicle were developed with the use of simulation tools such as MATLAB-Simulink and MATLAB-Simscape. An optimization was carried out to determine the correct energy management and the use of regenerative braking, as well as the possibility to run the entire line (or portions of it) without the over-head line. The results show that recovered energy produced in the braking phase and a correct energy management can reduce the emissions produced, saving energy about 40% for each line configuration and obtain architectural improvement. Keywords: Affordable and Clean Energy · Sustainable cities and communities · Railway · Energetic Optimization · Simulation · Energy Storage Systems

1 Introduction Transport is a major source of air pollution and greenhouse gas emissions [1]. Transitioning to more sustainable modes of transport, and optimizing them, can play a key role in achieving this goal. Modern railway vehicles, during the braking phase, can convert mechanical energy into electricity. The current trend is to allow the reuse or accumulation of the energy produced (regenerative braking), contrary to that was done previously, where the energy was dissipated in special rheostats (dissipative braking). There are some main ways of using the energy produced during braking: • Energy cooperation between different vehicles; © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 468–475, 2023. https://doi.org/10.1007/978-3-031-32439-0_53

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Use of ESS positioned on board the vehicle; Use of stationary ESS integrated into the infrastructure; Conversion and re-introduction into the electricity grid outside the line; Combination of the above modes.

Regenerative braking systems have been already introduced in urban type vehicles, like metro and tram vehicles whose running is characterized by several and continuous accelerations and decelerations. Literature shows some research focused on the optimization of the timetables to maximise the energy cooperation between nearby vehicles. In this way the energy obtained from the regenerative braking of a decelerating train is used by another accelerating train. The electricity generated is returned to the catenary supply line, leading to a high level of uncertainty as there is no guarantee that a train will accelerate at the same time and in the vicinity where the energy is available. However, this methodology, combined with the optimization of the speed profiles between the stations, allowed to obtain up to 14% of energy savings [2, 3]. This approach enables for an integrated optimization, which results in better energy savings than using individual optimization of the timetables and speed profiles of the vehicles. Another significant example was conducted on Beijing subway [4, 5]. Energy Storage Systems (ESS) can be mounted on the vehicle or be stationary. The use of ESS can reduce the peak demand for electricity. In fact, they can be used as “peak shaving”, i.e. to store energy when demand is low and release it when the demand for electricity is greater [6]. In the research conducted, lithium ion (Li-ion) batteries have been used. These accumulators have become very popular in recent years for powering electric vehicles and small electronic devices [7], thanks to their high energy density, high charge efficiency and a long life [8, 9]. Examples of ESS implementations on board a vehicle are the Brussels and Madrid metro lines and the Mannheim tramway, reducing the energy required by up to 25%. These systems allow reducing losses and the stabilization of the energy supply line voltage, but their efficiency depends on the characteristics of the vehicle, which can affect the amount of energy produced (during braking) and consumed (during acceleration) [10]. Stationary systems, on the other hand, allow to power more than one vehicle and help reduce brownout problems that could damage vehicle equipment [11, 12]. They usually consist of a battery connected to the power line through a power control unit. This solution allows energy savings of up to 30%. There are some commercial products such as “Sitras SES” (Static Energy Storage) from Siemens [13], or “EnerGstor” from Bombardier [14]. The last approach to reuse the regenerative braking energy is the use of reversible substations that takes advantage of regenerated energy to be fed into the AC line upstream of the substation itself [15]. Even though reversible substations are designed to have the capability to feed regenerative braking energy to the upstream grid, if maximum regenerative energy recovery is aimed for, priority should be given to energy exchange between trains on the DC side of the grid electric. The possibility of powering the vehicles using only on-board batteries allows to overcome architectural constraints typical of historic city centres, removing the over-head line. The solutions, for the installation of this kind of systems, differ on the basis of the ESS recharging method: • Solutions with recharge at the stations while stopped there;

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• Solutions with recharge while passing under the traditional contact line on short parts of line. In this case there are sections with catenary and others without it; • Solutions based on continuous power supply systems alternative to the catenary, such as by means of magnetic induction. In this paper, the results shown before were used to optimize a tramway line in Florence. The aim was to find solutions for the use of new ESS and the possibility of running sections without the over-head catenary line. At the same time, an energy optimization was carried out. The implementation of the solutions obtained in this work could allow the reduction of energy consumption and the emissions of pollutants, to achieve the goal of “Sustainable cities and communities” provided by the Sustainable Development Goals (SDG).

2 System Modelling The research carried out in the present paper, proposes a flexible modelling to simulate the electrical and mechanical behaviour of a railway vehicle on any line. The main objectives of this work were: • • • •

Efficient energy management achieved through regenerative braking of vehicle; The use of ESS (stationary and on board) to optimize the regenerative braking; The modelling of an innovative system partially or totally without catenary; Energy optimization of the examined tramway system.

For the implementation of functional models for the purposes of the research work, MATLAB - Simulink software was used, allowing to simulate the interaction between complex systems, such as mechanical and electrical. The activity started from a previously developed model which considered a high-speed railway vehicle (ETR 1000) [16]. Initially, the existing tram system was represented and then the stationary and on-board ESS were implemented, testing the possibility of running parts of the section (or the entire line) without the use of the catenary. The ESS were also sized to be able to travel on various line configurations that alternate sections with and without a catenary. Finally, the vehicle speed profiles were evaluated to optimize the vehicle timetables. The system model has been divided into two sub-model: the first one described the longitudinal dynamics of the vehicle (mechanical), while the second one represented all the elements necessary for the vehicle power supply (electrical). The two sub-models communicated in real time using Simulink. The simulation, and its optimization, have been carried out considering both a single and a multi-vehicle system, with trams moving in two directions. The mechanical model took as input the voltage in a given point of the line from the electrical sub-model and communicated the electrical energy request of the vehicle to the supply line and to the batteries. The goal was to respect the timetable of the vehicle but, at the same time, optimize the regenerative braking. This model allowed to determine the position and speed of the rolling stock instant by instant, starting from its ideal speed profile (obtained by experimental tests conducted on the line and provided by the vehicle manufacturer), considering traction and braking forces, forward and accidental

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resistance forces, adherence and comfort passengers limits. A virtual driver, modelled using a PID control, allowed to determine the difference between the ideal speed and the real one, and consequently to accelerate or decelerate the vehicle. As regards the acceleration and deceleration efforts, the traction and braking curves of the vehicle have been implemented in the mechanical model, in order to avoid sliding. The resistant forces, i.e. the aerodynamic ones, those related to the wheel-rail contact, those due to the slope and to the curvature of the track, have been also considered (Fig. 1).

Fig. 1. Architecture of the vehicle mechanical model.

The acceleration has been calculated by the ratio between the resultant of the forces and the equivalent total mass of the vehicle (Considering also the contribution of rotating masses of elements such as axles, motors and transmission components). By integrating twice over time, both the speed and the position, necessary to calculate the electrical power requested, has been obtained. The auxiliary power required to power all the onboard devices has been added to the power thus obtained. In the braking phase, on the other hand, the electric and hydraulic braking forces has been obtained, with which the regenerated electric power has been calculated, considering the efficiency of the system. The output of the mechanical model represented the input of the electrical one. The electrical sub-model was developed using Simscape. The electrical substations, the stationary and vehicle ESS, the catenary line and the feeder system have been modelled. The input were the position and the power required from the vehicle, while the output was the voltage applied to the vehicle. The communication between parts in Simulink and in Simscape has been realized by proper conversion blocks between the two languages. The obtained system was strongly time-varying due to the dependence of the electrical variables on the mechanical ones and vice versa. For the power supply of the line, a physical sub-model has been developed to represent the electrical substations in a simplified way. The catenary line was then modelled to simulate the change in electrical resistance of the power cable, as a function of the vehicle position. This consideration allowed to determine the supply voltage of the tram and the absorbed current. The feeder system, used along the Florence tramway line, was also modelled (Fig. 2).

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Fig. 2. Diagram of power substations, overhead line with feeder and vehicle subsystems.

For the modelling of the ESS, lithium batteries were considered, because evaluated as the most promising for the applications under study. The modelling of the electrical part considered the possibility of installing stationary and on-board batteries. In the first case, the batteries were placed in parallel respect to the substations, in order to limit the space required for them. In the second case, a parallel connection was made between the battery and the ideal current generator which represents the energy requirements of the vehicle, placing proper switches to connect the battery to the rest of the model. All the parts mentioned above are shown in Fig. 3. The presented module allowed to fully represent a section between two electrical substations. Repeating it in series or in parallel, it is possible to represent even very complex lines. The modularity of the model also allowed the representation of the unpowered sections, disconnecting the catenary line and operating, in proper way, the switches for connecting the batteries. In addition, the model can include several vehicles circulating on the line. The vehicles are represented with distinct mechanical sub-models to impose different timetables or different vehicles.

Fig. 3. Diagram of the configuration of a module between two substations.

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3 Test Case and Results The main technical data of the vehicle has been obtained from the manufacturer. This data contains the speed profiles, traction and braking mechanical characteristic, tare weight and maximum weight, axle load and accelerations in the entire line. Furthermore, there is also the technical datasheet of the four motors present on the tram with the relative voltage, current, power, number of poles and rotation speed. The considered route is a Florence line and the energy supply system was based on five irreversible substations positioned along the section. The original system did not contain any ESS to take advantage of regenerative braking. The energy produced during the braking phases by the vehicles was always dissipated in rheostats placed on the rolling stock. The research conducted assessed the possibility of reusing the energy obtained from regenerative braking implementing stationary and on-board ESS. The possibility of running the line (or portions of it) without the catenary was also tested, taking advantage of the innovative retrofit proposed by the manufacturer for the vehicle. To obtain this goal, the original configuration was initially modelled, to be used as a comparison with the other proposals. The use of reversible substations was not considered for the high complexity and costs of this solution. In the present work, four configurations have been considered with sections where the vehicle is powered by the over-head line and sections without it, where the vehicle uses only the on-board ESS. The line was divided into three parts in correspondence of two power substations. In this way the modification of the electrical supply line could be relatively easy, reducing the costs of the proposal (Table 1). Table 1. Characteristics of the tested configurations. Configurations

Section 1

Section 2

Section 3

Configuration 1

Catenary Free

Catenary

Catenary

Configuration 2

Catenary Free

Catenary

Catenary Free

Configuration 3

Catenary

Catenary Free

Catenary Free

Configuration 4

Catenary Free

Catenary Free

Catenary Free

For each configuration, the stationary and on-board ESSs have been sized, respecting the constraints that allowed to make the most of the batteries and ensure their long life. From the simulations carried out, it was possible to obtain the state of charge of the batteries (SOC) and the speed profile of the vehicles. In all the configurations, the regenerative braking made it possible to recover part of the mechanical energy, even if the battery still tended to discharge. When, on the other hand, the vehicle was connected to the power supply line, the ESSs tended to recharge. In the last configuration, it was considered to recharge the batteries at the beginning and at the end of the line, since the energy obtained through the regenerative braking was not sufficient to maintain the required SOC. This configuration turned out to be the most onerous, for the use of onboard batteries since there was neither a power line nor stationary ESS. In any case,

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thanks to the use of the electrical energy produced by regenerative braking, a reduction of the energy required to operate the vehicle on the considered line was obtained (Fig. 4).

Fig. 4. Comparison between the proposed configurations and the original case.

4 Conclusion and Further Developments In this research a flexible model has been developed to describe, instant by instant, the mechanical behaviour of a light rail vehicle and the electrical behaviour of its energy supply line. The model has been divided into two parts. The mechanical one can analyse the longitudinal dynamic of the vehicle, while the electrical one can determine the energy requirement during the utilization. The developed model has been used to evaluate four different configurations where the vehicles can run connected to the catenary line or without it, thanks to the energy provided by the on-board ESS. The stationary and onboard ESSs have been sized and an optimization has been carried out to make the most of the batteries considered. The regenerative braking connected with the usage of ESS can provide an increased energy efficiency, but also architectural improvement in city centres. All the configurations can lead to saving up to 44% of energy required during the operation of the vehicle on the considered line. As future developments, specific costs and benefits obtained with the solution and the model exposed will be evaluated. In particular, it will be interesting to evaluate the possibility to use the proposed model to retrofit or to design new tramway lines. In addition, the model could also be used to design new tram vehicle to use in catenary free lines. Acknowledgements. This study was carried out within the MOST – Sustainable Mobility National Research Center and received funding from the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1033 17/06/2022, CN00000023). This manuscript reflects only

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the authors’ views and opinions, neither the European Union nor the European Commission can be considered responsible for them.

References 1. European Environment Agency, Transport and environment report 2021 (2022) 2. Zhao, N., Roberts, C., Hillmansen, S., Tian, Z., Weston, P., Chen, L.: An integrated metro operation optimization to minimize energy consumption. Transp. Res. Part C 75, 168–182 (2017) 3. Li, X., Lo, H.K.: An energy-efficient scheduling and speed control approach for metro rail operations. Transp. Res. Part B 64, 73–89 (2014) 4. Su, S., Li, X., Tang, T., Gao, Z.: A subway train timetable optimization approach based on energy-efficient operation strategy. EEE Trans. Intell. Transp. Syst. 14(2), 883–893 (2013) 5. Yang, X., Li, X., Ning, B., Tang, T.: A survey on energy-efficient train operation for urban rail transit. IEEE Trans. Intell. Transp. Syst. 17(1), 2–13 (2016) 6. Tian, Z., Weston, P., Zhao, N., Hillmansen, S., Roberts, C., Chen, L.: System energy optimisation strategies for metros with regeneration. Transp. Res. Part C Emerg. Technol. 75, 120–135 (2017) 7. Jiang, J., Zhang, C.: Fundamentals and applications of Lithium-Ion batteries in electric drive vehicles. Wiley, China (2015) 8. Liu, X., Li, K., Li, X.: The electrochemical performance and applications of several popular lithium-ion batteries for electric vehicles - a review. In: Li, K., Zhang, J., Chen, M., Yang, Z., Niu, Q. (eds.) Advances in Green Energy Systems and Smart Grid. ICSEE IMIOT 2018 2018. CCIS, vol. 925. Springer, Singapore (2018). https://doi.org/10.1007/978-981-13-23812_19 9. Liu, X., Li, K.: Energy storage devices in electrified railway systems: a review. Transp. Saf. Environ. 1–19 (2020) 10. Los Angeles County Metropolitan Transportation Authority, Energy & Resource Report (2018) 11. Alfieri, L., Battistelli, L., Pagano, M.: Impact on railway infrastructure of wayside energy storage systems for regenerative braking management: a case study on a real Italian railway infrastructure. IET Electr. Syst. Transp. 9(3), 140–149 (2019) 12. Lamedica, R., Ruvio, A., Palagi, L., Mortelliti, N.: Optimal siting and sizing of wayside energy storage systems in a D.C. railway line. Energies. 13, 22 (2022) 13. Urien, N.: Energy optimization for public transportation applications. Autom. People Movers Transit Syst. 404–415 (2013) 14. Meishner, F., Sauer, D.U.: Wayside energy recovery systems in DC urban railway grids. eTransportation 1, 20 (2019) 15. Gil, G., Palacin, R., Batty, P.: Sustainable urban rail systems: strategies and technologies for optimal management of regenerative braking energy. Energy Convers. Manag. 75, 374–388 (2013) 16. Frilli, A., Meli, E., Nocciolini, D., Pugi, L., Rindi, A.: Energetic optimization of regenerative braking for high speed railway systems. Energy Convers. Manag. 129, 200–215 (2016)

Multibody Simulation of an Underactuated Gripper for Sustainable Waste Sorting Gabriele Maria Achilli1 , Silvia Logozzo1(B) , and Monica Malvezzi2 1 Dipartimento di Ingegneria, Università degli Studi di Perugia, Perugia, Italy

[email protected], [email protected] 2 Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università degli Studi di Siena, Siena, Italy [email protected]

Abstract. The waste disposal is a fundamental issue for the planet’s health, as the inevitable accumulation of waste represents a serious threat that endangers our environment. In this context, devices that can facilitate activities in the disposal of waste allow to meet some of the 17 goals defined in the “Sustainable Development Agenda”. The Sustainable Development Goals are calls to action for all countries to promote prosperity while protecting the planet. In this paper, a multibody model is proposed for an underactuated gripper dedicated to sorting operations in the waste industry to evaluate grasping operations with particular attention to the implemented contact models. The design of the gripper was previously proposed but, in this paper, simulations are carried out for studying the grasping behavior proposing different contact models implemented and developed in Simscape Multibody. Results obtained from some simulations are presented and discussed. The studied gripper has the function to protect the operators in the waste industry during waste handling operations, and for this reason the topic of this paper is oriented at the achievement of SDG3 and SDG8 promoting health and well-being of human workers due to a safe and decent work. Moreover, the enhancement of the waste industry in terms of waste recycling and improved waste management helps to build resilient infrastructure and promote fair, sustainable, and responsible industrialization, reducing the impact of waste on the environment and human health and promoting a circular economy in compliance with SDG9 and SDG12. Keywords: SDG 3 · SDG 8 · SDG 9 · SDG 12 · Robotic grasping · Contact models · Multibody

1 Introduction Robotics contributes at achieving many of the goals of the sustainable development defined by the United Nations in the 2030 Agenda: from the reduction of pollution [1] to the enhancement of the sustainability of life through wearable devices for impaired persons [2] and the use of robotic devices for medical operations and teleoperations [3, 4]. The paper presents a robotic device which can help ecological operators during waste disposal operations enhancing their safety and improving waste management. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 476–483, 2023. https://doi.org/10.1007/978-3-031-32439-0_54

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Waste management is an open challenge to improve the health of the planet and the innovation in the waste industry [5]. Both these aspects are fundamental for complying with the objectives described in SDG12 (responsible consumption and production) and connected to the innovation of industry described in SDG9. Furthermore, since working in safe conditions is essential for a more sustainable society, the present work and the studied gripper are also oriented at satisfying SDG3 and SDG8, by promoting health and well-being of human workers due to a safe and decent work. Great attention must be paid to the use of eco-sustainable materials in the design of products, and to the implementation and employment of machinery that allow more effective material consumption and waste management [6, 7]. Differentiating waste is an essential task for all the human populations to promote the waste recycling which is crucial to preserve the environment, and which is as important as to deal with solutions that reduce the economic impact of waste on companies and citizens. The operations related to the waste industry are mainly characterized by two phases: the collection of waste and its management and disposal. Both phases have an impact on ecological operators which are exposed to a series of potential hazards. Robotic grippers have been widely adopted in the waste industry for a variety of tasks such as sorting, segregating, and packaging of waste materials. These grippers are equipped with advanced sensors and control systems that allow them to perform complex tasks with high precision and accuracy. Robotic grippers also have the ability to work in hazardous environments, such as in recycling plants where they can help to reduce the risk of injury to human workers [8]. Furthermore, they can be integrated into fully automated waste management systems which can improve the overall efficiency of the whole process [9]. It is very important to consider that robotic grippers allow automating repetitive and labor-intensive tasks, increasing efficiency and productivity, handling a wide range of waste materials [10]. In fact, human workers in the waste industry are at risk of various hazards, such as exposure to hazardous materials, accidents from heavy machinery, and musculoskeletal injuries from repetitive motions. They may also be exposed to dangerous working conditions such as extreme temperatures and poor air quality. Moreover, workers are at risk of injury from sharp objects, slips and falls, and of exposure to infectious diseases. These risks can be mitigated by providing proper training, protective equipment, and implementing safety protocols, but most of all by equipping them with robotic devices and related safety protocols [11]. Considering these aspects, the paper refers to the study of a multibody model of a gripper designed for the handling of municipal solid waste and devoted to limiting the involvement of human operators in dangerous activities. The gripper was previously presented in other works with attention on its design and production with different materials and in particular eco-friendly materials [12]. The preliminary model developed in Simscape multibody was proposed in [13] but the work presented in this paper is focused on the improvement of the multibody model by proposing and applying two customized contact models together with the default model provided by Simscape. The importance and the innovation of this work lies in the introduction of more sophisticated contact models that allow to analyze the gripper behavior in a virtual

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environment and test the non-destructive grasping of waste that, if broken, could seriously compromise the health of the operator [14]. The multibody simulation of a robotic gripper is an important result to understand the behavior and performance of the gripping system. The simulation can be used to model the movement of the gripper’s various components, such as the fingers, in response to different control inputs, such as the position or velocity of the gripper. By analyzing the resulting trajectories and forces, researchers can gain insights about the dynamics of the gripper and can identify areas for improvements. This can include analyzing the accuracy and precision of the gripper’s motion, as well as the time required for the gripper to complete a task. Additionally, the simulation can also be used to evaluate the effects of changes in the gripper’s design, such as the addition of new sensors or actuators, on its overall performance.

2 Materials and Methods 2.1 SynGrasp and Simscape Multibody Simulation SynGrasp is a MATLAB toolbox which can be used to design lumped parameter models of compliant deformable components and synergistic coordination between joint variables for grasp analysis of fully or partially actuated robotic hands [15]. All the elements can be analyzed considering the contact points, the joints, the transmission, and actuation [16]. The hand configuration and simulation parameters can be established with a MATLAB script or using a graphical user interface. Using the available functions, a grasp under quasi-static conditions can be evaluated in terms of contact and actuation forces, manipulability features, grasp quality indicators, and stiffness [17]. Simscape Multibody has the advantage of being incorporated in the MATLAB environment, which means it relates to a range of other tools and allows complete analyses, as well as the ability to connect the mechanical model with other components, such as control systems. In addition, MATLAB Simscape performs kinematic and dynamic analyses, which can help to identify the motion of a system and the forces that drive that motion. Moreover, the tool can be used to perform control system analysis, which can help identifying the best control strategies. Another relevant integration is with tools that evaluate grasping and manipulation features, such as those provided by the SynGrasp toolbox, which is applicable to the specific application of robotic grippers and hands envisaged in this study. The grasping was simulated in Simulink by connecting SynGrasp and Simscape Multibody. Figure 1 reports the functional architecture of the tendon driven gripper, and Fig. 2 shows the multibody model of the gripper in the open and closed position without any target object to grasp. As it can be seen, the gripper’s structure comprises a palm, an articulated scoop and two articulated fingers [18]. 2.2 Custom Contact Models To investigate the gripper’s behavior in a multibody simulation system during various operating conditions, different contact models were designed and integrated using Simscape. The Spatial Contact Force block, included in the Simscape Multibody toolbox,

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Fig. 1. Functional architecture of the studied gripper.

Fig. 2. The gripper multibody model in different configurations: (a) open; (b) closed.

replicates contacts between solid bodies. According to [19], this toolbox estimates the contact force between bodies and deformations using a sequence of spring and damper elements, representing the surface compliance of the contact bodies [20–23]. Combining the Hertz, the Kevin and Voigt models, and the penalty methods, the contact model used in Simscape can be represented by the following equation   (1) Fn = s(δ) Kδ + Dδ˙ where K is the stiffness, D the damping coefficient, δ the indentation, δ˙ the time derivative of the indentation and s(δ) the smoothing function, dependent on the indentation δ. The resolution of the smoothing function s(δ) is based on the transition region width w. This parameter determines how briefly the function goes into saturation. This is a simplified model of the contact event that neglects several parameters and generalizes the issue. Rarely, the proposed simplification might result in incorrect results. To enhance these estimations, alternative models were evaluated. These contact models are based on the results presented in [24], where the formulations indicate various configurations and applications. Consideration was given to the models explaining multiple sorts of probable contact: 1. Hunt-Crossley model   Fn = s(δ) Kδ n + χ δ n δ˙

(2)

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where χ is the hysteresis damping factor, defined as χ=

3K (1 − cr ) 2δ˙0

(3)

where δ˙0 is the initial relative contact velocity and cr the coefficient of restitution. Implementing the χ coefficient in the first equation it results:   3(1 − cr ) δ˙ n (4) Fn = s(δ)Kδ 1 + 2 δ˙0 which models impacts with a high coefficient of restitution and low dissipation. 2. Lankarani-Nikravesh model     2 ˙ 3 1 − c δ r Fn = s(δ)Kδ n 1 + (5) ˙δ0 4 in which χ=

3K  1 − cr2 4δ˙0

(6)

In this model the χ coefficient accounts for the internal damping which causes a loss of kinetic energy evaluated as a function of the coefficient of restitution and δ˙0 . In the Simscape routing, the sensing subsystem is based on a Transform sensor block. The translations along the x, y, and z axes are measured and referenced to the base world origin coordinate system and the object’s position can be traced during the simulation. The translation of the object is obtained summing the x, y and z vectors magnitude. The displacement signal passes through a derivative block to pull out the object instantaneous velocity, useful for all the developed contact methods. This signal is filtered, and the negative values are collected. Indeed, only the indentation phase is considered. The transient signals detected at the beginning and the end of the contact event are smoothed: a few smoothing functions were tested, comparing the original Spatial Contact Force block results, as reported in Eq. (1). An exponential function highlights the best fitting, according to the equation:  3 δ δ s(δ) = 3 − 2 w w

(7)

Both the chosen methods are based on the same variables: displacement δ, velocity ˙ stiffness K, hysteresis coefficient χ and coefficient of restitution cr . δ,

3 Results and Discussion All the three contact models presented in Sect. 2.2 describe the interaction between solid bodies, but they work well with certain boundary conditions. In this section results of the application of the three contact models are reported considering that the gripper

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contacts the target objects with a planar surface (the scoop) and two fingers made of a set of articulated cylinders. In fact, the elements of the simulated robotic fingers are realized by solid cylinder functions, while the scoop is represented by a planar surface with appreciable thickness. Considering spherical and cylindrical waste to grasp, the contact with different surfaces can be analyzed, as shown in Fig. 3.

Fig. 3. The gripper multibody model in while grasping a spherical waste.

The initial conditions of the simulation consider the possible scenarios that arise in a grasping task. The two fingers close over the object, and the scoop also grabs it in the opposite direction. In the contact simulations the Kevin and Voigt model was considered as a reference, as it is provided by Simscape as a default model and the customized Hunt-Crossley and Lankarani-Nikravesh models were compared for the same value of stiffness. Results of the contact force between the scoop and spherical and cylindrical waste resulting from the application of the three adopted methods are reported in Fig. 4.

Fig. 4. Contact force at the scoop obtained with the three models. (a) Sphere; (b) Cylinder.

The possibility of obtaining these simulations’ results represents an advancement with respect to previous works to simulate the behavior of the gripper during the grasping of waste with different mechanical properties and shapes. Results show different behaviors for different contact models and shapes and allow to study many contact problems. In particular, the Kevin-Voigt model does not account for the nonlinearity of the contact process and it is suitable for simulating contacts at higher impact velocities [24]. In general, this model is used for the contact between flexible bodies. The Hunt and Crossley model evaluates the contact forces using the Hertzian model and a non-linear

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viscous-elastic element which accounts for damping, and it is based on the penetration depth. This second contact model works better for elastic impacts and for impacts with a high value of the coefficient of restitution and with lower energy dissipation, [25, 26]. In general, impacts between soft and flexible objects, with high coefficient of restitution tends to have less energy dissipation. The Lankarani-Nikravesh model determines the hysteresis-damping factor based on the loss of kinetic energy caused by internal damping. It can be applied to general contacts in mechanical systems, particularly when the ratio of lost energy is small. The model is effective for elastic contacts with a coefficient of restitution close to 1. Objects made of elastic materials such as rubber, latex, or metals such as gold, silver, and copper can be represented by this contact pattern. This model can be used to represent grippers with flexible scoops that manipulate rigid objects.

4 Conclusions This paper presents the mechanical contact study of a robotic underactuated gripper devoted to the waste industry to help humans in harmful tasks. The development of custom contact models allowed to detect the contact forces when the gripper grasps waste of different shapes through a multibody simulation. The implementation of these models in a multibody environment will help to simulate the different interactions between the gripper and several kinds of waste. Findings of this paper can be advantageously used to properly design the gripper’s components for the grasping of specific waste limiting the human interface with hazardous items. Therefore, the studied gripper is compliant with SDG3, SDG8, SDG9 and SDG12.

References 1. Muscat, M., Cammarata, A., Maddio, P.D., Sinatra, R.: Design and development of a towfish to monitor marine pollution. Euro-Mediterr. J. Environ. Integr. 3(1), art. 11 (2018) 2. Malvezzi, M., Iqbal, Z., Valigi, M.C., Pozzi, M., Prattichizzo, D., Salvietti, G.: Design of multiplewearable robotic extra fingers for human hand augmentation. Robotics 8(4), art. 102 (2019) 3. Cammarata, A., Lacagnina, M., Sinatra, R.: Closed-form solutions for the inverse kinematics of the Agile Eye with constraint errors on the revolute joint axes. In: IEEE International Conference on Intelligent Robots and Systems 2016-Nov, pp. 317–322, art. 7759073 (2016) 4. Tanev, T.K., Cammarata, A., Marano, D., Sinatra, R.: Elastostatic model of a new hybrid minimally-invasive-surgery robot. In: 2015 IFToMM World Congress Proceedings, IFToMM 2015 (2015) 5. Heacock, M., Kelly, C.B., Suk, W.A.: E-waste: the growing global problem and next steps. Rev. Environ. Health 31(1), 131–135 (2016) 6. Logozzo, S., Valigi, M.C.: Wear assessment and reduction for sustainability: some applications. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 395–402. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-87383-7_43 7. Logozzo, S., Valigi, M.C.: Green tribology: wear evaluation methods for sustainability purposes. Int. J. Mech. Control 23(01), 23–34 (2022) 8. Auler, F., Nakashima, A.T.A., Cuman, R.K.N.: Health conditions of recyclable waste pickers. J. Commun. Health 39(1), 17–22 (2013). https://doi.org/10.1007/s10900-013-9734-5

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9. Gundupalli, S.P., Hait, S., Thakur, A.: A review on automated sorting of source-separated municipal solid waste for recycling. Waste Manag. 60, 56–74 (2017) 10. Krechetov, I., Skvortsov, A., Poselsky, I., Lavrikov, P.: Scheduling jobs and managing a robotic sorting node. Int. J. Mech. Eng. Technol. 9(11), 95–105 (2018) 11. Medina, A.C., Mora, J.F., Martinez, C., Barrero, N., Hernandez, W.: Safety protocol for collaborative human-robot recycling tasks. In: 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019, vol. 52, no. 13, pp. 2008–2013 (2019) 12. Achilli, G.M., Logozzo, S., Valigi, M.C., Salvietti, G., Prattichizzo, D., Malvezzi, M.: Underactuated soft gripper for helping humans in harmful works. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds.) I4SDG 2021. MMS, vol. 108, pp. 264–272. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-87383-7_29 13. Achilli, G.M., Logozzo, S., Malvezzi, M., Valigi, M.C.: Underactuated embedded constraints gripper for grasping in toxic environments. SN Applied Sciences In press (2023) 14. Achilli, G.M., Logozzo, S., Malvezzi, M., Valigi, M.C.: Contact mechanics analysis of a soft robotic fingerpad. Front. Mech. Eng. 8, art. 966335 (2022) 15. http://syngrasp.dii.unisi.it. (2022). Accessed 2023 16. Achilli, G.M., Logozzo, S., Valigi, M.C., Malvezzi, M.: Preliminary study on multibody modeling and simulation of an underactuated gripper with differential transmission. In: Proceedings of ASME Design Engineering Technical Conference, no. 9, art. V009t009a005 (2021) 17. Pozzi, M., Achilli, G.M., Valigi, M.C., Malvezzi, M.: Modeling and simulation of robotic grasping in Simulink through Simscape multibody. Front. Robot. AI-Soft Robot. 9, art. 873558 (2022) 18. Achilli, G.M., Valigi, M.C., Salvietti, G., Malvezzi, M.: Design of soft grippers with modular actuated embedded constraints. Robotics 9(4), 1–15, art. 105 (2020) 19. https://it.mathworks.com/help/sm/ref/spatialcontactforce.html. (2023). Accessed 2023 20. Lankarani, H.M., Nikravesh, P.E.: A contact force model with hysteresis damping for impact analysis of multibody systems. J. Mech. Des. Trans. ASME 112(3), 369–376 (1990) 21. Fourment, L., Chenot, J.L., Mocellin, K.: Numerical formulations and algorithms for solving contact problems in metal forming simulation. Int. J. Numer. Meth. Eng. 46(9), 1435–1462 (1999) 22. Valigi, M.C., Papini, S.: Analysis of chattering phenomenon in industrial S6-high rolling mill. Diagnostyka 14(3), 3–8 (2013) 23. Valigi, M.C., Logozzo, S.: Do exostoses correlate with contact disfunctions? A case study of a maxillary exostosis. Lubricants 7(2), art. n. 15 (2019) 24. Skrinjar, L., Slaviˇc, J., Boltežar, M.: A review of continuous contact-force models in multibody dynamics. Int. J. Mech. Sci. 145, 171–187 (2018) 25. Marhefka, D.W., Orin, D.E.: A compliant contact model with nonlinear damping for simulation of robotic systems. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 29(6), 566–572 (1999) 26. Gonthier, Y., McPhee, J., Lange, C., Piedbœuf, J.C.: A regularized contact model with asymmetric damping and dwell-time dependent friction. Multibody Sys.Dyn. 11(3), 209–233 (2004)

Preliminary Study on a Handle with Haptic Devices for Collaborative Robotics in a Remote Maintenance Environment Gabriele Maria Achilli1(B) , Francesco Chinello2 , Cheng Fang3 , Pedro Gomez Hernandez2 , Silvia Logozzo1 , and Maria Cristina Valigi1 1 Dipartimento di Ingegneria, Università degli Studi di Perugia, Perugia, Italy

[email protected], {silvia.logozzo, mariacristina.valigi}@unipg.it 2 Business Development and Technology, Aarhus University, Herning, Denmark {chinello,pedrogh}@btech.au.dk 3 Faculty of Engineering, The Maersk Mc-Kinney Moller Institute, SDU Robotics, Odense, Denmark [email protected]

Abstract. Operators involved in plant and machine maintenance operations are often exposed to many risks due to hazardous tasks. This is evident especially during the maintenance of offshore wind turbines, which implies that the human workers are in contact with dangerous components with risk of falls, as they must climb the turbine to perform their intervention. Therefore, an ethical approach is necessary to promote a more sustainable industrialization and safe work. Studying new safe solutions is essential to improve job conditions and economic growth. A new handling device is proposed for a telerobotic platform that uses collaborative robots and Immersive Virtual Reality (IVR) to increase safety and efficiency in the maintenance of renewable energy machines as offshore wind turbines. The study aims at achieving the SDG8 objectives of Decent Work and Economic Growth by reducing hazards and risks for operators, as well as the SDG7 objective of Affordable and Clean Energy. Two versions of a maneuvering device for remote maintenance of offshore wind turbines are compared in terms of ergonomics and safety. The tests are carried out with a sample of 13 operators also equipped with tactile devices useful to regulate the application of force by the operator when the contact between the tool and the machine to be maintained occurs. Keywords: SDG8 · SDG7 · Haptic device · Collaborative robotics · Teleoperation

1 Introduction The use of Virtual Reality (VR) with collaborative robotics makes it possible to reduce risks in some hazardous working tasks. In recent years, important advancements in Immersive VR (IVR) raised the attention of various industrial sectors on bringing an “immersive” experience to the users, with the introduction of wearable headsets such as © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 484–491, 2023. https://doi.org/10.1007/978-3-031-32439-0_55

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Oculus Rift and HTC Vive. IVR has an important impact on costs and risks reduction for working personnel in dangerous environments [1] as industrial scenarios involving machinery [2, 3] or in safety trainings regarding hard-to-access environments such as wind turbine nacelles [4]. The use of IVR training is growing in a variety of industries, including manufacturing and healthcare [5]. The use of haptics in immersiveness is also notable, despite its limited diffusion in manufacturing areas. In this scenario, the results are particularly important considering studies in telerobotics, that struggle to reach popularity in manufacturing areas because of the very specific applications dedicated to teleoperation in industry, such as the manipulation of hazardous materials or machinery remote control [6, 7]. Regardless of its currently limited industrial diffusion, telerobotic remains crucial in specific industrial tasks with variable complexity and non-repetitive operations that are not easily programmable. In a VR environment, the necessity of using interaction paradigms that differ from the real scenarios is brought, for example, by the needing to use joypads or handles. These drive the developers to employ specific interlacement processes in VR to resolve the interaction with objects. The difference between the IVR representation and the real training scenario can end up extending the training time of practitioners in manufacturing or assembly processes [8]. Surveys can be used to gather feedback from users. To incorporate IVR in industrial areas and teleoperation, twin robots are required. In the industrial field, these technologies can be used in hazardous environments to perform tasks that are too dangerous for human workers. To increase the interaction between users and robots, combining these with a VR environment, haptic devices are necessary. The cutaneous feedback is perceived in the place where the device is located [9], and it gives the user a direct and accurate sense of the contact force, even though the sense of movement is not present. This tactile experience makes VR tasks more immersive and productive. The main goal of the devices studied in this paper is the offshore wind turbines remote maintenance. The use of offshore wind turbines can contribute to the achievement of several SDGs, including SDG7 on affordable and clean energy. Plant maintenance requires high standards of safety: onsite operations expose workers to risks that must be managed properly [10–12]. Integration of VR training and teleoperation greatly reduces the risks associated with onsite operations, according to the objectives of SDG 8 which is focused on the achievement of decent work conditions [4, 13].

2 Instruments and Technologies The instruments and technologies used in this paper are twin robots and haptic devices. Twin robots are industrial devices equipped with cameras, sensors, and other tools that allow them to inspect and repair the turbine without the workers’ presence. Twin robots work in tandem: one robot can provide a visual inspection and the other robot can perform the maintenance task; this way the tasks can be done more efficiently and safely. The robots can also be remotely controlled by operators on the ground, who can monitor the progress of the task and make the needed adjustments, further increasing the safety of the operation. Overall, the use of twin robots for the remote maintenance of wind turbines can greatly improve the safety of workers and their working conditions, by reducing the need for workers to climb the turbine, performing tasks in dangerous conditions.

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Wearable haptic devices can provide users with tactile feedback, allowing them to feel the sense of touch in virtual environments [14]. The tactile interaction between human and virtual scenarios enhances the realism and effectiveness of the experience [15], sending a feedback that reproduces a force stimulus [16]. Wearable haptic interfaces help to improve the sense of immersion, making it more effective for learning and skill acquisition [17]. Haptic feedback can improve the performance of tasks such as object manipulation and navigation in VR environments, teleoperation [18] or medical rehabilitation [19].

3 New Handle Development The handles that control collaborative robots are designed to fit the natural shape of the human hand and reduce the amount of force required to grasp and manipulate the tools [20]. They can also be designed to reduce the impact that the hand is exposed to during use. This can help to reduce the risk of hand fatigue and injury and improve the overall comfort and ease of use of the handle. Research on human-robot collaboration in the digital industry aims at improving physical and cognitive ergonomics by reducing mental stress and psychological discomfort that may be experienced by operators when working with robots, in compliance with SDG8. These devices are designed considering different sizes and shapes of the workers’ hands, to ensure that the handle can be used comfortably by a wide range of people [21]. For this reason, 3D scanning technologies [22] can assist in the design process of the device, according to the user’s limb shape [23, 24]. Besides the handle’s design and shape, the way it is used also has a relevant impact on ergonomics. For example, it is important to ensure that the handle is positioned to allow the worker to maintain a natural wrist posture, which can help to reduce the risk of injury [25]. Dedicated interfaces, such as handles, are crucial for the operator to effectively control the twin robots and perform tasks remotely. These interfaces are designed to replicate the physical work environment as closely as possible, which overcomes the limitations of virtual reality and haptic devices. In the specific case study, the use of handles has been shown to greatly improve the operator’s ability to control the end effector and perform tasks with precision and accuracy. The robot used for the experiment session was a Panda Robot by Franka Emika, a 7-degree-of-freedom collaborative robot arm, able to reach and manipulate objects in complex ways and that can be used in a wide range of industrial applications. This robot was chosen also due to its low-friction joints, as the friction force at the joints influences the users’ movement and the given resistance. Collaborative robots, also known as cobots, are designed to work safely alongside humans [26] in industrial applications: one of their key safety features is their ability to detect and respond to physical contact with humans. Two handles are compared and tested, evaluating the comfort and safety, by a questionnaire submitted to a set of users. The first handle (standard handle) is used as a reference to study the improvements of a second handle configuration (new handle assembly) properly developed in this work. The standard handle used for the manipulation tasks has a cylindrical shape and is drilled on the top to allow attachment to the flange of the robot’s head (Fig. 1).

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The simple shape has a little clearance during the tasks but makes the user freer in movements. This feature can distort immersiveness in the virtual environment and test execution. Additionally, the proximity of the haptic devices to the head of the robotic arm makes them difficult to wear, as well as the fact that they are installed on two fingers (index and thumb) that have free movement. For these reasons, the new handle assembly was developed and compared to the first one.

Fig. 1. Standard handle, mounted on a Franka Emika Panda robot: CAD model.

The new handle assembly has a more complex shape and is composed of several parts specifically designed for manipulation tasks on a wind blade. The device has a main handle (Fig. 2a, b), which allows the grip via the three free fingers (little, ring, and middle fingers). In addition, the attachment with the flange of the robot’s head is located below the user’s arm. These features allow the operator to have the other two fingers free to use haptic devices. The shape of the main handle is bent: the profile follows ergonomics practices to make it less tiring and troublesome for the user, while still having a tight grip. The handle was designed with two flexures with respect to the vertical direction: the first bending of 15% as represented in Fig. 2a, and a 28% bending as in Fig. 2b. The other parts that compose the new handle assembly are two shields (Fig. 2c, d), that lock, respectively, the wrist and forearm, to prevent unintended movements. The parts are modelled based on a 3D scan of a human arm, that makes it comfortable and easy to use. The forearm is thus integral to the robot’s head. The shields cover only a portion of the limb and are positioned opposite to each other. In this configuration, the user can exit during the task, making the device safer.

Fig. 2. New handle assembly: (a) handle rear view, (b) handle side view, (c) wrist shield, (d) forearm shield, (e) assembly overall view. (f) assembly mounted on the Panda Robot.

The complete new handle assembly is shown in Fig. 2 e, f. Two rails are added to allow adaptability to different limb lengths of the users being tested, making the device easily reconfigurable. The attachment to the flange of the robotic arm is modeled through a

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topological optimization algorithm. Considering the possible applied loads and reducing the mass of the part as much as possible, the robot arm is able to adequately compensate for the weight force of the component attached to it (Fig. 2e).

4 Devices Testing and Comparison The experimental flowchart setup is shown in Fig. 3a, and it is valid for both the configurations. The user controls the remote robot in the VR environment through the handle, attached to the local robot. The remote robot replicates the movements done by the local robot performing the machining tasks on the wind blade using a milling tool attached to the remote robot. The reaction force generated between the tool and the wind blade is read by the force sensor located on the flange of the remote robot. This signal, reproduced as force feedback, is sent to the haptic devices, worn by the user. The thimbles transmit cutaneous feedback to the user, representing the force applied while performing the task, through a haptic stimulus. Both Fig. 3b, c show the setup used during the trial session. A group of 13 users was selected to participate in a VR training session, testing the two handles with the Franka Emika Panda cobot and the haptic device. The standard handle was made of aluminum, providing less deformability and more stability. Instead, the new handle assembly was made of 3D printed ABS; in fact, the larger volume of this handle, if made of metal, would have increased the weight of the device too much.

(a)

(b)

(c)

Fig. 3. Testing setup. (a) Experiment flowchart. (b) Standard handle, (c) new handle assembly.

4.1 Questionnaire for the Users A questionnaire, shown in Table 1, was submitted to the group of users. The survey proposed five questions comparing the two handles. Participants gave a score between 0 and 4. The questionnaire aimed at gathering feedback on the effectiveness of the training, as well as information about any issues or concerns that the users may have encountered during the test. Overall, the survey was designed to ensure that the VR training was as user-friendly as possible.

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Table 1. The questionnaire submitted to the users. Query

Score1

1

The new handle assembly is easy-to-use for the teleoperation task compared to the standard handle

0 1 2 3 4

2

I feel safe to use the new handle assembly in the teleoperation task compared to the standard handle

0 1 2 3 4

3

I feel comfortable with the new handle assembly in the teleoperation task 0 1 2 3 4 compared to the standard handle

4

I am satisfied with the overall performance of the new handle assembly

0 1 2 3 4

5

I think the overall performance of the new handle assembly outperforms the standard handle

0 1 2 3 4

1 0 = strongly disagree 1 = disagree 2 = neutral 3 = agree 4 = strongly agree

4.2 Comparing the Two Handles Results reported in Table 2 indicate that the standard handle design was preferred over the new handle assembly, due to its safety appeal. The total score column shows a percentage score calculated with respect to the maximum score. A percentage score below 50% indicates a favorable result for the standard handle. Only query 3 shows a positive result for the new design: the score demonstrates that the goal of ergonomics in the new design was reached. By incorporating ergonomic principles into the design, the new handle can provide improved comfort and reduced strain for users, which can ultimately lead to increased productivity and reduced risk of injury. On the contrary, question 2 highlights a low safety perception, related to the shape of the device. The freedom of movement inherent in the simpler structure of the standard handle makes a safer perception of the device. The authors suppose that this is due to the fact that releasing the new handle assembly is perceived as harder requiring more attention and a more compact series of movements, while disengaging from the standard handle requires no extra effort. However, users have left feedback that makes the evaluation more comprehensive. Indeed, despite safety concerns, the lower force required as well as the inherent design constraints make training sessions easier and less strenuous. Table 2. Results of the questionnaire, divided by queries and scores. Query

Total Score %

Score 0

Score 1

Score 2

Score 3

Score 4

1

42

1

6

3

2

1

2

35

3

5

2

3

0

3

58

0

2

7

2

2

4

46

2

3

5

1

2

5

42

3

2

5

2

1

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5 Conclusions and Future Works The study has demonstrated the potential of using an adaptive designed handle in remote maintenance for renewable energy systems, achieving a safer and more comfortable work, according both to SDG7 and SDG8. Results show that the new handle assembly has a potential role, due to the shape and the comfort perceived by the operators: the main disadvantage found by users is the feeling of safety, compared with the reference standard handle. These considerations lead to suggest that a trade-off between safety and ease of use can be a solution for future developments. Indeed, a new device with a smaller volume but keeping the advantages of the new design, such as the custom shaping, is currently under design. This will make the device easier to handle and maneuver in tight spaces, while still providing the comfort and ergonomic benefits of the original design. Regarding safety, a passive magnet-based release system is being studied. Authors plan to evaluate the handle in different scenarios and conditions to ensure its usability and effectiveness in different maintenance tasks.

References 1. Falck, A.C., Örtengren, R., Högberg, D.: The impact of poor assembly ergonomics on product quality: a cost–benefit analysis in car manufacturing. Hum. Factors Ergon. Manuf. Serv. Ind. 20(1), 24–41 (2010) 2. Koumaditis, K., Chinello, F., Mitkidis, P., Karg, S.: Effectiveness of virtual versus physical training: the case of assembly tasks, trainer’s verbal assistance, and task complexity. IEEE Comput. Graphics Appl. 40(5), 41–56 (2020) 3. Grossman, R., Salas, E.: The transfer of training: what really matters. Int. J. Train. Dev. 15(2), 103–120 (2011) 4. Radhakrishnan, U., Chinello, F., Koumaditis, K.: Immersive virtual reality training: three cases from the danish industry. In: 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pp. 1–5 (2021) 5. Radhakrishnan, U., Koumaditis, K., Chinello, F.: A systematic review of immersive virtual reality for industrial skills training. Behav. Inf. Technol. 40(12), 1310–1339 (2021) 6. Wu, Y., Chan, W.L., Li, Y., Tee, K.P., Yan, R., Limbu, D.K.: Improving human-robot interactivity for tele-operated industrial and service robot applications. In: 2015 IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), pp. 153–158 (2015) 7. Marturi, N., et al.: Towards advanced robotic manipulation for nuclear decommissioning: A pilot study on tele-operation and autonomy. In: 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA), pp. 1–8 (2016) 8. Gavish, N., et al.: Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks. Interact. Learn. Environ. 23(6), 778–798 (2015) 9. Prattichizzo, D., Chinello, F., Pacchierotti, C., Malvezzi, M.: Towards wearability in fingertip haptics: a 3-dof wearable device for cutaneous force feedback. IEEE Trans. Haptics 6(4), 506–516 (2013) 10. Ren, Z., Verma, A.S., Li, Y., Teuwen, J.J., Jiang, Z.: Offshore wind turbine operations and maintenance: a state-of-the-art review. Renew. Sustain. Energy Rev. 144, 110886 (2021) 11. Mentes, A., Turan, O.: A new resilient risk management model for offshore wind turbine maintenance. Saf. Sci. 119, 360–374 (2019)

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12. ISO: Occupational health and safety management systems — Requirements with guidance for use. ISO 40015:2018 (2018) 13. Linn, C., Bender, S., Prosser, J., Schmitt, K., Werth, D.: Virtual remote inspection—a new concept for virtual reality enhanced real-time maintenance. In: 2017 23rd International Conference on Virtual System & Multimedia (VSMM), pp. 1–6 (2017) 14. Singhala, M., Brown, J.D.: Prefatory study of the effects of exploration dynamics on stiffness perception. In: 2020 IEEE Haptics Symposium (HAPTICS), pp. 128–133 (2020) 15. Pacchierotti, C., Sinclair, S., Solazzi, M., Frisoli, A., Hayward, V., Prattichizzo, D.: Wearable haptic systems for the fingertip and the hand: taxonomy, review, and perspectives. IEEE Trans. Haptics 10(4), 580–600 (2017) 16. Franco, L., Salvietti, G., Prattichizzo, D.: Command acknowledge through tactile feedback improves the usability of an EMG-based interface for the frontalis muscle. In: 2019 IEEE World Haptics Conference (WHC), pp. 574–579 (2019) 17. Pacchierotti, C., Meli, L., Chinello, F., Malvezzi, M., Prattichizzo, D.: Cutaneous haptic feedback to ensure the stability of robotic teleoperation systems. Int. J. Robot. Res. 34(14), 1773–1787 (2015) 18. Escobar-Castillejos, D., Noguez, J., Neri, L., Magana, A., Benes, B.: A review of simulators with haptic devices for medical training. J. Med. Syst. 40, 1–22 (2016) 19. Dragusanu, M., Troisi, D., Villani, A., Prattichizzo, D., Malvezzi, M.: HAPP: a haptic portable pad for hand disease manual treatment. In: 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 345–350 (2022) 20. Lorenzini, M., Lagomarsino, M., Fortini, L., Gholami, S., Ajoudani, A.: Ergonomic humanrobot collaboration in industry: a review. Front. Robot. AI 9, 262 (2023) 21. Melo, M., Vasconcelos-Raposo, J., Bessa, M.: Presence and cybersickness in immersive content: Effects of content type, exposure time and gender. Comput. Graph. 71, 159–165 (2018) 22. Valigi, M.C., Logozzo, S., Butini, E., Meli, E., Marini, L., Rindi, A.: Experimental evaluation of tramway track wear by means of 3D metrological optical scanners. In: Proceedings of the 11th International Conference on Contact Mechanics and Wear of Rail/Wheel Systems (CM2018), pp. 1007–1012 (2018) 23. Logozzo, S., Valigi, M.C., Malvezzi, M.: Modelling the human touch: a basic study for haptic technology. Tribol. Int. 166, 107352 (2022) 24. Valigi, M.C., Logozzo, S., Canella, G.: A new automated 2 DOFs 3D desktop optical scanner. In: Advances in Italian Mechanism Science: Proceedings of the First International Conference of IFToMM ITALY, pp. 231–238 (2017) 25. Fellows, G., Freivalds, A.: Ergonomics evaluation of a foam rubber grip for tool handles. Appl. Ergon. 22(4), 225–230 (1991) 26. Dragusanu, M., et al.: The DressGripper: a collaborative gripper with electromagnetic fingertips for dressing assistance. In: 2022 IEE 18th International Conference on Automation Science and Engineering (2022)

Joint Stiffness Analysis and Regulation for Underactuated Soft Grippers Based on Monolithic Structure Mihai Dragusanu1 , Danilo Troisi1,2 , Domenico Prattichizzo1,3 , and Monica Malvezzi1(B) 1

Department of Information Engineering and Mathematics, University of Siena, Siena, Italy [email protected] 2 Department of Information Engineering, University of Pisa, Pisa, Italy 3 Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy

Abstract. Underactuated tendon-driven fingers are a simple and effective solutions for realizing robotic grippers and hands whose range of applications is very wide and could contribute to accomplish Sustainable Development Goals (SDG), as for instance SDG8 (Decent work and economic growth) and 9 (Industry, Innovation and Infrastructure). One of the main drawback of these robotic fingers is that, due to the small number of actuators, they lacks in dexterity and are poorly adaptable to different tasks. In this paper, we introduce a passive elastic joint to be implemented in monolithic robotic fingers in which the stiffness can be actively regulated by applying a pre-compression to the structure, controlled by a twistedstring actuator (TSA). The paper describes the working principle of the joint and investigates on the relationship between pre-compression and flexural stiffness both with numerical simulations and with experimental measures. Keywords: SDG8 · SDG9 · soft robotics · robotic grippers · Twisted String Actuator · service systems for sustainability

1 Introduction The global Sustainable Development Goals (SDGs) are going to guide several aspects of our everyday lives, spacing from technical to business, ethical, political, legal and socioeconomic. Robotics is a quite young discipline with respect to other, well established, ones, but nevertheless has a relevant potential in contributing to SDG accomplishment [1, 2]. An increasing interest in developing soft robotic devices, as for instance grippers [3] and hands [4] has been motivated by the development of new materials, technologies, and efficient design methodologies for largely deformable structures. Soft robotics opens new technological and application opportunities contributing to SDG achievements [5] and new applications of robots in unstructured environments, where soft robotic devices can be effectively employed, are becoming relevant [6]. Authors MD and DT Equally contributed to this work. c The Author(s), under exclusive license to Springer Nature Switzerland AG 2023  V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 492–499, 2023. https://doi.org/10.1007/978-3-031-32439-0_56

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More specifically, robotic grasping and manipulation is a subject that has challenged robotics researchers and engineers since the beginning, and it is becoming more and more important as robotic applications in new and unstructured environments and applications increase. Notwithstanding a large amount of literature and devices available, the research on this topic is still lively and several theoretical as well as operative problems are still open. Soft manipulation represents a particularly effective solution in unstructured and uncertain operative environments since it overcomes the sensing limitations in defining object location and shape [7]. Soft hands and grippers are simply closed over the object and the intrinsic compliance allows the hand to adapt to different object shapes. They can furthermore exploit environmental constraints for compensating the lack of controllable degrees of freedom. More specifically, hand compliance properties, particularly joint stiffness, play an important role in defining the properties of a robotic grasp [8]. One of the drawbacks of this type of hands and grippers is represented by the lack of dexterity and manipulation capabilities, due to the limited number of actuators: once the robotic finger is manufactured and assembled, its closure movement and its grasping capabilities cannot be modified anymore.

Fig. 1. The developed elastic joint with controllable stiffness applyed to the proximal joint of a monolithic robotic finger, trajectories followed by the fingertip obtained for three different values of the proximal joint stiffness, obtained applying different pre-compression forces to the joint (indicated with arrows): (a) low stiffness; (b) medium stiffness; (c) maximum stiffness.

In this paper, we present a compliant wave-shaped joint, that can be used to assemble monolithic gripper finger structures in which the joint bending stiffness can be actively modified by applying a controllable pre-compression. Varying the stiffness of the joints and applying the methodology introduced in [9] and extended in [10], different tasks can be performed by the same gripper. The finger structure considered in this paper has been introduced in [11], it consists of monolithic fingers with wave-shaped elastic joints where the elastic properties can be regulated in the design and manufacture phases by changing joints’ geometrical shape and dimension. In this work, we seek to overcome the limitations of the solution presented in [11] by proposing a way for controlling and adapting finger joint stiffness beyond its fabrication and assembly, during gripper operative life. We started from the monolithic soft-rigid finger structure based on wave-joints [11], introducing a new system, based on TSA (twisted string actuation), for regulating joint stiffness, obtained by applying a pre-compression of the joint. The pre-compression, applied by the TSA, introduces a stress/deformation state in the joint

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that modifies its bending stiffness and therefore, according to [9], modify finger closure motion and gripper grasping capabilities. In Fig. 1 a prototype of a finger composed of two phalanges is shown, in which the stiffness of the proximal joint can be regulated by means of a TSA. Three different trajectories obtained for three compression values are shown. By regulating joint stiffness the closure motion of the finger can be modified, allowing the gripper to perform different tasks (e.g. precision grasp, power grasp or in-hand manipulation). An example of application of this joint is shown in Fig. 1, in which a compliant robotic finger with a structure similar to the one described in [11], and where the stiffness od the proximal joint can be regulated by applying a pre-compression by means of a TSA. It’s evident how stiffness variation in the proximal joint influences the finger closure motion and in particular fingertip trajectory. This paper in particular focuses on the single joint and proposes the characterization of three cases, both with numerical FEM–based analysis and with a set of experiments.

2 Wave Joint with Variable Stiffness: Description and Model 2.1

The Wave-Gripper Structure

The monolithic soft-rigid finger structure is composed of compliant wave-shaped elements, introduced as wave-joints in [11]. Each joint has a simple sinusoidal wave shape created and parametrically defined by using CAD software as a function of a few parameters: the length of the wave l0 , number of ridges ns , the thickness t, the height of the wave h and the width w. In [11] we characterized the joint in terms of bending stiffness, analyzing how this parameter is affected by joint geometrical parameters. A twisted string actuator has been used to apply the pre–compression to the joint. The TSA converts the rotary motion into linear by twisting a set of parallel strings (two in our case) that are connected on one side to a rotary motor on the other to a linear moving element. Thanks to the TSA characteristics, small-size motors with high speed and low torque can be used to create a very high force and, moreover a cheap, lightweight, and compact linear transmission system [12, 13]. In this paper, the strings were made of polyethylene (Dyneema fiber, Japan), due to its good strength with limited weight (Fig. 2a). When a load Fn parallel to the wave is applied (compression load), the corresponding stiffness can be approximately evaluated as: kw =

2Ew J , ns h3

(1)

where Ew is the Young’s coefficient for joint material and J is wave cross section 3 moment of inertia, ( J = wt 12 . ) This simplified expression for the normal stiffness is based on the hypothesis that when a compression or tension load is applied to the wave– joint, the wave ridges are subject to a pure bending solicitation. The stiffness kw can be considered approximately constant until the ridges assume a “packed” configuration. By compressing the wave joint, it become stiffer also in the bending direction. In this work we regulate joint bending stiffness, by applying a pre–compression by means of the TSA. This element allows to actively change joint stiffness after its fabrication, in an active and controllable way.

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2.2 Overview on Twisted String Actuators In [14, 15] the TSA system’s kinematics and dynamics model is presented. We report here the main relationships. Let us indicate with n the number of strings, with rs string radius, with r the helix radius, with L the length of the strings, with p the length of the actuator when the strings are twisted by an angle θ (motor rotation angle). The length p can be evaluated as a function of L and θ as follows (direct kinematics relationship):  (2) p = L2 − r2 θ2 . From eq. (2) the differential kinematic relationship can be easily evaluated as dp r2 θ r2 θ = −√ . =− dθ p L2 − r2 θ2

(3)

By applying the Principle of Virtual Works it’s possible to verify that the relationship between the torque applied to the motor τt and the pulling force Fn that the actuator applies is given by p (4) Fn = 2 τ. r θ Let us assume that all the strings are equal and are made of a material characterized by a Young’s modulus E. The tensile stiffness can be evaluated, for each string, as πEr 2 ks = Ls s , where Ls is the length of the string when no loads are applied on it. When a tensile force Fs is applied to the string, its length increases to the value L such that Fs = ks (L − Ls )

(5)

Assuming that all the strings in the TSA are equally stretched when a load F is applied to it, it results that Fn = nFs . By elaborating the above equations it’s possible to evaluate the TSA stiffness value as [14]:   ∂F 1 p2 1 KT SA = = nks − + 2 . (6) ∂p L0 (p + r2 θ2 )3/2 p2 + r 2 θ 2

3 Joint Characterization 3.1 Characterization Based on FEM Analysis Three different wave joints were considered in the analysis, with a different number of ridges and lengths, specifically ns = 3, 4, 5 and an initial length l0 of the flexible part respectively equal to 30 mm, 36 mm and 42 mm (see Fig. 2a). This set of values has been chosen to be sufficiently representative and manageable both in simulation and in the experiments in terms of data amount. Each compliant wave–joint consist of a single module 3D–printed in Acrylonitrile Butadiene Styrene (ABS). Each sample is composed of a rigid part and a compliant wave–shaped part. A homogeneous, isotropic linear-elastic constitutive model was assumed for the material. The lower part of the joint was constrained, while on the upper part two forces Fn and Ft were applied to simulate the TSA tendon action for joint compression and the tendon force applied to bend the joint, respectively. For both the forces the direction perpendicular to the upper face (compression); Fn magnitude was varied from 0 to 30 N, while Ft magnitude was varied from 0 to 5 N, in accordance to the forces applied in the experimental tests.

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Fig. 2. (a) CAD models of the three analysed joints, with ns = 3, ns = 4, and ns = 5. (b) Results of the joint characterization based on FEM analysis. Compression test, displacement in the z direction as a function of the force Fn applied by the TSA, for three different joints with ns = 3, ns = 4, and ns = 5.

3.2

Compression Tests

A first set of tests were realized to analyze the joint behavior when a compression load Fn , corresponding to the action applied by the TSA, is applied. In this set of tests, the force Ft due to the tendon providing joint bending was not applied. A force varying from 0 to 20 N was applied to joints with ns = 3 and ns = 4, a force varying from 0 to 30 N was applied to the joint with ns = 5. Results are shown in Fig. 2b in terms of displacement in the z direction (corresponding to the compression force direction) of the upper part of the joint as a function of the magnitude of the applied force. A nearly linear relationship can be observed for forces lower than 20 N for all three cases. This result shows that, in case of normal forces, the joint can be modeled with a reasonable approximation as a linear-elastic element, with a constant stiffness value kw . that can be approximated as Eq. (1). 3.3

Compression and Bending Tests

A second set of simulations were performed to analyze the combination of TSA and the bending tendon, i.e. by applying different combinations of Fn and Ft values. In this case, Fn varied in the range between 0 to approximately 20 N, and was calculated as a function of TSA motor adsorbed current, τ , by means of eq. (4), in order to obtain values comparable with the experimental ones described in the following part, while Ft varied from 0 to 5 N in all the three joints. The first row of Fig. 4 reports the obtained results in terms of joint rotation angle as a function of Ft , for different values of τ . The results show, as expected, how by increasing TSA force Fn joint rotation angle decreases, i.e. joint stiffness increases. This effect is more evident as the joint length l0 increases.

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3.4 Characterization Based on Experimental Tests

Fig. 3. Experimental setup for joint characterization, photo and scheme. In the test, actuation force is measured by a dynamometer, while joint bending angle is measured by an IMU.

In Fig. 3 an image and a scheme of the experimental setup for joint characterization are shown. The testing setup is composed of an inertial measurement unit IMU Xsens Mi-3 (Xsens, NL) mounted on the mobile part of the joint, used to measure its orientation angle when the actuation tendon is pulled, a digital dual-range Vernier dynamometer (Vernier Software & Technology, US) with an accuracy of 0.05 N and a microcontroller (OpenCM9.04, Robotis) is used to control the TSA, actuated by a Dynamixel XL330M077-T motor, characterised by stall torque of 0.228 Nm at 6.0 V. All the samples described above have been evaluated in the same way and under the same conditions for 10 defined TSA motor currents (τ ) during the twisting. Once the TSA motor reached the required τ value, the tester started to pull the tendon connected to the dynamometer, with a force in the range 1-5 N with steps of 1 N for each torque creating a step force function profile with a time step of 5 s. Each test was repeated 3 times. Finally, for each sample, when the motor reached the maximum torque, the corresponding joint final length was measured. Data from force and IMU sensors were collected at a frequency of 100 Hz and then processed using MATLAB. For each step of the acquired force profile, the average was evaluated and associated with the corresponding average of the step of the angles. In the second row of Fig. 4 the results for the five most representative τ values, approximately corresponding to the ones used for the FEM simulations, for the three joint samples, are reported. The three diagrams correspond to the three representative joints previously introduced, with ns = 3, 4, 5, respectively. In each diagram, the rotation angle is reported as a function of the force applied to the tendon. It is worth to notice that, as expected, as the TSA force increases, the bending angle of decreases, indicating that the joint stiffness increases. The results are in an acceptable agreement with the ones obtained from the simulations, as it can be observed by comparing the subfigures (a)-(d), (b)-(e), and (c)-(e).

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Fig. 4. Results of single joint characterization with τ1 = 12 mA, τ2 = 38 mA, τ3 = 80 mA, τ4 = 160 mA, τ5 = 290 mA. (a),(b),(c) Results of FEM analysis. (d),(e),(f) Results of experimental characterization (a,d) nr = 3. (b,e) nr = 4.

4 Conclusion In this paper, we presented a possible solution for realizing underactuated robotic grippers where the stiffness of the passive joints can be regulated. This feature increases the adaptability and versatility of the gripper, allowing it to be used n multiple tasks, without the need for adjustments and substitution of components. The structure of the gripper is monolithic, this reduces the need of components and operations in the prototyping phase. The use of a single material is also useful at the end of the gripper operative life, reducing issues related to its disposal. Flexural joint stiffness is controlled by regulating a pre–compression to the joint by means of a TSA. Stiffness regulation does not require high dynamics properties, so the TSA motor can be sufficiently small to be easily embedded inside the rigid parts of the modules composing the finger and requires a small amount of energy. Furthermore, in some cases in which the presence of actuators and electronics components close to the fingers could be a problem (e.g. in food handling, underwater manipulation, etc.), and if such a regulation is required una tantum, stiffness regulation could be realized manually, for instance by means of a screw. In this paper in particular we focused on the characterization of a single joint, in future developments of this work we apply it to a multifingered gripper and we further investigate how tendon actuation and joint stiffness regulation can be dynamically combined.

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References 1. Mai, V., et al.: The role of robotics in achieving the united nations sustainable development goals-the experts’ meeting at the 2021 IEEE/RSJ IROS workshop [industry activities]. IEEE Robot. Autom. Mag. 29(1), 92–107 (2022) 2. Shintake, J.: Green robotics: toward realization of environmentally friendly soft robots. J. Robot. Mechatron. 34(2), 270–272 (2022) 3. Shintake, J., Cacucciolo, V., Floreano, D., Shea, H.: Soft robotic grippers. Adv. Mater. 30(29), 1707035 (2018) 4. Deimel, R., Brock, O.: A novel type of compliant and underactuated robotic hand for dexterous grasping. Int. J. Rob. Res. 35(1–3), 161–185 (2016) 5. Tan, Y.J.: Harnessing the circular economy to develop sustainable soft robots. Sci. Rob. 7(63), eabn8147 (2022) 6. Quaglia, G., Tagliavini, L., Colucci, G., Vorfi, A., Botta, A., Baglieri, L.: Design and prototyping of an interchangeable and underactuated tool for automatic harvesting. Robotics 11(6), 145 (2022) 7. Deimel, R., Brock, O.: Soft hands for reliable grasping strategies. In: Verl, A., Albu-Sch¨affer, A., Brock, O., Raatz, A. (eds.) Soft Robotics, pp. 211–221. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-44506-8 18 8. Ruiz Garate, V., Pozzi, M., Prattichizzo, D., Ajoudani, A.: A bio-inspired grasp stiffness control for robotic hands. Frontiers Robot. AI 5, 89 (2018) 9. Salvietti, G., Hussain, I., Malvezzi, M., Prattichizzo, D.: Design of the passive joints of underactuated modular soft hands for fingertip trajectory tracking. IEEE Robot. Autom. Lett. 2(4), 2008–2015 (2017) 10. Hussain, I., et al.: Design and prototyping soft-rigid tendon-driven modular grippers using interpenetrating phase composites materials. Int. J. Robot. Res. 39(14), 1635–1646 (2020) 11. Dragusanu, M., Achilli, G.M., Valigi, M.C., Prattichizzo, D., Malvezzi, M., Salvietti, G.: The wavejoints: a novel methodology to design soft-rigid grippers made by monolithic 3d printed fingers with adjustable joint stiffness. In: 2022 International Conference on Robotics and Automation (ICRA). IEEE, pp. 6173–6179 (2022) 12. Tsabedze, T., Hartman, E., Abrego, E., Brennan, C., Zhang, J.: TSA-BRAG: a twisted string actuator-powered biomimetic robotic assistive glove. In: 2020 International Symposium on Medical Robotics (ISMR). IEEE, pp. 159–165 (2020) 13. Lee, D., Kim, D.H., Che, C.H., In, J.B., Shin, D.: Highly durable bidirectional joint with twisted string actuators and variable radius pulley. IEEE/ASME Trans. Mechatron. 25(1), 360–370 (2019) 14. Palli, G., Natale, C., May, C., Melchiorri, C., Wurtz, T.: Modeling and control of the twisted string actuation system. IEEE/ASME Trans. Mechatron. 18(2), 664–673 (2012) 15. W¨urtz, T., May, C., Holz, B., Natale, C., Palli, G., Melchiorri, C.: The twisted string actuation system: modeling and control. In: 2010 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. IEEE, pp. 1215–1220 (2010)

Author Index

A Achilli, Gabriele Maria 476, 484 Adduci, Rocco 97 Alampay, Micah J. P. 154 Alonso Ortuzar, Ángela 181 Alonso-Reig, María 37 Altuzarra, Oscar 55 Amici, Cinzia 367 Antonelli, Mattia 333 Archetti, Ivan 367 Archetti, Leonardo 367

Chuev, K. V. 115 Ciappi, Gabriele 468 Cinzia, Amici 459 Ciulli, Enrico 199 Clochiatti, Enrico 47 Colombo, Federico 307 Colucci, Giovanni 136, 278 Cornagliotto, Valerio 162 Corves, Burkhard 19 Cosco, Francesco 97 Curcio, Elio Matteo 253

B Basoalto, Cristian 19 Bazanchuk, G. A. 343 Berselli, G. 65 Bettega, Jason 89 Bjerkefors, Anna 333 Borboni, Alberto 359, 367 Boscariol, Paolo 47, 290 Botta, Andrea 136 Bracco, Giovanni 11 Brancati, Renato 3, 217 Brusa, Eugenio 393 Bruzzone, Fabio 420 Bruzzone, Luca 65 C Canton, Alice 270 Carbone, Giuseppe 97, 253 Cardoso Palomares, Miguel Antonio Cardoso-Palomares, M. A. 324 Carnì, Domenico Luca 253 Casarez-Duran, A. A. 324 Cascino, Alessio 468 Caselli, Elena 333 Català, P. 191 Cazares Duran, Adolfo Angel 315 Ceccarelli, Marco 241 Cerminara, Arnaldo Michele 97 Chinello, Francesco 484

D Dagna, Alberto 393 De Falco, Domenico 217 Delprete, Cristiana 393 Di Massa, Giandomenico 3, 217 Digo, Elisa 73 Dona’, Domenico 81 Dragusanu, Mihai 492 E Egorova, O. V.

315

343

F Faglia, Rodolfo 367 Fang, Cheng 484 Fanghella, Pietro 65 Faraggiana, Emilio 11 Fettin, Jannik 105 Florescu, Florin 233 Franco, Walter 350 G Galvagno, Enrico 441 Gasparetto, Alessandro 47 Gastaldi, Chiara 393 Gastaldi, Laura 73, 162, 333 Genovese, Andrea 3

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 V. Petuya et al. (Eds.): I4SDG 2023, MMS 134, pp. 501–503, 2023. https://doi.org/10.1007/978-3-031-32439-0

502

Author Index

Giorgi, Giuseppe 11 Guerra, Elena 382

Moldovan, Macedon 27 Mundo, Domenico 97, 253

H Harada, Ken 146 Hernandez, Pedro Gomez 484 Herrero Villalibre, Saioa 181 Hoshiba, Kotaro 146 Hüsing, Mathias 19

N Nehme, Bechara 262 Nodehi, Shahab E. 65

I Incardona, Walter

P Pagano, Stefano 217 Paredes Rojas, Juan Carlos 315 Paredes-Rojas, J. C. 324 Passarella, Francesco 298 Pastorelli, Stefano 73, 162, 333 Perevuznik, V. S. 115 Perrelli, Michele 97 Petracca, Ermando 11 Petuya, Víctor 37, 55 Pierart, Fabián G. 19 Polito, Michele 73, 162 Popescu, Ioan-Emil 233 Prattichizzo, Domenico 492

225

J Janssens, Luc 333 Jiang, Ming 146, 154 Jordi, L. 191 K Kalligeros, Stamatis 411 Kawabata, Masato 146 Ketkar, Satish 403 Khurtasenko, A. V. 115 Kobayashi, Tsune 209 Kurakov, S. V. 343 Kurata, Mari 146 L Lamonaca, Francesco 253 Landi, Luca 451 Lentini, Luigi 307 Lenzo, Basilio 81, 270 Logozzo, Silvia 451, 476, 484 Lovasz, Erwin-Christian 171, 233, 241 Lovato, Stefano 270 M Maffiodo, Daniela 225 Maletta, Carmine 253 Malvezzi, Monica 476, 492 Malyshev, D. I. 115 Mantriota, Giacomo 298 Massaro, Matteo 270 Matsuura, Daisuke 209 Meli, Enrico 468 Memida, Shoko 127 Mendikoa, Iñigo 37 Miretti, Federico 430 Misul, Daniela 430 Miura, Satoshi 127

O Oarcea, Alexandru

Q Quaglia, Giuseppe

171, 233, 241

55, 136, 278

R Raghavan, Madhu 403 Raparelli, Terenziano 225, 307 Reina, Giulio 298 Richiedei, Dario 89, 290 Righetti, Giovanni 270 Rindi, Andrea 468 Roberto, Bussola 459 Rocca, Ernesto 217 Rodinò, Stefano 253 Romagnoli, Lorenzo 375 Rosati, Giulio 81 Rosso, Carlo 420 Rusea, Denisa 27 Rybak, L. A. 115 S Saab, Christian 262 Scalera, Lorenzo 47 Schappler, Moritz 105 Shakhovska, Nataliya 359 Shidore, Neeraj 403 Siciliano, Marco 253

Author Index

Sirigu, Massimo 11 Skorski, Justin 403 Stathopoulos, Ioannis 411 Sterneck, Tim 105 Sticlaru, Carmen 241 Sugahara, Yusuke 146, 154 T Tagliavini, Luigi 55 Takeda, Yukio 136, 146, 154 Tamellin, Iacopo 89, 290 Tiboni, Monica 459 Tikhomirov, G. V. 343 Tivadar, Demjen 241 Torres San Miguel, Christopher René 315 Torres-SanMiguel, C. R. 324 Tota, Antonio 441 Trevisani, Alberto 89, 290 Trivella, Andrea 307 Troisi, Danilo 492 Tulcan, Elida-Gabriela 171

503

U Uehara, Takahiro 146 Urriolagoitia-Calderón, G. M. 324 V Valigi, Maria Cristina 451, 484 Vanlandewijck, Yves 333 Veciana, J. M. 191 Velardocchia, Mauro 441 Vella, Angelo Domenico 441 Vernados, Thomas 411 Villegas, Claudio 19 Visa, Ion 27 Visconte, Carmen 278 W Wright, Jacob

403

Z Zaharia, Radu Sebastian Zerbato, Luca 441

233