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Based on human-like variable admittance control for human–robot collaborative motion

Published online by Cambridge University Press:  11 April 2023

Chengyun Wang Open the ORCID record for Chengyun Wang [Opens in a new window]  and
Jing Zhao Open the ORCID record for Jing Zhao [Opens in a new window]
Chengyun Wang
Affiliation:
Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, China
Jing Zhao*
Affiliation:
Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, China
*
*Corresponding author. E-mail: zhaojing@bjut.edu.cn
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Abstract

Admittance control of the robot is an important method to improve human–robot collaborative performance. However, it displays poor matching between admittance parameters and human–robot collaborative motion. This results in poor motion performance when the robot interacts with the changeable environment (human). Therefore, to improve the performance of human–robot collaboration, the human-like variable admittance parameter regulator (HVAPR) based on the change rate of interaction force is proposed by studying the human arm’s static and dynamic admittance parameters in human–human collaborative motion. HVAPR can generate admittance parameters matching with human collaborative motion. To test the performance of the proposed HVAPR, the human–robot collaborative motion experiment based on HVAPR is designed and compared with the variable admittance parameter regulator (VAPR). The satisfaction, recognition ratio, and recognition confidence of the two admittance parameter regulators are statistically analyzed via questionnaire. Simultaneously, the trajectory and interaction force of the robot are analyzed, and the performance of the human–robot collaborative motion is assessed and compared using the trajectory smoothness index and average energy index. The results show that HVAPR is superior to VAPR in human–robot collaborative satisfaction, robot trajectory smoothness, and average energy consumption.

Keywords

human–robot collaborative motionhuman-like variable admittance controlhuman–robot interactionevaluation of human–robot collaborative performancecompliant control
Type
Research Article
Information
Robotica , Volume 41 , Issue 7 , July 2023 , pp. 2155 - 2176
Copyright
© The Author(s), 2023. Published by Cambridge University Press

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