The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2024
Session ID : 2P1-C07
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Variable Admittance Control using Preferential Bayesian Optimization in Human-Robot Collaboration
*TRAN Duc LiemTasuku YAMAWAKIHiroyuki FUJIWARAMasahito YASHIMA
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Abstract

In physical human-robot collaboration (PHRC) systems, impedance or admittance control is commonly used for safety and flexibility. Moreover, tuning and optimization of the impedance or admittance parameters can enhance the PHRC system’s performance. However, a challenge encountered in parameter optimization within PHRC systems is the selection of an appropriate evaluation function. This paper introduces Preferential Bayesian Optimization as a method for parameter optimization in PHRC settings. Unlike traditional approaches, this method does not require an explicit definition of the evaluation function and instead relies solely on human preference information during the optimization process. The effectiveness of this approach is verified through its application of tuning a variable admittance controller for a 7-degree-of-freedom robot arm.

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© 2024 The Japan Society of Mechanical Engineers
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