Li, C., Liu, J., Teng, T., Wang, S., Calinon, S. and Chen, F. (2025)
Whole-Body Impedance Control of a Humanoid Robot Based on Human-Human Demonstration for Human-Robot Collaboration
In Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (IROS).
Abstract
This paper proposes a novel whole-body impedance control method for the Collaborative dUal-arm Robot manIpulator (CURI) in Human-Robot Collaboration (HRC). The method enables CURI to adapt its physical behavior to human motion while following trajectories learned from human-human demonstrations. A whole-body impedance controller coordinates the robot joints to achieve desired Cartesian space impedance. Collaborative tasks are captured from human-human demonstrations and represented using a Task-parameterized Gaussian Mixture Model (TP-GMM). Electromyography (EMG) sensors record muscle activities to estimate human impedance profiles, which are then mimicked by a variable impedance controller. An adaptive parameter is introduced to adjust robot stiffness based on spatial displacement between the robot and human, ensuring safe and efficient interaction. Experimental validation through confrontational Tai Chi pulling/pushing tasks demonstrates the superiority of the proposed adaptive impedance method over constant impedance control.
Bibtex reference
@inproceedings{CLi25IROS,
author={Li, C. and Liu, J. and Teng, T. and Wang, S. and Calinon, S. and Chen, F.},
title={Whole-Body Impedance Control of a Humanoid Robot Based on Human-Human Demonstration for Human-Robot Collaboration},
booktitle={Proc.\ {IEEE/RSJ} Intl Conf.\ on Intelligent Robots and Systems ({IROS})},
year={2025}
}