Bayesian estimation of human impedance and motion intention for human-robot collaboration

Yu, Xinbo; He, Wei; Li, Yanan; Xue, Chengqian; Li, Jianqiang; Zou, Jianxiao; Yang, Chenguang

Abstract

This article proposes a Bayesian method to acquire the estimation of human impedance and motion intention in a human-robot collaborative task. Combining with the prior knowledge of human stiffness, estimated stiffness obeying Gaussian distribution is obtained by Bayesian estimation, and human motion intention can be also estimated. An adaptive impedance control strategy is employed to track a target impedance model and neural networks are used to compensate for uncertainties in robotic dynamics. Comparative simulation results are carried out to verify the effectiveness of estimation method and emphasize the advantages of the proposed control strategy. The experiment, performed on Baxter robot platform, illustrates a good system performance.

• Journal Article Type: Article
• Acceptance Date: Aug 13, 2019
• Online Publication Date: Oct 22, 2019
• Publication Date: Apr 1, 2021
• Deposit Date: Oct 24, 2019
• Publicly Available Date: Oct 25, 2019
• Journal: IEEE Transactions on Cybernetics
• Print ISSN: 2168-2267
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 51
• Issue: 4
• Pages: 1822 - 1834
• DOI: https://doi.org/10.1109/tcyb.2019.2940276
• Keywords: Control and Systems Engineering; Human-Computer Interaction; Electrical and Electronic Engineering; Software; Information Systems; Computer Science Applications
• Public URL: https://uwe-repository.worktribe.com/output/4066347