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

Yu, Xinbo, He, Wei, Li, Yanan, Xue, Chengqian, Li, Jianqiang, Zou, Jianxiao and Yang, Chenguang (2019) Bayesian estimation of human impedance and motion intention for human-robot collaboration. IEEE Transactions on Cybernetics. pp. 1-13. ISSN 2168-2267

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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.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Depositing User: Yanan Li
Date Deposited: 27 Aug 2019 13:20
Last Modified: 22 Nov 2019 14:00
URI: http://sro.sussex.ac.uk/id/eprint/85682

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