Human-robot co-carrying using visual and force sensing

Yu, Xinbo, He, Wei, Li, Qing, Li, Yanan and Li, Bin (2020) Human-robot co-carrying using visual and force sensing. IEEE Transactions on Industrial Electronics. ISSN 0278-0046

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Abstract

In this paper, we propose a hybrid framework using visual and force sensing for human-robot co-carrying tasks. Visual sensing is utilized to obtain human motion and an observer is designed for estimating control input of human, which generates robot's desired motion towards human's intended motion. An adaptive impedance-based control strategy is proposed for trajectory tracking with neural networks (NNs) used to compensate for uncertainties in robot's dynamics. Motion synchronization is achieved and this approach yields a stable and efficient interaction behavior between human and robot, decreases human control effort and avoids interference to human during the interaction. The proposed framework is validated by a co-carrying task in simulations and experiments.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 05 Aug 2020 06:42
Last Modified: 11 Sep 2020 15:16
URI: http://sro.sussex.ac.uk/id/eprint/92926

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