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Bio-inspired robotic impedance adaptation for human-robot collaborative tasks

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Abstract

To improve the robotic flexibility and dexterity in a human-robot collaboration task, it is important to adapt the robot impedance in a real-time manner to its partner’s behavior. However, it is often quite challenging to achieve this goal and has not been well addressed yet. In this paper, we propose a bio-inspired approach as a possible solution, which enables the online adaptation of robotic impedance in the unknown and dynamic environment. Specifically, the bio-inspired mechanism is derived from the human motor learning, and it can automatically adapt the robotic impedance and feedforward torque along the motion trajectory. It can enable the learning of compliant robotic behaviors to meet the dynamic requirements of the interactions. In order to validate the proposed approach, an experiment containing an anti-disturbance test and a human-robot collaborative sawing task has been conducted.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 61861136009, 61811530281).

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Authors and Affiliations

  1. School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China

    Chao Zeng & Chenguang Yang

  2. TAMS Group, Informatics, University of Hamburg, Hamburg, D22527, Germany

    Zhaopeng Chen

Authors
  1. Chao Zeng
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  2. Chenguang Yang
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  3. Zhaopeng Chen
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Correspondence to Chenguang Yang.

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Zeng, C., Yang, C. & Chen, Z. Bio-inspired robotic impedance adaptation for human-robot collaborative tasks. Sci. China Inf. Sci. 63, 170201 (2020). https://doi.org/10.1007/s11432-019-2748-x

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  • DOI: https://doi.org/10.1007/s11432-019-2748-x

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