Adaptive Admittance Control for Physical Human-Robot Interaction based on Imitation and Reinforcement Learning-Reference-Cited by-同舟云学术

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Adaptive Admittance Control for Physical Human-Robot Interaction based on Imitation and Reinforcement Learning

Published:2023-11-21 Issue: Volume:31 Page:1-5
ISSN:
Container-title:2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
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Author:

Guo Mou¹,Yao Bitao¹,Ji Zhenrui²,Xu Wenjun²,Zhou Zude¹

Affiliation:

1. School of Mechanical and Electronic Engineering, Wuhan University of Technology,Wuhan,China

2. School of Information Engineering, Wuhan University of Technology,Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks,Wuhan,China

Funder

Hubei Provincial Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10413343/10413344/10413438.pdf?arnumber=10413438

Reference15 articles.

1. Cooperative motion control of a robot and a human

2. Variable impedance control of redundant manipulators for intuitive human-robot physical interaction;Fanny;TRO,2015

3. Deep reinforcement learning for robotic manipulation-the state of the art;Amarjyoti;arXiv preprint,2017

4. A User-Intention Based Adaptive Manual Guidance with Force-Tracking Capabilities Applied to Walk-Through Programming for Industrial Robots

5. Implementation and Test of Human-Operated and Human-Like Adaptive Impedance Controls on Baxter Robot

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