Model-based reinforcement learning variable impedance control for human-robot collaboration
Abstract Industry 4.0 is taking human-robot collaboration at the center of the production
environment. Collaborative robots enhance productivity and flexibility while reducing …
environment. Collaborative robots enhance productivity and flexibility while reducing …
[HTML][HTML] An Admittance Parameter Optimization Method Based on Reinforcement Learning for Robot Force Control
X Hu, G Liu, P Ren, B Jia, Y Liang, L Li, S Duan - Actuators, 2024 - mdpi.com
When a robot performs tasks such as assembly or human–robot interaction, it is inevitable
for it to collide with the unknown environment, resulting in potential safety hazards. In order …
for it to collide with the unknown environment, resulting in potential safety hazards. In order …
Adaptive Admittance Control for Physical Human-Robot Interaction based on Imitation and Reinforcement Learning
M Guo, B Yao, Z Ji, W Xu, Z Zhou - 2023 29th International …, 2023 - ieeexplore.ieee.org
Physical human-robot interaction (pHRI) is applied in various applications such as hand
guiding of robots in manufacturing. In this paper, an adaptive admittance controller based on …
guiding of robots in manufacturing. In this paper, an adaptive admittance controller based on …