40 citations · 49 across the 7 of their papers we have counts for
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cs.RO2021★ 40 cited
Robotic Knee Tracking Control to Mimic the Intact Human Knee Profile Based on Actor-critic Reinforcement Learning
Ruofan Wu, Zhikai Yao, Jennie Si +2
We address a state-of-the-art reinforcement learning (RL) control approach to automatically configure robotic prosthesis impedance parameters to enable end-to-end, continuous locom…
cs.RO2021★ 4 cited
Reinforcement Learning Enabled Automatic Impedance Control of a Robotic Knee Prosthesis to Mimic the Intact Knee Motion in a Co-Adapting Environment
Ruofan Wu, Minhan Li, Zhikai Yao +3
Automatically configuring a robotic prosthesis to fit its user's needs and physical conditions is a great technical challenge and a roadblock to the adoption of the technology. Pre…
eess.SY2021★ 2 cited
Toward Reliable Designs of Data-Driven Reinforcement Learning Tracking Control for Euler-Lagrange Systems
Zhikai Yao, Jennie Si, Ruofan Wu +1
This paper addresses reinforcement learning based, direct signal tracking control with an objective of developing mathematically suitable and practically useful design approaches.…