84 citations · 100 across the 4 of their papers we have counts for
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3 papers · 1 filter
cs.RO2020★ 1 cited
How does the structure embedded in learning policy affect learning quadruped locomotion?
Kuangen Zhang, Jongwoo Lee, Zhimin Hou +3
Reinforcement learning (RL) is a popular data-driven method that has demonstrated great success in robotics. Previous works usually focus on learning an end-to-end (direct) policy…
cs.RO2019★ 5 cited
Teach Biped Robots to Walk via Gait Principles and Reinforcement Learning with Adversarial Critics
Kuangen Zhang, Zhimin Hou, Clarence W. de Silva +2
Controlling a biped robot to walk stably is a challenging task considering its nonlinearity and hybrid dynamics. Reinforcement learning can address these issues by directly mapping…
cs.RO2019★ 84 cited
Compare Contact Model-based Control and Contact Model-free Learning: A Survey of Robotic Peg-in-hole Assembly Strategies
Jing Xu, Zhimin Hou, Zhi Liu +1
In this paper, we present an overview of robotic peg-in-hole assembly and analyze two main strategies: contact model-based and contact model-free strategies. More specifically, we…