22 citations · 65 across the 8 of their papers we have counts for
10 papers
Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptation
Kuangen Zhang, Jiahong Chen, Jing Wang +4
Recognizing human locomotion intent and activities is important for controlling the wearable robots while walking in complex environments. However, human-robot interface signals ar…
Preserving Domain Private Representation via Mutual Information Maximization
Jiahong Chen, Jing Wang, Weipeng Lin +2
Recent advances in unsupervised domain adaptation have shown that mitigating the domain divergence by extracting the domain-invariant representation could significantly improve the…
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…
Off-policy Maximum Entropy Reinforcement Learning : Soft Actor-Critic with Advantage Weighted Mixture Policy(SAC-AWMP)
Zhimin Hou, Kuangen Zhang, Yi Wan +3
The optimal policy of a reinforcement learning problem is often discontinuous and non-smooth. I.e., for two states with similar representations, their optimal policies can be signi…
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…
Sequential Decision Fusion for Environmental Classification in Assistive Walking
Kuangen Zhang, Wen Zhang, Wentao Xiao +3
Powered prostheses are effective for helping amputees walk on level ground, but these devices are inconvenient to use in complex environments. Prostheses need to understand the mot…