activity
20192022
most citedSensor Fusion for Predictive Control of Human-Prosthesis-Environment Dynamics in Assistive Walking: A Survey

22 citations · 55 across the 7 of their papers we have counts for

collaborators

10 papers

cs.RO20221 cited

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…

cs.RO20212 cited

Mapping Human Muscle Force to Supernumerary Robotics Device for Overhead Task Assistance

Jianwen Luo, Sicong Liu, Chengyu Lin +6

Supernumerary Robotics Device (SRD) is an ideal solution to provide robotic assistance in overhead manual manipulation. Since two arms are occupied for the overhead task, it is des…

cs.RO20201 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.RO2020

Robotic Cane as a Soft SuperLimb for Elderly Sit-to-Stand Assistance

Xia Wu, Haiyuan Liu, Ziqi Liu +6

Many researchers have identified robotics as a potential solution to the aging population faced by many developed and developing countries. If so, how should we address the cogniti…

cs.LG202010 cited

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…

cs.RO20195 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…