CUHK Legged Robot Lab
The CUHK Legged Robot Lab develops robust and precise locomotion for legged robots across diverse terrains using reinforcement learning and imitation learning. Their research emphasizes environment-aware perception and learning-based locomotion policies.
Notable achievements
Terrain-adaptive legged robot control, learning-based locomotion policies
Notable work
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
PAEAR: Point Clouds Area Exploration and Active Recognition method driven by reinforcement learning for robotic welding
Yong Tao, Donghua Tan, Fan Ren +6 more
Robotics and Computer-Integrated Manufacturing · 2026
A hierarchical approach to imitation learning for manipulation tasks requiring time varying forces
Rishabh Shukla, Adithya Santhosh, Shaili Gandhi +2 more
Robotics and Computer-Integrated Manufacturing · 2026
Multi-pass cutting parameters optimisation with causal reinforcement learning for deformation control of thin-walled parts
Fengyi Lu, Guanghui Zhou, Chao Zhang +2 more
Robotics and Computer-Integrated Manufacturing · 2026
Wheeled autonomous rover design and control for snow-covered terrain
Austin P. Lines, Adam Gronewold, Joshua Elliot +6 more
Robotics and Autonomous Systems · 2026
MA2MB: Multi-agent mutual-advising model-based reinforcement learning for pursuit and evasion games
Baolin Zhao, Qi Guo, Xiandong Wang +2 more
Robotics and Autonomous Systems · 2026
Learning practically stabilizing output-feedback nonlinear controllers
Kui Xie, Pablo Krupa, Alberto Bemporad
2026