5 papers
Preference-Conditioned Multi-Objective RL for Integrated Command Tracking and Force Compliance in Humanoid Locomotion
Tingxuan Leng, Yushi Wang, Tinglong Zheng +2
Humanoid locomotion requires not only accurate command tracking for navigation but also compliant responses to external forces during human interaction. Despite significant progres…
AutoOdom: Learning Auto-regressive Proprioceptive Odometry for Legged Locomotion
Changsheng Luo, Yushi Wang, Wenhan Cai +1
Accurate proprioceptive odometry is fundamental for legged robot navigation in GPS-denied and visually degraded environments where conventional visual odometry systems fail. Curren…
Learning Vision-Driven Reactive Soccer Skills for Humanoid Robots
Yushi Wang, Changsheng Luo, Penghui Chen +7
Humanoid soccer poses a representative challenge for embodied intelligence, requiring robots to coordinate agile locomotion with unreliable visual perception in dynamic environment…
Booster Gym: An End-to-End Reinforcement Learning Framework for Humanoid Robot Locomotion
Yushi Wang, Penghui Chen, Xinyu Han +2
Recent advancements in reinforcement learning (RL) have led to significant progress in humanoid robot locomotion, simplifying the design and training of motion policies in simulati…
HiFAR: Multi-Stage Curriculum Learning for High-Dynamics Humanoid Fall Recovery
Penghui Chen, Yushi Wang, Changsheng Luo +2
Humanoid robots encounter considerable difficulties in autonomously recovering from falls, especially within dynamic and unstructured environments. Conventional control methodologi…