8 papers
PCHC: Enabling Preference Conditioned Humanoid Control via Multi-Objective Reinforcement Learning
Huanyu Li, Dewei Wang, Xinmiao Wang +4
Humanoid robots often need to balance competing objectives, such as maximizing speed while minimizing energy consumption. While current reinforcement learning (RL) methods can mast…
X-Loco: Towards Generalist Humanoid Locomotion Control via Synergetic Policy Distillation
Dewei Wang, Xinmiao Wang, Chenyun Zhang +4
While recent advances have demonstrated strong performance in individual humanoid skills such as upright locomotion, fall recovery and whole-body coordination, learning a single po…
Pro-HOI: Perceptive Root-guided Humanoid-Object Interaction
Yuhang Lin, Jiyuan Shi, Dewei Wang +4
Executing reliable Humanoid-Object Interaction (HOI) tasks for humanoid robots is hindered by the lack of generalized control interfaces and robust closed-loop perception mechanism…
HUSKY: Humanoid Skateboarding System via Physics-Aware Whole-Body Control
Jinrui Han, Dewei Wang, Chenyun Zhang +4
While current humanoid whole-body control frameworks predominantly rely on the static environment assumptions, addressing tasks characterized by high dynamism and complex interacti…
Towards Adaptive Humanoid Control via Multi-Behavior Distillation and Reinforced Fine-Tuning
Yingnan Zhao, Xinmiao Wang, Dewei Wang +5
Humanoid robots are promising to learn a diverse set of human-like locomotion behaviors, including standing up, walking, running, and jumping. However, existing methods predominant…
MoRE: Mixture of Residual Experts for Humanoid Lifelike Gaits Learning on Complex Terrains
Dewei Wang, Xinmiao Wang, Xinzhe Liu +4
Humanoid robots have demonstrated robust locomotion capabilities using Reinforcement Learning (RL)-based approaches. Further, to obtain human-like behaviors, existing methods integ…
Skill-Nav: Enhanced Navigation with Versatile Quadrupedal Locomotion via Waypoint Interface
Dewei Wang, Chenjia Bai, Chenhui Li +4
Quadrupedal robots have demonstrated exceptional locomotion capabilities through Reinforcement Learning (RL), including extreme parkour maneuvers. However, integrating locomotion s…
Adversarial Locomotion and Motion Imitation for Humanoid Policy Learning
Jiyuan Shi, Xinzhe Liu, Dewei Wang +6
Humans exhibit diverse and expressive whole-body movements. However, attaining human-like whole-body coordination in humanoid robots remains challenging, as conventional approaches…