8 papers
KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills
Weiji Xie, Jinrui Han, Jiakun Zheng +6
Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of tracking smooth, low-speed human motions, eve…
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…
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…
InterReal: A Unified Physics-Based Imitation Framework for Learning Human-Object Interaction Skills
Dayang Liang, Yuhang Lin, Xinzhe Liu +3
Interaction is one of the core abilities of humanoid robots. However, most existing frameworks focus on non-interactive whole-body control, which limits their practical applicabili…
Learning Soccer Skills for Humanoid Robots: A Progressive Perception-Action Framework
Jipeng Kong, Xinzhe Liu, Yuhang Lin +4
Soccer presents a significant challenge for humanoid robots, demanding tightly integrated perception-action capabilities for tasks like perception-guided kicking and whole-body bal…