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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…
Towards Reliable LLM-based Robot Planning via Combined Uncertainty Estimation
Shiyuan Yin, Chenjia Bai, Zihao Zhang +4
Large language models (LLMs) demonstrate advanced reasoning abilities, enabling robots to understand natural language instructions and generate high-level plans with appropriate gr…
KungfuBot2: Learning Versatile Motion Skills for Humanoid Whole-Body Control
Jinrui Han, Weiji Xie, Jiakun Zheng +4
Learning versatile whole-body skills by tracking various human motions is a fundamental step toward general-purpose humanoid robots. This task is particularly challenging because a…
HumanoidGen: Data Generation for Bimanual Dexterous Manipulation via LLM Reasoning
Zhi Jing, Siyuan Yang, Jicong Ao +3
For robotic manipulation, existing robotics datasets and simulation benchmarks predominantly cater to robot-arm platforms. However, for humanoid robots equipped with dual arms and…
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…
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…
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…
Humanoid Whole-Body Locomotion on Narrow Terrain via Dynamic Balance and Reinforcement Learning
Weiji Xie, Chenjia Bai, Jiyuan Shi +4
Humans possess delicate dynamic balance mechanisms that enable them to maintain stability across diverse terrains and under extreme conditions. However, despite significant advance…