6 papers · 1 filter
RPG: Robust Policy Gating for Smooth Multi-Skill Transitions in Humanoid Fighting
Yucheng Xin, Jiacheng Bao, Yubo Dong +5
Humanoid robots have demonstrated impressive motor skills in a wide range of tasks, yet whole-body control for humanlike long-time, dynamic fighting remains particularly challengin…
Learn Weightlessness: Imitate Non-Self-Stabilizing Motions on Humanoid Robot
Yucheng Xin, Jiacheng Bao, Haoran Yang +6
The integration of imitation and reinforcement learning has enabled remarkable advances in humanoid whole-body control, facilitating diverse human-like behaviors. However, research…
PhyGile: Physics-Prefix Guided Motion Generation for Agile General Humanoid Motion Tracking
Jiacheng Bao, Haoran Yang, Yucheng Xin +7
Humanoid robots are expected to execute agile and expressive whole-body motions in real-world settings. Existing text-to-motion generation models are predominantly trained on captu…
ZeroWBC: Learning Natural Whole-Body Humanoid Interaction from Human Egocentric Data
Haoran Yang, Jiacheng Bao, Yucheng Xin +5
Achieving versatile and natural whole-body humanoid interaction control remains challenging due to the high cost of whole-body teleoperation data. We present ZeroWBC, a teleoperati…
Efficient Collision Detection Framework for Enhancing Collision-Free Robot Motion
Xiankun Zhu, Yucheng Xin, Shoujie Li +3
Fast and efficient collision detection is essential for motion generation in robotics. In this paper, we propose an efficient collision detection framework based on the Signed Dist…
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu +4
Offline Safe Reinforcement Learning (RL) seeks to address safety constraints by learning from static datasets and restricting exploration. However, these approaches heavily rely on…