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HARP-VLA: Human-Robot Aligned Representation Learning for Vision-Language-Action Model
Xiang Zhu, Puzhen Yuan, Yichen Liu +1
Learning generalizable vision-language-action (VLA) models from large-scale human videos is promising but challenging due to cross-embodiment discrepancies in both visual observati…
Dexora: Open-source VLA for High-DoF Bimanual Dexterity
Zongzheng Zhang, Jingrui Pang, Zhuo Yang +22
Vision-Language-Action (VLA) models have recently become a central direction in embodied AI, but current systems are restricted to either dual-gripper control or single-arm dextero…
Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt
Xiang Zhu, Yichen Liu, Hezhong Li +1
Recent robot learning methods commonly rely on imitation learning from massive robotic dataset collected with teleoperation. When facing a new task, such methods generally require…
Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning
Xinyang Gu, Yen-Jen Wang, Xiang Zhu +4
Humanoid robots, with their human-like skeletal structure, are especially suited for tasks in human-centric environments. However, this structure is accompanied by additional chall…
Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer
Xinyang Gu, Yen-Jen Wang, Jianyu Chen
Humanoid-Gym is an easy-to-use reinforcement learning (RL) framework based on Nvidia Isaac Gym, designed to train locomotion skills for humanoid robots, emphasizing zero-shot trans…
Stylized Table Tennis Robots Skill Learning with Incomplete Human Demonstrations
Xiang Zhu, Zixuan Chen, Jianyu Chen
In recent years, Reinforcement Learning (RL) is becoming a popular technique for training controllers for robots. However, for complex dynamic robot control tasks, RL-based method…