7 papers
TopoRetarget: Interaction-Preserving Retargeting for Dexterous Manipulation
Jielin Wu, Shenzhe Yao, Guanqi He +6
Human hand-object demonstrations provide dense reference motions for training dexterous manipulation reinforcement learning (RL) policies through reference tracking. However, to us…
Is Your Trajectory Displacement Safe in Long-tail?
Qiao Sun, Weicheng Zheng, Yixin Huang +1
Long-tail scenarios remain a major bottleneck for autonomous driving evaluation, even as datasets grow by orders of magnitude. Existing evaluation pipelines are rarely human-aligne…
TTT-Parkour: Rapid Test-Time Training for Perceptive Robot Parkour
Shaoting Zhu, Baijun Ye, Jiaxuan Wang +5
Achieving highly dynamic humanoid parkour on unseen, complex terrains remains a challenge in robotics. Although general locomotion policies demonstrate capabilities across broad te…
Hiking in the Wild: A Scalable Perceptive Parkour Framework for Humanoids
Shaoting Zhu, Ziwen Zhuang, Mengjie Zhao +2
Achieving robust humanoid hiking in complex, unstructured environments requires transitioning from reactive proprioception to proactive perception. However, integrating exterocepti…
Deep Whole-body Parkour
Ziwen Zhuang, Shaoting Zhu, Mengjie Zhao +1
Current approaches to humanoid control generally fall into two paradigms: perceptive locomotion, which handles terrain well but is limited to pedal gaits, and general motion tracki…
Playful DoggyBot: Learning Agile and Precise Quadrupedal Locomotion
Xin Duan, Ziwen Zhuang, Hang Zhao +1
Quadrupedal animals can perform agile and playful tasks while interacting with real-world objects. For instance, a trained dog can track and catch a flying frisbee before it touche…