4 papers
Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration
Xinghao Zhu, Zixi Liu, Shalin Jain +18
Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains challenging. We present Contact…
AGILE: A Comprehensive Workflow for Humanoid Loco-Manipulation Learning
Huihua Zhao, Rafael Cathomen, Lionel Gulich +6
Recent advances in reinforcement learning (RL) have enabled impressive humanoid behaviors in simulation, yet transferring these results to new robots remains challenging. In many r…
COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis
Wei Liu, Huihua Zhao, Chenran Li +4
As robots are increasingly deployed in diverse application domains, enabling robust mobility across different embodiments has become a critical challenge. Classical mobility stacks…
X-MOBILITY: End-To-End Generalizable Navigation via World Modeling
Wei Liu, Huihua Zhao, Chenran Li +5
General-purpose navigation in challenging environments remains a significant problem in robotics, with current state-of-the-art approaches facing myriad limitations. Classical appr…