5 papers
RoboCoach: World Models as Active Coaches for Compositional Robot Skills
Jiajun Liu, Yifan Chen, Yichao Liu +7
Long-horizon robot manipulation reuses skills across many task compositions, but improving these compositions with additional end-to-end demonstrations is costly. A practical self-…
Weave: Learning Whole-Body Dexterous Loco-Manipulation from Human-Object Interactions
Liu Cao, Xingze Wu, Jingzhi Cui +4
Learning humanoid-object interaction requires coordinating whole-body balance, locomotion, and dexterous hand contact to control both robot and object motion. Human demonstrations…
Dex-X: Learning Visual-Tactile Dexterous Manipulation From Human Videos with Simulated Interaction
Ruoqu Chen, Feixiang Ruan, Liu Cao +9
Human videos are an abundant source of dexterous manipulation behaviors, but they lack tactile information that is crucial for contact-rich interaction. This raises a fundamental q…
R2S-Eval: Robot Evaluation with Real-to-Sim Calibration via Vision-Language Models
Yidi Wang, Feixiang Ruan, Ruoqu Chen +4
Evaluating robot manipulation policies is becoming increasingly important as generalist models, particularly vision-language-action (VLA) models, are deployed on physical robots. H…
UltraDP: Generalizable Carotid Ultrasound Scanning with Force-Aware Diffusion Policy
Ruoqu Chen, Xiangjie Yan, Kangchen Lv +3
Ultrasound scanning is a critical imaging technique for real-time, non-invasive diagnostics. However, variations in patient anatomy and complex human-in-the-loop interactions pose…