5 citations · 11 across the 11 of their papers we have counts for
3 papers · 1 filter
COWBOY: A Scalable Sim-to-Real Framework for Learning Contextual Whole-Body Manipulation
Jiahui Yang, Jason Jingzhou Liu, Ray Muxin Liu +4
Mobile manipulators must adapt not only to objects, but also to the spatial context in which they appear: where to position the base, how to manipulate, and where to look while nav…
Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video
Yunhai Han, Jianuo Qiu, Linhao Bai +14
Human manipulation videos are a convenient and intuitive source for robot learning. However, directly transferring human dexterity to robots remains challenging due to perception e…
FACTR 2: Learning External Force Sensing for Commodity Robot Arms Improves Policy Learning
Steven Oh, Jason Jingzhou Liu, Tony Tao +5
Contact-rich manipulation requires force sensitivity, but many robot arms lack dedicated force sensors due to their high cost. We present Neural External Torque Estimation (NEXT),…