4 papers
IronMind: Scaling Humanoid Dexterous Manipulation via Camera-Space Ego-Centric Pretraining
Huimin Pan, Yufan Ren, Kunpeng Song +16
Egocentric human video offers a scalable data source for dexterous manipulation, yet using it to train humanoid robots presents two challenges: (1) an embodiment gap, as human hand…
XPACE: Joint World and Action Modeling from Heterogeneous Experience
Jiacheng Wei, Jerry Bai, Xiaoyu Yue +13
A general-purpose robot needs to draw on diverse experience, choose actions, and anticipate how those actions will change the world. We introduce XPACE, a unified embodied world mo…
AnyWorld: Factorized Egocentric World Models for Cross-Embodiment Generalization
Cheng Chen, Jerry Bai, Jiacheng Wei +11
Collecting contact-rich robot experiences at scale remains a major bottleneck for generalizable manipulation. Beyond data quantity, robot learning also requires diverse experiences…
UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling
Boyu Chen, Yi Chen, Lu Qiu +3
Scaling humanoid foundation models is bottlenecked by the scarcity of robotic data. While massive egocentric human data offers a scalable alternative, bridging the cross-embodiment…