14 papers
EgoVerse: An Egocentric Human Dataset for Robot Learning from Around the World
Ryan Punamiya, Simar Kareer, Zeyi Liu +37
Robot learning increasingly depends on large and diverse data, yet robot data collection remains expensive and difficult to scale. Egocentric human data offer a promising alternati…
EgoPhys: Learning Generalizable Physics Models of Deformable Objects from Egocentric Video
Hyunjin Kim, Ri-Zhao Qiu, Guangqi Jiang +1
Humans naturally understand object physics through everyday interactions, but faithfully predicting complex deformable dynamics, such as elastic materials and fabrics, remains a ma…
ConTrack: Constrained Hand Motion Tracking with Adaptive Trade-off Control
Yutong Liang, Quanquan Peng, Ri-Zhao Qiu +1
Human demonstrations provide strong priors for robot manipulation, yet it is non-trivial to transfer them to execute on real robots due to the kinematic gap. In dexterous manipulat…
Long-Horizon Manipulation via Trace-Conditioned VLA Planning
Isabella Liu, An-Chieh Cheng, Rui Yan +7
Long-horizon manipulation remains challenging for vision-language-action (VLA) policies: real tasks are multi-step, progress-dependent, and brittle to compounding execution errors.…
In-N-On: Scaling Egocentric Manipulation with in-the-wild and on-task Data
Xiongyi Cai, Ri-Zhao Qiu, Geng Chen +5
Egocentric videos are a valuable and scalable data source to learn manipulation policies. However, due to significant data heterogeneity, most existing approaches utilize human dat…
HMC: Learning Heterogeneous Meta-Control for Contact-Rich Loco-Manipulation
Lai Wei, Xuanbin Peng, Ri-Zhao Qiu +3
Learning from real-world robot demonstrations holds promise for interacting with complex real-world environments. However, the complexity and variability of interaction dynamics of…