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RoboTok: A Scalable Data Engine for Internet Demonstration Video Retrieval and Dexterous Manipulation Learning
Howard Qian, Yiting Chen, Yunfei Xie +6
Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and difficult to scale across the wide range of real-world task…
EgoInfinity: A Web-Scale 4D Hand-Object Interaction Data Engine for Any-View Robot Retargeting and Video-to-Action Robot Learning
Gaotian Wang, Kejia Ren, Andrew Morgan +4
Internet videos constitute the largest reservoir of embodied human manipulation knowledge, yet converting arbitrary RGB footage into actionable robot training data remains a major…
Zero-Shot Sim-to-Real Robot Learning: A Dexterous Manipulation Study on Reactive Catching
Kejia Ren, Gaotian Wang, Andrew S. Morgan +1
Dexterous manipulation is physics-intensive and highly sensitive to modeling errors and perception noise, making sim-to-real transfer prohibitively challenging. Domain randomizatio…
ManiDreams: An Open-Source Library for Robust Object Manipulation via Uncertainty-aware Task-specific Intuitive Physics
Gaotian Wang, Kejia Ren, Andrew S. Morgan +1
Dynamics models, whether simulators or learned world models, have long been central to robotic manipulation, but most focus on minimizing prediction error rather than confronting a…
MotionBits: Video Segmentation through Motion-Level Analysis of Rigid Bodies
Howard H. Qian, Kejia Ren, Yu Xiang +2
Rigid bodies constitute the smallest manipulable elements in the real world, and understanding how they physically interact is fundamental to embodied reasoning and robotic manipul…
V-VLAPS: Value-Guided Planning for Vision-Language-Action Models
Ke Ren, Ali Salamatian, Kieran Pattison +1
Vision-language-action (VLA) models provide strong action priors for robotic manipulation, but their reactive behavior can fail under distribution shift and long-horizon task struc…