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20232026
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12 papers · 1 filter

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2025

B4P: Simultaneous Grasp and Motion Planning for Object Placement via Parallelized Bidirectional Forests and Path Repair

Benjamin H. Leebron, Kejia Ren, Yiting Chen +1

Robot pick and place systems have traditionally decoupled grasp, placement, and motion planning to build sequential optimization pipelines with the assumption that the individual c…

cs.RO2024

Collision-Inclusive Manipulation Planning for Occluded Object Grasping via Compliant Robot Motions

Kejia Ren, Gaotian Wang, Andrew S. Morgan +1

Robotic manipulation research has investigated contact-rich problems and strategies that require robots to intentionally collide with their environment, to accomplish tasks that ca…