31 citations · 45 across the 35 of their papers we have counts for
10 papers · 2 filters
Expert-Play Contouring Control: Faster-than-Demonstration Planning from Slow Expert and Fast Play
Seunghoon Cho, Wonsuhk Jung, Sundhar Vinodh Sangeetha +1
Expert demonstrations often specify what a robot should do, but not how fast it can do it. Imitation Learning (IL) inherits demonstration timing, while directly accelerating the le…
Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation
Woo Chul Shin, Zhenyang Chen, Alfred Cueva +5
Visuomotor policies have advanced on manipulation tasks where the target object stays static during execution, but real deployments break this assumption: parts drift on conveyors…
Exact, Efficient, and Safe Occlusion-Aware Planning Using AH-Polyhedrons
Long Kiu Chung, David Isele, Toktam Mohammadnejad +4
Safely handling occlusions is a fundamental challenge for autonomous mobile robots operating in dynamic environments. This issue is especially prominent in autonomous valet parking…
WARP: Whole-Body Retargeting for Learning from Offline Human Demonstrations
Zhenyang Chen, Chuizheng Kong, Chuye Zhang +4
Direct transfer from human demonstration to learnable robot action is a crucial step towards scalable whole-body mobile manipulation. While human data scales better than mobile tel…
Make Your VLA More Robust Without More Data By Interleaving Motion Planning
Dan BW Choe, Sundhar Vinodh Sangeetha, Samuel Coogan +1
Vision-Language-Action (VLA) models have shown remarkable progress for mobile manipulation, but their performance on long-horizon tasks remains poor. These tasks are especially cha…
RTD-RAX: Fast, Safe Trajectory Planning for Systems under Unknown Disturbances
Evanns Morales-Cuadrado, Long Kiu Chung, Shreyas Kousik +1
Reachability-based Trajectory Design (RTD) is a provably safe, real-time trajectory planning framework that combines offline reachable-set computation with online trajectory optimi…