1 citations · 1 across the 3 of their papers we have counts for
7 papers
When Automata Meet Streams: Temporal Logic Compilation for Stream-Based Robotics Task and Motion Planning
Sayem Nazmuz Zaman, Cyrus Neary
Stream-based robotics Task and Motion Planning (TAMP) integrates discrete symbolic planning with dynamically generated continuous geometric parameters, such as poses, grasps, and t…
Task Robustness via Re-Labelling Vision-Action Robot Data
Artur Kuramshin, Özgür Aslan, Cyrus Neary +1
The recent trend in scaling models for robot learning has resulted in impressive policies that can perform various manipulation tasks and generalize to novel scenarios. However, th…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
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…
ARM-FM: Automated Reward Machines via Foundation Models for Compositional Reinforcement Learning
Roger Creus Castanyer, Faisal Mohamed, Pablo Samuel Castro +2
Reinforcement learning (RL) algorithms are highly sensitive to reward function specification, which remains a central challenge limiting their broad applicability. We present ARM-F…
Improving Pre-Trained Vision-Language-Action Policies with Model-Based Search
Cyrus Neary, Omar G. Younis, Artur Kuramshin +2
Pre-trained vision-language-action (VLA) models offer a promising foundation for generalist robot policies, but often produce brittle behaviors or unsafe failures when deployed zer…