7 papers
RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models
Jacky Kwok, Christopher Agia, Rohan Sinha +5
Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in visuomotor control, yet ensuring their robustness in unstructured real-world environments remains a…
CUPID: Curating Data your Robot Loves with Influence Functions
Christopher Agia, Rohan Sinha, Jingyun Yang +5
In robot imitation learning, policy performance is tightly coupled with the quality and composition of the demonstration data. Yet, developing a precise understanding of how indivi…
Scan, Materialize, Simulate: A Generalizable Framework for Physically Grounded Robot Planning
Amine Elhafsi, Daniel Morton, Marco Pavone
Autonomous robots must reason about the physical consequences of their actions to operate effectively in unstructured, real-world environments. We present Scan, Materialize, Simula…
Deformable Cargo Transport in Microgravity with Astrobee
Daniel Morton, Rika Antonova, Brian Coltin +2
We present pyastrobee: a simulation environment and control stack for Astrobee in Python, with an emphasis on cargo manipulation and transport tasks. We also demonstrate preliminar…
Real-Time Out-of-Distribution Failure Prevention via Multi-Modal Reasoning
Milan Ganai, Rohan Sinha, Christopher Agia +3
While foundation models offer promise toward improving robot safety in out-of-distribution (OOD) scenarios, how to effectively harness their generalist knowledge for real-time, dyn…
Deep Learning Warm Starts for Trajectory Optimization on the International Space Station
Somrita Banerjee, Abhishek Cauligi, Marco Pavone
Trajectory optimization is a cornerstone of modern robot autonomy, enabling systems to compute trajectories and controls in real-time while respecting safety and physical constrain…