3 papers
cs.RO2026
Learning Robot Safety from Sparse Human Feedback using Conformal Prediction
Aaron O. Feldman, Joseph A. Vincent, Maximilian Adang +2
Ensuring robot safety can be challenging; user-defined constraints can miss edge cases, policies can become unsafe even when trained from safe data, and safety can be subjective. T…
cs.RO2026
Foundational World Models Accurately Detect Bimanual Manipulator Failures
Isaac R. Ward, Michelle Ho, Houjun Liu +7
Deploying visuomotor robots at scale is challenging due to the potential for anomalous failures to degrade performance, cause damage, or endanger human life. Bimanual manipulators…
cs.LG2025
Reachable Polyhedral Marching (RPM): An Exact Analysis Tool for Deep-Learned Control Systems
Joseph A. Vincent, Mac Schwager
Neural networks are increasingly used in robotics as policies, state transition models, state estimation models, or all of the above. With these components being learned from data,…