5 citations · 7 across the 4 of their papers we have counts for
4 papers
Input-to-State Stability in Probability
Preston Culbertson, Ryan K. Cosner, Maegan Tucker +1
Input-to-State Stability (ISS) is fundamental in mathematically quantifying how stability degrades in the presence of bounded disturbances. If a system is ISS, its trajectories wil…
Learning Responsibility Allocations for Safe Human-Robot Interaction with Applications to Autonomous Driving
Ryan K. Cosner, Yuxiao Chen, Karen Leung +1
Drivers have a responsibility to exercise reasonable care to avoid collision with other road users. This assumed responsibility allows interacting agents to maintain safety without…
Robust Safety under Stochastic Uncertainty with Discrete-Time Control Barrier Functions
Ryan K. Cosner, Preston Culbertson, Andrew J. Taylor +1
Robots deployed in unstructured, real-world environments operate under considerable uncertainty due to imperfect state estimates, model error, and disturbances. Given this real-wor…
Safety-Aware Preference-Based Learning for Safety-Critical Control
Ryan K. Cosner, Maegan Tucker, Andrew J. Taylor +7
Bringing dynamic robots into the wild requires a tenuous balance between performance and safety. Yet controllers designed to provide robust safety guarantees often result in conser…