Online Safety Verification and Control for Nonlinear Systems in Dynamic Environments
A computationally-lightweight algorithm called gatekeeper that ensures trajectories of a nonlinear system satisfy safety constraints despite sensing limitations and dynamic environments.
Safety-Critical Trajectory Planning and Control for Dynamic Obstacle Avoidance Using Discrete-Time Control Barrier Functions
This paper presents a novel framework that integrates iterative model predictive control with discrete-time control barrier functions to generate collision-free trajectories for a robot navigating through tight and dynamically changing environments with both convex and nonconvex obstacles.
Optimizing Robotic Behavior and Motion Through Tail Risk Measures
Tail risk measures, such as Value-at-Risk, Conditional Value-at-Risk, and Entropic Value-at-Risk, provide a systematic approach to quantifying and managing risk in robotic planning, control, and verification tasks. By focusing on rare but high-consequence events, these measures enable robots to balance performance and safety under uncertainty.
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