A new robust Q-CBF framework synthesized via adversarial RL enables safety enforcement on the maximal robust safe set for black-box nonlinear systems.
Viscosity CBFs: Bridging the control barrier function and Hamilton-Jacobi reachability frameworks in safe control theory
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Combinatorial stabilization and reach-avoid filters enforce r-out-of-p contingency requirements using CLFs and Hamilton-Jacobi sets with only p+1 constraints.
citing papers explorer
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Synthesis and Deployment of Maximal Robust Control Barrier Functions through Adversarial Reinforcement Learning
A new robust Q-CBF framework synthesized via adversarial RL enables safety enforcement on the maximal robust safe set for black-box nonlinear systems.
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Steering with Contingencies: Combinatorial Stabilization and Reach-Avoid Filters
Combinatorial stabilization and reach-avoid filters enforce r-out-of-p contingency requirements using CLFs and Hamilton-Jacobi sets with only p+1 constraints.