Combinatorial stabilization and reach-avoid filters enforce r-out-of-p contingency requirements using CLFs and Hamilton-Jacobi sets with only p+1 constraints.
Composing control barrier functions for complex safety specifications
3 Pith papers cite this work. Polarity classification is still indexing.
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A modular belief-space controller using learned Belief Control Lyapunov Functions for information gathering and conformal-prediction Belief Control Barrier Functions for safety reduces reach-avoid POMDP synthesis to fast quadratic programs.
A perception-driven composite CBF safety filter from 3D LIDAR data enables real-time collision avoidance for robots in dynamic constrained environments by using a body-frame ellipsoid safety region with per-point time-varying constraints.
citing papers explorer
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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.
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Safety-critical Control Under Partial Observability: Reach-Avoid POMDP meets Belief Space Control
A modular belief-space controller using learned Belief Control Lyapunov Functions for information gathering and conformal-prediction Belief Control Barrier Functions for safety reduces reach-avoid POMDP synthesis to fast quadratic programs.
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Reactive Robot-Centric Safety for Autonomous Navigation in Constrained and Dynamic Environments
A perception-driven composite CBF safety filter from 3D LIDAR data enables real-time collision avoidance for robots in dynamic constrained environments by using a body-frame ellipsoid safety region with per-point time-varying constraints.