Policy Library CBF: Finite-Horizon Safety at Runtime via Parallel Rollouts
For safety-critical autonomous systems in unstructured environments, PL-CBF provides a practical runtime safety certification method that handles evolving constraints with minimal computational overhead.
The paper proposes PL-CBF, a runtime safety filter that selects the least invasive safe mode from a library of fallback policies via parallel rollouts, and enforces safety via a quadratic program. Simulations on double-integrator, highway driving, and quadrotor navigation show improved safety coverage over single-policy filters with millisecond-level runtime.
Safety-critical autonomy in unstructured environments poses significant challenges for online safety certification under evolving constraints. We propose Policy Library Control Barrier Function~(PL-CBF), a runtime safety filter that evaluates a library of fallback policies via parallel finite-horizon rollouts, selects the least invasive safe mode, and enforces safety by solving a quadratic program that minimally modifies a nominal policy. We provide a theoretical analysis based on a finite-horizon language metric over closed-loop behaviors, characterizing policy-library coverage requirements for certifying finite-horizon safety. Simulations on a planar double-integrator (4 states), highway driving with abrupt friction changes using a realistic nonlinear vehicle model (8 states), and 3D quadrotor navigation in crowded dynamic environments (12 states) demonstrate improved safety coverage over single-policy safety filters while retaining millisecond-level runtime.