A liveness-based Bellman operator enables conservative offline policy evaluation for manipulation tasks by encoding task progression and reducing truncation bias from finite horizons.
Hamilton-Jacobi reachability: A brief overview and recent advances
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A post-hoc predictive safety filter adjusts RL policy contact locations for quadruped robots via sampling-based optimization on a full-physics model, reducing safety violations in cluttered environments with minimal performance deviation.
A conformal prediction certification for belief-space safety filters focuses verification on reliable inference regions to produce less conservative yet high-probability safe filters than standard baselines in human-vehicle simulations.
Non-Markovian policies from decomposed temporal logic value functions are proven optimal for nested Until, Globally, and Globally-Until specifications and extend Q-function safety filters to complex tasks.
Applies conformalized quantile regression with equalized coverage to predict motion control performance in automated vehicles under nominal, degraded, and failed actuator conditions.
citing papers explorer
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Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation
A liveness-based Bellman operator enables conservative offline policy evaluation for manipulation tasks by encoding task progression and reducing truncation bias from finite horizons.
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Shield-Loco: Shielding Locomotion Policies with Predictive Safety Filtering
A post-hoc predictive safety filter adjusts RL policy contact locations for quadruped robots via sampling-based optimization on a full-physics model, reducing safety violations in cluttered environments with minimal performance deviation.
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Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics
A conformal prediction certification for belief-space safety filters focuses verification on reliable inference regions to produce less conservative yet high-probability safe filters than standard baselines in human-vehicle simulations.
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Value Functions for Temporal Logic: Optimal Policies and Safety Filters
Non-Markovian policies from decomposed temporal logic value functions are proven optimal for nested Until, Globally, and Globally-Until specifications and extend Q-function safety filters to complex tasks.
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Equalized Coverage in Motion Control Performance Prediction for Self-Adaptive Road Vehicles
Applies conformalized quantile regression with equalized coverage to predict motion control performance in automated vehicles under nominal, degraded, and failed actuator conditions.