Safe and Robust Neural Policy Learning with Statistical Verification for Sim-to-Real Deployment in Robotics

Synthesizing safe and robust neural controllers in simulation for reliable sim-to-real deployment remains a critical challenge in robotics. Existing learning-based methods typically lack safety and performance guarantees over an explicitly defined operating region, while post-training verification t