CALOS: Control-Affine Lyapunov On-manifold Safety Layer for Safe Deep Reinforcement Learning for Quadrotors

A safety layer for deep reinforcement learning on quadrotors that enforces on-manifold Lyapunov stability, improving the reliability of learned control policies for aerial robots.

Auto-scored: A real but partial technical safety improvement for RL-controlled quadrotors, with no direct risk escalation.