Rewind-IL: Online Failure Detection and State Respawning for Imitation Learning
Rewind-IL is a training-free framework for generative imitation learning that detects failures in real-time and recovers automatically. It uses a metric called TIDE to spot internal policy inconsistencies and then respawns the robot at a previously verified safe state identified by a Vision-Language Model.