CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Liyiming Ke, Yunchu Zhang, Abhay Deshpande +2

We present a new technique to enhance the robustness of imitation learning methods by generating corrective data to account for compounding errors and disturbances. While existing…