RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrations
Imitation learning in robotics faces significant challenges in generalization due to the complexity of robotic environments and the high cost of data collection. We introduce RoCoDA, a novel method that unifies the concepts of invariance, equivariance, and causality within a single framework to enha