Shifted Flow Policy: Uncertainty-Aware Time Reparameterization for Visuomotor Learning
Imitation learning for robotics often uses action chunking to mitigate the compounding errors associated with autoregressive policies. By predicting multiple future actions simultaneously, action chunking limits the accumulation of errors but introduces new difficulties. In particular, it relies on …