POIL: Point-Based One-Shot Imitation Learning with Stable Dynamical Systems

POIL is a point-based one-shot imitation learning framework designed for robotic manipulation with stable dynamical systems. It transfers a demonstrated trajectory to a novel object while seeking robust execution under changing scene conditions, grasp configurations, and external disturbances. The method addresses both trajectory transfer and stable manipulation through a shared representation.