System and method suitable for tuning a pre-trained diffusion policy of a robot

Abstract

The present disclosure provides a system and a method for controlling an operation of a robot to execute a task. The method includes collecting a set of trajectories by executing a pre-trained diffusion policy of the robot and receiving a feedback label corresponding to each pair of trajectories of the set of trajectories, wherein the feedback label corresponding to each pair of trajectories indicates a preference to at least one trajectory of the corresponding pair of trajectories. The method further includes learning a reward function based on each pair of trajectories and its corresponding feedback label, and tuning the pre-trained diffusion policy based on the reward function, via reinforcement learning. The method further includes controlling, based on the tuned pre-trained diffusion policy, the operation of the robot to execute the task.

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