Yinbei Li

A Hybrid Framework Using Diffusion Policy and Residual RL for Force-Sensitive Robotic Manipulation

Force-sensitive manipulation is essential for tasks such as cleaning, polishing, and surgical assistance, yet it remains challenging due to complex contact dynamics and the need for real-time adaptation. We propose DP-RRL, a hybrid learning framework that combines a diffusion policy (DP) for imitati