2025
Integrating Model-Based Control and RL for Sim2Real Transfer of Tight Insertion Policies
Isidoros Marougkas, Dhruv Metha Ramesh, Joe Doerr, Edgar Granados, Aravind Sivaramakrishnan, Abdeslam Boularias +1
ICRA 2025
Object insertion under tight tolerances (<Imm) is an important but challenging assembly task as even small errors can result in undesirable contacts. Recent efforts focused on Reinforcement Learning (RL), which often depends on careful definition of dense reward functions. This work proposes an effe