Visuo-tactile feedback policies for terminal assembly facilitated by reinforcement learning

phase, a visuo-tactile policy is learned to precisely insert the terminal head into the terminal base. To ensure safe training, the robot leverages human demonstrations and interventions. Experimental results on PLC terminal assembly demonstrate that the proposed method achieves 100% successful insertions across 100 different initial end-effector and grasp poses, while imitation learning and online-RL policy yield only 9% and 0%.