Error Recovery System for Robotic Snap Assembly Task

Abstract

In this research, we propose an error recovery system in robotic snap assembly task by learning the result of past assembly tasks. During a snap assembly task, the proposed system can judge the type of error and what adequate motion should be performed for error recovery. In this paper, firstly, we obtain the feature quantities of force and torque data measured during simulated snap assembly tasks. Then, we cluster these data into success and several different failure cases. Furthermore, we try to predict an error in realtime in the middle of a snap assembly task. Finally, we show simulation results of error detection.