불확실한 환경에서의 조립 작업을 위한 온라인 모델링 방법

Abstract

Uncertainties are inevitable in robotic assembly in unstructured environment since it is difficult to construct fixtures to guide motions of robots. This paper proposes an augmented Petri net and an algorithm to adapt the assembly model on-line during actual assembly process. The augmented Petri net identifies events using force and position information simultaneously. Unmodeled contact states are identified and incorporated into the model on-line. The proposed method increases the level of intelligence of the robot system by enhancing the autonomy. The proposed method is evaluated by simulation and experiments with L-type peg-in-hole assembly using a two-arm robot system.