Fully automated robotic assembly cell: scheduling and simulation

Abstract

In this paper, we propose the scheduling methodology for a multirobot assembly cell, which is then integrated into a simulation environment. Since modeling a multirobot assembly system is difficult and tedious, a systematic method is proposed to transfer the AND/OR product assembly graph and the domain knowledge to assembly rules. Given this rule-base knowledge, an inference engine first generates all possible subsequent assembly tasks, and then a search algorithm finds the optimal ones. These promising tasks thus become the operation commands assigned to the assembly system. A simulation environment of a two-robot assembly cell is built and an experiment is performed using the proposed scheduling strategy. Satisfactory performance has been demonstrated.