Simultaneous Optimization of Mechanism and Control in Cooperative Work of Multiple Robot Arms

Abstract

　This paper present a simultaneous optimization of the mechanism and control when two six degree of freedom robot arms in the cooperate button pushing task by combining reinforcement learning and genetic algorithm. The proposed optimization system uses a genetic algorithm to optimize the mechanism and reinforcement learning to optimize the control. The length of each link is changed to the length represented by the gene, and the target is to press six buttons in cooperation with two robot arms. The results are evaluated and optimization is performed by repeating crossovers and generational changes. As a result, it was confirmed that not only the control is optimized, but also the mechanism is optimized to achieve efficient and coordinated task achievement.