Optimal Subtask Allocation for Human and Robot Collaboration Within Hybrid Assembly System

Abstract

In human and robot collaborative hybrid assembly cell as we proposed, it is important to develop automatic subtask allocation strategy for human and robot in usage of their advantages. We introduce a folk-joint task model that describes the sequential and parallel features and logic restriction of human and robot collaboration appropriately. To preserve a cost-effectiveness level of task allocation, we develop a logic mathematic method to quantitatively describe this discrete-event system by considering the system tradeoff between the assembly time cost and payment cost. A genetic based revolutionary algorithm is developed for real-time and reliable subtask allocation to meet the required cost-effectiveness. This task allocation strategy is built for a human worker and collaborates with various robot co-workers to meet the small production situation in future. The performance of proposed algorithm is experimentally studied, and the cost-effectiveness is analyzed comparatively on an electronic assembly case.