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 systemby 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.