Base position and task assignment optimization concerning productivity and machining performance for multi-robot systems in aerospace manufacturing

Flexible and efficient multi-robot systems are being increasingly used in the field of aerospace manufacturing. The task planning considers solely the objective of productivity has been well studied in previous works, however, when dealing with high-quality machining of complex products, combining the objective of productivity and machining performance in planning is an issue that requires further discussion. This paper proposes a twoobjective optimization technique for the MRS that undertakes the machining mission of large spacecraft components, where the robot base positions and task assignment are taken as optimization variables, and a multiobjective algorithm based on NSGA-II is introduced, efficient execution of the algorithm is guaranteed by specially designed crossover and correction operators. A test case of spacecraft structure machining mission shows that the algorithms find both productivity-optimal and machining performance-optimal solutions, and an appropriate trade-off between productivity and machining performance should be more desirable in real-world applications.

Automated summary

This paper proposes a two-objective optimization technique for multi-robot systems, addressing the issue of balancing productivity and machining performance in high-quality machining tasks.