Joint Optimization of Path Planning and Task Assignment for Space Robot

Yifei Sun, Zikai Zhang, Yidong Li, Jigang Wu

Abstract: The space robot has been used widely in the aerospace industry. Because of the special working environment and limited fuel, an appropriate path is necessary for space robots to work. This paper investigates the path planning for multiple space robots to execute exploration tasks. To reduce the completion latency of exploration tasks, we model the joint problem of path planning and task assignment. Then we propose a combination algorithm named Branch addition path planning and Task Assignment (BTA). Finally, we implement a series of experiments to evaluate the performance of the proposed algorithms. Experimental results show that the proposed algorithm performs better than the Random path planning and Task Assignment algorithm (RTA) constructed also in this paper. Specifically, BTA performs better than RTA in terms of completion latency and BTA can save more fuel than RTA. Furthermore, the path planning algorithms forward search branch addition of BTA performs more stably than the random path planning of RTA in terms of running time.