Task planning of space-robot clusters based on modified differential evolution algorithm

Abstract

This study studies the problem of on-orbit maintenance task planning for space-robot clusters. Aiming at the problem of low maintenance efficiency of space-robot cluster task-planning, this study proposes a cluster-task-planning method based on energy and path optimization. First, by introducing the penalty-function method, the task planning problem of the space-robot cluster under limited energy is analyzed, and the optimal-path model for task planning with comprehensive optimization of revenue and energy consumption are constructed; then, the maintenance task points are clustered to reduce the scale of the problem, thus reducing the difficulty of solving the problem; finally, a modified differential evolution algorithm is proposed to solve the problem of space-robot cluster task-planning, improve the performance of space-robot cluster task-assignment and path planning. Simulation results show that the proposed optimal-path model of space-robot cluster and the modified differential evolution algorithm can effectively solve the task-planning problem of spatial robot clusters.