Self-Organizing Neural Network based Mission Planning for Space Unmanned System

In this paper, the task planning problem of multi-mission location information collection for space unmanned system with long-range detection sensors is considered and modeled as a NP hard combinatorial optimization problem. An algorithm for solving planning problems based on self-organizing neural network is proposed to construct a zero-distance information collection path. On this basis, the effective detection areas of space unmanned system at each mission point are sampled. Four search operators are designed and the appropriate detection points are searched by local search algorithm. In addition, the mission scenario is constructed by random initial multi-mission sites. The simulation and analysis of the algorithm verify the validity of the proposed algorithm for the problem of space unmanned system information collection mission planning.