Cooperative path planning of multiple unmanned aerial vehicle(multi-UAV)is one of the key technologies of UAV cooperative engagement. A multi-objective optimization algorithm for cooperative path planning of multi-UAV, which is named as cooperated nondominated sorting genetic algorithms II(CO-NSGAII) is proposed for planning track distance, safety, spatial and time cooperativity of multi-UAV. By using the multi-objective optimization algorithm, the deficiency of taking weight for every objective function in the traditional path planning is overcame, and can get multiple alternative results. Meanwhile, by introducing the co-evolution strategy, the path planning of each UAV is treated as sub population, the best individual is used to cooperate between sub populations, and multiple objectives are optimized by non-dominated sorting genetic algorithms II(NSGA II) respectively in each sub population. Considering spatial and time constraints of UAV, the parameter of “crowding distance” in traditional algorithm is replaced by the parameter of spatial and time cooperativity. The simulation results show that the proposed algorithm can achieve cooperative path planning of multi-UAV effectively.
周德云, 王鹏飞, 李枭扬, 张堃. 基于多目标优化算法的多无人机协同航迹规划[J]. 系统工程与电子技术, 10.3969/j.issn.1001-506X.2017.04.13.
ZHOU Deyun, WANG Pengfei, LI Xiaoyang, ZHANG Kun. Cooperative path planning of multi-UAV based on multi-objective optimization algorithm[J]. Systems Engineering and Electronics, 2017, 39(4): 782-787.