Cooperative path planning of multi-UAV based on multi-objective optimization algorithm

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 non-dominated sorting genetic algorithms-II(CO-NSGA-II) 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.