The UAV Swarm Mission Planning Based on Adaptive Genetic Algorithm

With the rapid development of Unmanned Aerial Vehicle(UAV) technology, the application fields of the UAV are becoming more and more wide. Especially in the field of military operations, as a new type of weapon with high cost performance, the application prospect of the UAV in modern war will be very broad. However, due to the complexity of the battlefield environment and the diversity of mission forms, the mission capability that a single UAV can perform is limited and its survivability is also challenged. The mission mode of the UAV has gradually developed from single platform mission execution to swarm collaborative mission execution. As one of the key technologies for multiple UAVs cooperative operations, mission planning technology has received extensive attention. This paper conducts research on the field of UAV swarm mission planning. Firstly, the multi-objective optimization model is established with the goal of the shortest path and the least airborne time for the UAV swarm to complete the mission. Secondly, the above model is optimized with constructing an adaptive genetic algorithm by improving the genetic operator and the crossover operator. Finally, the corresponding algorithm is simulated and analyzed through a specific example.