Research on Multi-UAV Loading Multi-type Sensors Cooperative Reconnaissance Task Planning Based on Genetic Algorithm

Unmanned Aerial Vehicle (UAV) has been playing an increasingly important role in modern military fields recently. The multi-UAV cooperative reconnaissance mission planning is one of the task allocation and resource scheduling problems in the field of multi-UAV co-operative control, which is full of challenges. In this paper, a multi-base, multi-target, multi-load and multi-UAV cooperative task model is established. Taking the actual battlefield situation into account, this paper built a confrontation scenario between the UAVs and radars. The objective function of the established model is the shortest route length of UAVs staying in the detection range of radars. This paper presented an improved genetic algorithm to address the problem scenario. The solving procedure consists of two steps. First of all, the route of UAVs that traverse targets within target group is considered as a Traveling Salesman Problem (TSP). Second, the route of UAVs that fly between different target groups is regarded as a Multiple Depot Vehicle Routing Problem (MDVRP). In addition, the working patterns of different sensors carried by UAVs are concerned. As a consequence, a more optimized route of UAVs is acquired. Finally, A simulated case is designed to verify the feasibility of our proposed algorithm.