基于序列生成对抗网络的无人机集群任务分配方法

In response to the problem that the existing UAV cluster task allocation algorithm decreases the solution efficiency and increases the solution time significantly when performing larger scale task allocations, a task allocation method based on sequence generative adversarial network is proposed. A sequence generation model containing a battlefield information feature extraction network and a sequence generation network are constructed to solve the problem of generating a sequence from battlefield information to task allocation. A discriminative model based on a multicore-multilayer convolutional network is constructed, and a gain-evaluation dual-guided policy gradient update is proposed for model training, which solves the problem of discrete task allocation sequences and ensures the quality of task allocation sequences. Simulation results show that the proposed method can efficiently generate task allocation sequences corresponding to battlefield information while guaranteeing the quality.