Task Allocation Method of UAV Clusters Based on Sequence Generative Adversarial Network

被引：0
作者：
Yan Y. [1 ]
Bi W. [1 ]
Zhang A. [1 ]
Zhang B. [1 ]
机构：
[1] School of Aeronautics, Northwestern Polytechnical University, Shaanxi, Xi'an
来源：
Binggong Xuebao/Acta Armamentarii | 2023年 / 44卷 / 09期
关键词：
generative adversarial network; policy gradient; sequence generation model; task allocation; UAV cluster;
D O I：
10.12382/bgxb.2022.0931
中图分类号：
学科分类号：
摘要：
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. © 2023 China Ordnance Society. All rights reserved.
引用
收藏
页码：2672 / 2684
页数：12
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