Research on multi-UAV cooperative target search method under unknown urban environment

被引：0
作者：
Liu D. [1 ]
Bao W. [1 ]
Fei B. [1 ]
Zhu X. [1 ]
机构：
[1] College of Systems Engineering, National University of Defense Technology, Changsha
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2023年 / 45卷 / 12期
关键词：
information sharing; multi-unmanned aerial vehicle (UAV) cooperation; regional coverage; target search; unknown urban environment;
D O I：
10.12305/j.issn.1001-506X.2023.12.19
中图分类号：
学科分类号：
摘要：
In the urban environment, the influence of factors such as buildings or inaccessible regions is easy to cause the failure of the multi-unmanned aerial vehicle (UAV) cooperative path planning strategy, which results in the failure of the target search task. To solve these issues above, a multi-UAV cooperative search (MUCS) method in the uncertain urban environment is proposed. Firstly, the urban environment is modeled, which includes the design of dense building clusters and targets with various motion states, so as to enhance the challenge of the target search task. Then on this basis, a cooperative optimization model based on information sharing cost and regional coverage benefit is constructed by comprehensively considering the flight constraint and the information interaction capability of UAV formation. Finally, according to the characteristics of the multi-UAV cooperative formation, the swarm intelligence method is used to solve the optimization problem? which ensures that each UAV can obtain the feasible solution of the optimal path and improve the efficiency of the multi-UAV cooperative target search. Compared with the existing search methods, the average target discovery success rate of MUCS method is increased by 20%, and the regional coverage rate is increased by 10%. The experimental results illustrate that MUCS has the strong capability of the target search and regional coverage. © 2023 Chinese Institute of Electronics. All rights reserved.
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收藏
页码：3896 / 3907
页数：11
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