A cooperative target search method based on intelligent water drops algorithm

被引:17
|
作者
Sun, Xixia [1 ]
Cai, Chao [2 ]
Pan, Su [1 ]
Zhang, Zhengning [3 ]
Li, Qiyu [3 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Internet Things, Key Lab Broadband Wireless Commun & Sensor Networ, Minist Educ, Nanjing, Jiangsu, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, State Key Lab Multispectral Informat Proc Technol, Wuhan, Hubei, Peoples R China
[3] Tianjin Zhong Wei Aerosp Data Syst Technol Co Ltd, Tianjin, Peoples R China
基金
中国国家自然科学基金;
关键词
Unmanned aerial vehicle (UAV); Cooperative search; Path planning; Intelligent water drops (IWD) algorithm; RESCUE;
D O I
10.1016/j.compeleceng.2019.106494
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This study investigates the problem of cooperative search path planning for multiple unmanned aerial vehicles. Firstly, we present a search probability map based environmental model, and formulate a multi-UAV cooperative search path optimization problem. Then, we propose a solution strategy based on an improved intelligent water drops (IWD) optimization algorithm. Compared with the traditional IWD algorithm, the proposed algorithm can simultaneously model the cooperation and competition among UAVs by introducing several heterogeneous water drop populations and a co-evolutionary mechanism. Water drops in the same population cooperate with each other, whereas water drops among different populations compete with each other to obtain the optimal path and reduce meaningless search effort. Meanwhile, the proposed algorithm can improve its search capability using a new soil update mechanism. Simulation results demonstrate the advantages of the proposed method over other baselines. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:14
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