Cooperative area search algorithm for UAV swarm in unknown environment

被引：0
|
作者：
Hou Y. [1 ,2 ]
Liang X. [1 ,2 ]
He L. [1 ,2 ]
Liu L. [1 ,2 ]
机构：
[1] National Key Laboratory of Air Traffic Collision Prevention, Air Force Engineering University, Xi'an
[2] Shaanxi Province Lab. of Meta-synthesis for Electronic & Information System, Air Force Engineering University, Xi'an
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2019年 / 45卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Cooperative search; Coverage rate; Distributed model predictive control; Hadamard product; UAV swarm; Unknown environment;
D O I：
10.13700/j.bh.1001-5965.2018.0230
中图分类号：
学科分类号：
摘要：
Aimed at the problem of cooperative search for UAV swarm in an unknown environment without prior information, a cooperative area search algorithm for UAV swarm with coverage rate as real-time search rewards is proposed. First, coverage distribution map (CDM) is established to describe the mission area, and the rapid update of CDM is realized by using Hadamard product. Then, the coverage rate is calculated based on CDM to describe the search results quantitatively. Considering UAV swarm as a control system, a predictive model of the system is established based on the distributed model predictive control theory, and the maximum increment of coverage rate in the predictive period is determined as a reward function. The optimal solution, as the optimal input of system, is obtained by differential evolution algorithm. Simulation results demonstrate that the proposed algorithm can complete the coverage and search of region effectively. In the event of emergencies, its area coverage rate is much higher than that of the parallel search method. © 2019, Editorial Board of JBUAA. All right reserved.
引用
收藏
页码：347 / 356
页数：9
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