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Multi-UAV Collaborative Area Search Strategy Based on Differential Evolutionary Particle Swarm Mixing Algorithm
Received date: 2023-06-14
Online published: 2024-12-28
To improve the area search efficiency of UAV swarms in unknown environments, a multi-UAV cooperative area search strategy is proposed. Firstly, according to the demand of area search task, an area information map containing three attributes of area coverage, area uncertainty and target existence probability is established; secondly, with the goal of maximizing search efficiency and minimizing energy consumption during UAV search, a rolling time-domain optimization objective function for UAV area search is established to guide UAVs to make online decisions on search routes; then, for the traditional swarm intelligence optimization algorithm that tends to Then, to address the shortcomings of the traditional swarm intelligence optimization algorithm, which is prone to fall into the local optimum, we design a hybrid differential evolutionary particle swarm algorithm to solve the multi-objective optimization problem online, improve the optimization performance of the algorithm, and thus improve the search efficiency of the UAV. Finally, the proposed algorithm is verified through numerical simulation experiments, and the simulation results show that the multi-UAV cooperative area search strategy based on differential evolutionary particle swarm hybrid algorithm designed in this paper has higher area search efficiency compared with the traditional swarm intelligence optimization algorithm.
LAI Xingjun , TANG Xin , LIN Lei , WANG Zhisheng , CONG Yuhua . Multi-UAV Collaborative Area Search Strategy Based on Differential Evolutionary Particle Swarm Mixing Algorithm[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2024 , 44(1) : 89 -97 . DOI: 10.15892/j.cnki.djzdxb.2024.01.014
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