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 at-tributes 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 in-telligence optimization algorithm that tends to Then,to address the shortcomings of the traditional swarm intelligence optimiza-tion algorithm,which is prone to fall into the local optimum,we design a hybrid differential evolutionary particle swarm algo-rithm 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 experi-ments,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 in-telligence optimization algorithm.
维普
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