A review of intelligent optimization algorithm applied to unmanned aerial vehicle swarm search task

Collaborative search is one of the key application fields of UAV swarm, Efficient and accurate algorithm is very important to complete the task of UAV swarm search, and the dynamic and real-time uncertainty of unmanned aerial vehicle swarm search task makes the problem very difficult. Therefore, in the past few years, a large number of scholars have shown strong interest in the problem of UAV swarm search task. With the rapid development of computer technology and Intelligent optimization algorithm, many Intelligent optimization algorithm have been proposed to solve this problem. However, the research on cooperative control and search algorithm is still not comprehensive, and there is a lack of induction and summary of recent research results. The purpose of this paper is to introduce the mathematical model of the search task and give a comprehensive review of the intelligence algorithms used in the swarm search task in recent years and their improvement. In addition, the results and efficiency of each algorithm to solve UAV search tasks are compared, and the advantages and disadvantages of different swarm intelligence algorithms applied to UAV swarm search tasks are summarized and summarized, so as to provide useful reference for UAV swarm to complete search tasks in the future.