Multi-UAV Collaborative Reconnaissance Based on Adaptive Particle Swarm Optimization

In recent years, there has been significant progress in Unmanned Aerial Vehicle (UAV) technology. UAVs have undergone significant advancements, becoming increasingly mature with improved maneuverability, ease of operation, and cost-effectiveness. As a result, UAVs have emerged as a vital tool in various domains, including intelligence reconnaissance and target search. In contrast to single UAV systems, the utilization of UAV formations or clusters has gained prominence as an innovative organizational approach, offering significant advantages such as expanded reconnaissance range and enhanced operational effectiveness. This paper initiates by establishing a comprehensive problem model for multi-UAV cooperative reconnaissance. Subsequently, we propose novel techniques, including the historical path probability decrease mechanism and the rolling optimization strategy. Additionally, we introduce an adaptive particle swarm optimization algorithm to effectively plan the search paths of UAVs. Finally, we conduct simulation experiments to evaluate the effectiveness of the proposed method.