C-search: A Swarm Cooperative Area Search System for UAVs

Abstract

The UAV swarm has been applied widely in various fields, which requires it to have more powerful capabilities. Area search is an important application of a UAV swarm, and large amounts of researches have been conducted to optimize the swarm's behavior. However, there are still some challenges of area search. The execution of search tasks usually depends on global cognition, which is difficult to obtain in reality. In addition, the search efficiency of the swarm is low and the ability to adapt to the environment is poor. In response to these challenges, a swarm cooperative area search system is proposed. The system consists of two modules: a global planning module and an autonomous flight module. In the global planning module, when the UAV swarm can obtain GPS information, the optimal area search routes of the UAVs are planned in advance to realize accurate area search. The autonomous flight module enables the UAVs to independently generate and optimize the control structure independent of GPS information. C-search improves the ability of UAV swarms to execute area search tasks, and increases the adaptability to a variety of task scenarios and robustness to harsh task environments. The effectiveness of the system is verified by experiments. The results show that the UAV swarm can complete the area search task in a variety of task scenarios.