Abstract
The task allocation of cooperative search involves many factors, which need to be coordinated when using unmanned aerial vehicle (UAV). Firstly, the coordinated search task model of multiple unmanned aerial vehicles was established, and the main factors include flight distance, flight time and mission timing constraints. Secondly, taking advantage of the strong global search ability and fast convergence speed of particle swarm optimization algorithm, the search task type matching information was used as heuristic information, and the idea of conflict resolution is used to improve the particle swarm optimization algorithm. Finally, the improved particle swarm optimization algorithm was applied to the task search instance for simulation research. The simulation results show that the improved particle swarm optimization algorithm with heuristic information of search task and task resolution strategy has higher search efficiency and faster convergence speed.
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