Energy-controlled optimization algorithm for rechargeable unmanned aerial vehicle network

Abstract

Unmanned Aerial Vehicles (UAVs) are widely used in civil and military fields. For a working UAV, the energy is limited, the coverage distance is short and the loading capacity is restricted. In order to execute more tasks in complex environment, there is a trend that UAVs are used in cluster and coordinated with each other. Wireless charging technology can charge the unmanned aerial vehicles in time and effectively extend the life of UAVs to reduce the number of disabled UAVs. In this paper, the scheduling algorithm for charging UAVs cluster is studied. By comparing with other optimization algorithms, the most suitable charge scheduling control algorithm can be evaluated according to the number of surviving nodes in a certain time in the rechargeable unmanned aircraft group.