Abstract
Unmanned aerial vehicles (UAVs) are currently used in many civil and military tasks. In cases where the multiple tasks must be assigned to multiple UAVs, the task assignment of the relevant UAVs should be carried out in a way that the consumption of the flight time and flight distances to perform the tasks must be minimized. In this study, we propose an approach to efficiently perform the task assignment problem in cases where the number of targets and UAVs is large. The proposed method consists of a combination of three efficient processes: In the first stage, desired target locations are clustered by clustering algorithms according to the number of UAVs. Then, optimal drone-to-task set assignments are made by using the Hungarian algorithm. Finally, the optimal task route is planned for each subset using the ant colony algorithm to minimize the distance traveled by each UAV in the assigned task. The proposed method has been simulated under different scenarios and successful results have been obtained.
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