A multi- unmanned aerial vehicle dynamic task assignment method based on bionic algorithms

Abstract

Because of the long calculation time in task allocation algorithms and the long travelled distance of the Unmanned Aerial Vehicle (UAV) during task allocation, a multi-UAV task allocation method based on three bionic algorithms, which are the ant colony algorithm, bat algorithm, and gray wolf algorithm was proposed in this paper. The Multi-UAV Dynamic Task Assignment Method Based on Bionic Algorithms (TABA) method dynamically allocates UAVs based on the number of task points and includes a comparison mechanism. The results of experiments demonstrate that, among the three algorithms, the proposed method has 30% improvement to the conventional methods, and the UAV travel time is about one-third that of the original algorithm on average, thereby revealing the effectively reduced algorithm complexity. Moreover, the algorithm can reduce the travel time of UAVs.