Labour division algorithm for a group of unmanned aerial vehicles in a clustered target field

Abstract

In this paper we propose an algorithm for tasks distribution (division of labour) for a group of unmanned aerial vehicles (UAVs) when monitoring an emergency zone. The input data of the algorithm are information on the homogeneous group of UAVs, the coordinates of the home point, and a set of elementary subtasks coming from the command center. The presented algorithm is analytical and allows obtaining the correct distribution result for any consistent input data. The algorithm is based on the principle of preliminary combining elementary tasks into clusters on a territorial basis. The results of simulation showed that the proposed labour distribution algorithm allows to achieve an average of 4.7% - 12.8% less time to complete a global task in comparison with the greedy algorithm. We experimentally established that the best result is achieved when choosing a cluster size so that about 75% of tasks are included in clusters, and 25% of tasks remain free