Distribution of tasks in a clustered field of goals for homogeneous and heterogeneous UAV groups

This work is devoted to the distribution of tasks in groups of unmanned aerial vehicles (UAVs) under conditions of a significant excess of the number of tasks over the number of agents. The main tasks solved by UAVs: survey and reconnaissance of territories, detection of dangerous objects or places of emergencies, search for victims, etc. The efficiency of solving the problems listed above achieved by the simultaneous use of a group of UAVs, the ele-ments (agents) of which can carry out the tasks of inspecting and scanning various areas of space in parallel. The article proposes an iterative method for distributing tasks in a group of UAVs with a significant excess of the num-ber of tasks over the number of agents (5-20 times). The proposed method for heterogeneous groups of UAVs based on a two-stage procedure for distributing agents of different specializations among task clusters, taking into account the agent's value function. At the first stage, the base part of the agents is distributed, the remaining agents at the second stage distributed in order to average the distance traveled by each agent. Execution of tasks within a cluster implemented by simulating annealing. To evaluate the effectiveness of the method variants, a comparison made with the greedy task distribution algorithm and the collective goal distribution algorithm. The analogs under consideration are widespread, universal and have a high convergence of the solution. Experimental studies car-ried out by computer simulation, where 2000 experiments carried out with various changes in the number of group agents and generation of a task map. The results showed the high efficiency of the task distribution method in terms of reducing the distance traveled by the agents of the UAV group when performing tasks in comparison with analogues. The efficiency of the path traveled by agents is up to 28% depending on the number of agents and tasks in the cluster, which is a scientific increment of the result of the study.