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.
Highlights
Modern emergency zones monitoring systems aim to counteract a negative tendency of changing the state of the environment, expressed in the activation of unfavourable, dangerous natural phenomena and processes and, in an increase in the frequency and scale of natural disasters, the development of natural disasters into man-made and vice versa [1,2]
It is worth noting that the listed monitoring tools are difficult to use, for example, for taking samples of the atmosphere or searching for people with a simultaneous monitoring of the emergency zone, which can be performed in parallel by unmanned aircraft
According to the results of the experiment (Table 1), the smallest average execution time for a global task is achieved with such a choice of the cluster size so that about 25% of tasks remain unallocated
Summary
Modern emergency zones monitoring systems aim to counteract a negative tendency of changing the state of the environment, expressed in the activation of unfavourable, dangerous natural phenomena and processes and, in an increase in the frequency and scale of natural disasters, the development of natural disasters into man-made and vice versa [1,2]. The growth of technological progress in the field of robotic, satellite and unmanned aircraft systems makes it possible to monitor the development of emergencies to assess the state of the environment, man-made objects, analyze the processes and phenomena occurring in them for the timely identification of trends in their change in order to ensure the prevention and elimination of natural and man-made emergencies [3,4,5]. Due to the low resolution, satellite monitoring can leave unnoticed small emergency zones, which potentially pose a great danger, and updating information several times a day does not ensure high efficiency in eliminating the consequences of an emergency. In light of the above circumstances, the most promising direction for solving the problems of automating the monitoring of emergency zones is the use of UAV groups
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