THE ESTIMATION OF CHANGING ENVIRONMENTAL CONDITIONS INFLUENCE ON THE WORKLOAD DISTRIBUTION IN THE UAV GROUP

Abstract

The paper considers the problem of workload distribution in a group of unmanned aerial vehicles
(UAVs) when monitoring a certain area in a changing environment, which has a direct impact on the
onboard energy resources consumption. The stage of a monitoring problem-solving, which includes the
distribution of UAVs over scanning bands, is described here. When this stage is carried, there is no
opportunity to take into account the factors of environmental impact. But these factors are crucial
due to the limited onboard energy resources. In this regard, a situation is very likely when the UAV is
not able to complete the sub-task assigned to it, which jeopardizes the completion of the entire mission
of the group. To avoid this situation, it is proposed to use the technique of a decision-making on
the need to relocate the workload in a group of mobile robots (MR). The decision-making is based on
the ontological analysis procedure, which allows limiting the number of choices for workload relocation.
The ontology model of the workload distribution in a group of UAVs was developed. This model
takes into account the possibility of additional performance involvement either by means of the resources
of neighboring UAVs, or by means of devices of the "foggy" layer. Examples of production
rules are given, on the basis of which a decision is made on the need to relocate the workload. A
comparative estimation of the resources volume involved in the implementation of two methods of
workload relocation problem solving, depending on the frequency of changes in environmental conditions,
is carried out. The results of computational experiments have shown that the method based on
ontological analysis is more efficient in comparison with the method based on LDG (Local Device
Group) in terms of the amount of resources involved. This makes it possible to increase the time of joint
mission implementation by the UAV group.