DOI:https://doi.org/10.15407/kvt211.01.064
Cybernetics and Computer Engineering, 2023, 1(211)
Chepizhenko V.I.1, DSc (Engineering), Senior Research,
Leading Researcher of the Intellectual Control Department.
https://orcid.org/0000-0001-8797-4868,
e-mail: chepizhenko.valeriy@gmail.com
Pavlova S.V.2, DSc (Engineering), Professor,
Professor of School of Software
https://orcid.org/0000-0002-6256-5248 ,
e-mail: pavlova_2020@ukr.net
Skyrda I.I.3, PhD (Engineering),
Aviation Communication, Navigation and Surveillance expert (CNS expert)
https://orcid.org/0000-0002-9363-8921 ,
e-mail: skyrda2@gmail.com
1International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine.
40, Akad. Glushkov ave., Kyiv, 03187, Ukraine.
2Shanxi Agricultural University
81, Longcheng str., Xiaodian Taiyuan, Shanxi, 030031, China.
3EUROCONTROL
Rue de la Fusée, 96, Brussels, 1130, Belgium
TRAJECTORY MOVEMENT CONTROL OF UNMANNED AERIAL VEHICLES IN A SWARM
Introduction. Today, the use of swarms of unmanned aerial vehicles (UAVs) is effective for solving the tasks of monitoring large areas of the earth’s surface and infrastructure objects, processing large areas of agricultural land, digital mapping, designing land objects in 3D, planning and designing construction works, road surface monitoring, etc. An important issue here is the potential for simultaneous conflicts between unmanned aerial vehicles moving in a swarm.
The purpose of the work is to develop a scalable, flexible method of controlling the trajectory of unmanned aerial vehicles in a swarm based on the approach of artificial potential fields.
The results. The developed method has properties of scalability and flexibility. The method contains a simple control algorithm, that allows several UAVs to fly as part of a swarm along a given trajectory, while solving the task of resolving conflict situations (preventing collisions between swarm members and with static and dynamic obstacles). The proposed method consists in decentralized real-time management of the swarm. The simulation results show that the method, presented in the article, increases the efficiency of swarm formation and flight performance, as well as UAV collision avoidance.
Conclusions. The proposed method scales well and is suitable for controlling a swarm of different sizes, it can also be applied to control a swarm of UAVs with different flight characteristics, since the formation of the resulting motion vector does not depend on the specific technical characteristics of the UAV, but takes into account certain limitations.
Keywords: unmanned aerial vehicle, modified artificial potential fields, UAV swarm, collision avoidance.
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Received 12.01.2023