Development of an Intelligent Control Algorithm for a Group of Unmanned Aerial Vehicles

At the current moment, the development of scientific and technological progress is being update. In particular, the development and widespread use of unmanned aerial vehicles is particularly relevant. These technological innovations are capable of solving a whole range of tasks in completely different areas of human life, both domestic and professional. One of the subtasks of applying these solutions is the use of groups of unmanned aerial vehicles. However, a problem arises related to their control in space, which requires the development of new algorithms and approaches to its solution. The main purpose of the presented article is to perform an analysis regarding the issue of controlling a group of unmanned aerial vehicles. The paper presents the results of the development of the author's interpretation of an algorithm designed to control a group of unmanned vehicles. The algorithm of the bee colony taken as a basis. A special feature of the proposed algorithm is the modification due to the integration of artificial intelligence elements. It assumed that the use of the proposed approaches in practice would significantly increase the efficiency and ensure the autonomy of the tasks performed by a group of unmanned aerial vehicles. The main advantage of the developed intelligent algorithm is the capture of the maximum possible survey area with the available number of unmanned aerial vehicles in the group.

Authors

Institutions

Publication Details

Journal
Computational nanotechnology
Published
2024-09-23
DOI
https://doi.org/10.33693/2313-223x-2024-11-2-86-92
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of an Intelligent Control Algorithm for a Group of Unmanned Aerial Vehicles

O. Yu. Timoshevskaya, Vladimir Londikov, S.YU. LUKANOV
Computational nanotechnology
Industrial Technology and Control Systems
article

Development of an Intelligent Control Algorithm for a Group of Unmanned Aerial Vehicles

O. Yu. Timoshevskaya, Vladimir Londikov, S.YU. LUKANOV
article en

Abstract

At the current moment, the development of scientific and technological progress is being update. In particular, the development and widespread use of unmanned aerial vehicles is particularly relevant. These technological innovations are capable of solving a whole range of tasks in completely different areas of human life, both domestic and professional. One of the subtasks of applying these solutions is the use of groups of unmanned aerial vehicles. However, a problem arises related to their control in space, which requires the development of new algorithms and approaches to its solution. The main purpose of the presented article is to perform an analysis regarding the issue of controlling a group of unmanned aerial vehicles. The paper presents the results of the development of the author's interpretation of an algorithm designed to control a group of unmanned vehicles. The algorithm of the bee colony taken as a basis. A special feature of the proposed algorithm is the modification due to the integration of artificial intelligence elements. It assumed that the use of the proposed approaches in practice would significantly increase the efficiency and ensure the autonomy of the tasks performed by a group of unmanned aerial vehicles. The main advantage of the developed intelligent algorithm is the capture of the maximum possible survey area with the available number of unmanned aerial vehicles in the group.

Computational nanotechnologyVol. 11(2)
Pskov State University (RU)
Openalex Percentile: Top 82%
Industrial Technology and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.