Metaheuristic Planner for a Swarm of UAVs

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0198433" target="_blank" >RIV/00216305:26220/26:0198433 - isvavai.cz</a>
Result on the web
<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2025_sbornik_1.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2025_sbornik_1.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Metaheuristic Planner for a Swarm of UAVs
Original language description
Unmanned Aerial Vehicles (UAVs) have become an important component in various applications, such as filmmaking or area surveillance. Many modern applications employ autonomous flight of UAV swarms, which offer advantages but also pose constraints. This paper is focused on research and testing of different metaheuristic algorithms used for swarm path planning. Specifically, this study compares the performance of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Tabu Search (TS) and Gravitational Search (GS) in solving UAV path planning problem. The proposed path planner aims to generate near optimal trajectories for area coverage while avoiding collisions within the swarm.
Czech name
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Czech description
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Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings I of the 31st Conference STUDENT EEICT 2025
ISBN
978-80-214-6321-9
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
201-204
Publisher name
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Place of publication
Brno
Event location
Brno
Event date
Apr 29, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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