[en] This article explores the application of evolutionary algorithms and agent-oriented programming to solve the problem of searching and monitoring objectives through a fleet of unmanned aerial vehicles. The subproblem of static off-line planning is studied to find initial flight plans for each vehicle in the fleet, using evolutionary algorithms to achieve compromise values between the size of the explored area, the proximity of the vehicles, and the monitoring of points of interest defined in the area. The results obtained in the experimental analysis on representative instances of the surveillance problem indicate that the proposed techniques are capable of computing effective flight plans.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
Gaudín, Américo
Madruga, Gabriel
Rodríguez, Carlos
Iturriaga, Santiago
Nesmachnow, Sergio
Paz, Claudio
DANOY, Grégoire ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
BOUVRY, Pascal ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Crespo-Mariño, Juan Luis
Meneses-Rojas, Esteban
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Autonomous Flight of Unmanned Aerial Vehicles Using Evolutionary Algorithms
Date de publication/diffusion :
2020
Nom de la manifestation :
Latin American High Performance Computing Conference (CARLA 2019)
Date de la manifestation :
from 25-09-2019 to 27-09-2019
Manifestation à portée :
International
Titre de l'ouvrage principal :
High Performance Computing
Maison d'édition :
Springer International Publishing, Cham, Inconnu/non spécifié
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