Article (Scientific journals)
SuSy-EnGaD: Surveillance System Enhanced by Games of Drones
STOLFI ROSSO, Daniel; BRUST, Mathias; DANOY, Grégoire et al.
2022In Drones, 6 (13)
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Keywords :
swarm robotics; unmanned aerial vehicles; evolutionary game theory; evolutionary algorithm; surveillance system; multi-objective optimisation
Abstract :
[en] In this article, we propose SuSy-EnGaD, a surveillance system enhanced by games of drones. We propose three different approaches to optimise a swarm of UAVs for improving intruder detection, two of them featuring a multi-objective optimisation approach, while the third approach relates to the evolutionary game theory where three different strategies based on games are proposed. We test our system on four different case studies, analyse the results presented as Pareto fronts in terms of flying time and area coverage, and compare them with the single-objective optimisation results from games. Finally, an analysis of the UAVs trajectories is performed to help understand the results achieved.
Disciplines :
Computer science
Author, co-author :
STOLFI ROSSO, Daniel  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG
BRUST, Mathias ;  University of Luxembourg
DANOY, Grégoire  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
BOUVRY, Pascal ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
External co-authors :
no
Language :
English
Title :
SuSy-EnGaD: Surveillance System Enhanced by Games of Drones
Publication date :
2022
Journal title :
Drones
eISSN :
2504-446X
Publisher :
MDPI AG, Switzerland
Special issue title :
Featured Papers of Drones
Volume :
6
Issue :
13
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
ONRG
Available on ORBilu :
since 07 March 2022

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