Article (Scientific journals)
A competitive Predator–Prey approach to enhance surveillance by UAV swarms
STOLFI ROSSO, Daniel; BRUST, Matthias R.; DANOY, Grégoire et al.
2021In Applied Soft Computing, 111, p. 107701
Peer reviewed
 

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Keywords :
Swarm robotics; Computer simulation; Mobility model; Unmanned aerial vehicle; Competitive coevolutionary genetic algorithm
Abstract :
[en] In this paper we present the competitive optimisation of a swarm of Unmanned Aerial Vehicles (UAV) protecting a restricted area from a number of intruders following a Predator–Prey approach. We propose a Competitive Coevolutionary Genetic Algorithm (CompCGA) which optimises the parameters of the UAVs (i.e. predators) to maximise the detection of intruders, while the parameters of the intruders (i.e. preys) are optimised to maximise their intrusion success rate. Having chosen the CACOC (Chaotic Ant Colony Optimisation for Coverage) as the base mobility model for the UAVs, we propose an improved new version, where its behaviour is modified by identifying and optimising new parameters to improve the overall success rate when detecting intruders. Six case studies have been optimised using simulations by performing 30 independent runs (180 in total) of our CompCGA. Finally, we conducted a series of master tournaments (1,800,000 evaluations) using the best specimens obtained from each run and case study to test the robustness of our proposed approach against unexpected intruders. Our surveillance system improved the average percentage of intruders detected with respect to CACOC by a maximum of 126%. More than 90% of intruders were detected on average when using a swarm of 16 UAVs while CACOC’s detection rates are always under 80% in all cases.
Disciplines :
Computer science
Author, co-author :
STOLFI ROSSO, Daniel  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG
BRUST, Matthias R. ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG
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 :
A competitive Predator–Prey approach to enhance surveillance by UAV swarms
Publication date :
2021
Journal title :
Applied Soft Computing
ISSN :
1568-4946
Volume :
111
Pages :
107701
Peer reviewed :
Peer reviewed
Name of the research project :
HUNTED
Funders :
ONRG
Available on ORBilu :
since 16 December 2021

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