Reference : Chaos-enhanced mobility models for multilevel swarms of UAVs
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Mathematics
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/34390
Chaos-enhanced mobility models for multilevel swarms of UAVs
English
Rosalie, Martin mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Danoy, Grégoire mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Chaumette, Serge mailto [Université Bordeaux 1 > LaBRI]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2018
Swarm and Evolutionary Computation
Elsevier
Yes
International
2210-6502
[en] ACO ; Swarms of UAVs ; Mobility model ; Chaotic dynamics ; Global optimization ; First return ma
[en] The number of civilian and military applications using Unmanned Aerial Vehicles (UAVs) has increased during the last years and the forecasts for upcoming years are exponential. One of the current major challenges consist in considering UAVs as autonomous swarms to address some limitations of single UAV usage such as autonomy, range of operation and resilience. In this article we propose novel mobility models for multi-level swarms of collaborating UAVs used for the coverage of a given area. These mobility models generate unpredictable trajectories using a chaotic solution of a dynamical system. We detail how the chaotic properties are used to structure the exploration of an unknown area and enhance the exploration part of an Ant Colony Optimization method. Empirical evidence of the improvement of the coverage efficiency obtained by our mobility models is provided via simulation. It clearly outperforms state-of-the-art approaches.
University of Luxembourg: High Performance Computing - ULHPC
Researchers
http://hdl.handle.net/10993/34390
10.1016/j.swevo.2018.01.002
https://www.sciencedirect.com/science/article/pii/S2210650217307587

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