Reference : Improving Pheromone Communication for UAV Swarm Mobility Management
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/53507
Improving Pheromone Communication for UAV Swarm Mobility Management
English
Stolfi Rosso, Daniel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG >]
Brust, Mathias mailto [University of Luxembourg > > >]
Danoy, Grégoire mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
30-Jul-2021
ICCCI 2021: Computational Collective Intelligence
228-240
Yes
International Conference on Computational Collective Intelligence (ICCCI 2021)
from 29-09-2021 to 01-10-2021
Rhodes
Greece
[en] Unmanned aerial vehicle ; Pheromones ; Evolutionary algorithm ; Surveillance system ; Swarm robotics ; Mobility model
[en] In this article we address the optimisation of pheromone communication used for the mobility management of a swarm of Unmanned Aerial Vehicles (UAVs) for surveillance applications. A genetic algorithm is proposed to optimise the exchange of pheromone maps used in the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model which improves the vehicles’ routes in order to achieve unpredictable trajectories as well as maximise area coverage. Experiments are conducted using realistic simulations, which additionally permit to assess the impact of packet loss ratios on the performance of the surveillance system, in terms of reliability and area coverage.
ONRG
http://hdl.handle.net/10993/53507
10.1007/978-3-030-88081-1_17
https://doi.org/10.1007/978-3-030-88081-1_17

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