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2016 | OriginalPaper | Chapter

UAV Fleet Mobility Model with Multiple Pheromones for Tracking Moving Observation Targets

Authors : Christophe Atten, Loubna Channouf, Grégoire Danoy, Pascal Bouvry

Published in: Applications of Evolutionary Computation

Publisher: Springer International Publishing

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Abstract

The last years, UAVs have been developed to address a variety of applications ranging from searching and tracking to the surveillance of an area. However, using a single UAV limits the range of possible applications. Therefore, fleets of UAVs are nowadays considered to work together on a common goal which requires novel distributed mobility management models. This work proposes a novel nature-inspired mobility model for UAV fleets based on Ant Colony Optimisation approaches (ACO). It relies on two types of pheromones, a repulsive pheromone to cover the designated area in an efficient way, and an attractive pheromone to detect and to track the maximum number of targets. Furthermore, all decision takings are taken online by each UAV and are fully distributed. Experimental results demonstrate promising target tracking performances together with a small increase in the exhaustivity of the coverage.

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Metadata
Title
UAV Fleet Mobility Model with Multiple Pheromones for Tracking Moving Observation Targets
Authors
Christophe Atten
Loubna Channouf
Grégoire Danoy
Pascal Bouvry
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-31204-0_22

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