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

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...

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Bibliographic Details
Published inApplications of Evolutionary Computation pp. 332 - 347
Main Authors Atten, Christophe, Channouf, Loubna, Danoy, Grégoire, Bouvry, Pascal
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2016
SeriesLecture Notes in Computer Science
Subjects
Ant Colony Optimisation
Mobility model
Pheromone
Target tracking
UAV
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ISBN3319312030
9783319312033
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-31204-0_22

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Summary: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.
ISBN:3319312030
9783319312033
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-31204-0_22