Evolutionary algorithm for positioning cameras networks mounted on UAV

Abstract : This paper aims to optimize the coverage of a given area from a set of views to allow a complete mosaicing. Among the investigated methods to find the best camera positions, two of them are studied, namely the Particle Swarm Optimization (PSO) and the Genetic Algorithms (GA). After having performed experiments to compare the algorithms, the hybridization of GA and PSO is investigated. To validate the proposed method, it is simulated area of irregular shapes with the cameras mounted on a Unmanned Aerial Vehicles (UAVs). V-REP is used to simulate the UAVs in an indoor environment and satellite images are used for a large outdoor area. The simulation validates the efficiency of the proposed method to find the optimal position of cameras. Then by using the images acquired it is possible to monitor the area and to compute a full mosaic of it.
Type de document :
Communication dans un congrès
Intelligent Vehicles Symposium (IV), 2017 IEEE, Jun 2017, Los Angeles, CA, United States. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, Intelligent Vehicles Symposium (IV), 2017 IEEE, pp.1758-1763, 2017, 〈http://ieeexplore.ieee.org/document/7995961/〉. 〈10.1109/IVS.2017.7995961〉
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01588439
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : vendredi 15 septembre 2017 - 16:26:08
Dernière modification le : vendredi 7 décembre 2018 - 16:48:04

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David Strubel,, Olivier Morel, Mohammed Saad Naufal, David Fofi. Evolutionary algorithm for positioning cameras networks mounted on UAV. Intelligent Vehicles Symposium (IV), 2017 IEEE, Jun 2017, Los Angeles, CA, United States. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, Intelligent Vehicles Symposium (IV), 2017 IEEE, pp.1758-1763, 2017, 〈http://ieeexplore.ieee.org/document/7995961/〉. 〈10.1109/IVS.2017.7995961〉. 〈hal-01588439〉

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