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Communication dans un congrès
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.
Keywords :
Cost function
Biological cells
Shape
Robot sensing systems
Algorithm design and analysis
autonomous aerial vehicles
cameras
genetic algorithms
indoor environment
mobile robots
particle swarm optimisation
robot vision
evolutionary algorithm
cameras networks positioning
unmanned aerial vehicles
UAV
particle swarm optimization
PSO
GA
satellite images
Coverage
Genetic Algorithm
Optimization
Mosaic
Application
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 17 juillet 2020 - 14:59:05
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : vendredi 15 septembre 2017 - 16:26:08
Dernière modification le : vendredi 17 juillet 2020 - 14:59:05