Fecha
2010-05-24
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Derechos de acceso
info:eu-repo/semantics/openAccess
Título de la revista
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Editor
IEEE Xplore
Citas
0 citas en 
207 citas en 
Resumen
This paper presents a path planner for multiple unmanned aerial vehicles (UAVs) based on evolutionary algorithms (EAs) for realistic scenarios. The paths returned by the algorithm fulfill and optimize multiple criteria that 1) are calculated based on the properties of real UAVs, terrains, radars, and missiles and 2) are structured in different levels of priority according to the selected mission. The paths of all the UAVs are obtained with the multiple coordinated agents coevolution EA (MCACEA), which is a general framework that uses an EA per agent (i.e., UAV) that share their optimal solutions to coordinate the evolutions of the EAs populations using cooperation objectives. This planner works offline and online by means of recalculating parts of the original path to avoid unexpected risks while the UAV is flying. Its search space and computation time have been reduced using some special operators in the EAs. The successful results of the paths obtained in multiple scenarios, which are statistically analyzed in the paper, and tested against a simulator that incorporates complex models of the UAVs, radars, and missiles, make us believe that this planner could be used for real-flight missions.
Descripción
Este es el manuscrito aceptado del artículo. La versión registrada fue publicada por primera vez en in IEEE Transactions on Robotics, vol. 26, no. 4, pp. 619-634, Aug. 2010, está disponible en línea en el sitio web del editor: https://doi.org/10.1109/TRO.2010.2048610.
This is the accepted manuscript of the article. The registered version was first published in IEEE Transactions on Robotics, vol. 26, no. 4, pp. 619–634, Aug. 2010, and is available online from the publisher's website: https://doi.org/10.1109/TRO.2010.2048610.
Categorías UNESCO
Palabras clave
Unmanned aerial vehicles, Evolutionary computation, Mobile robots, Radar, Missiles, Path planning, Remotely operated vehicles, Constraint optimization, Testing, Computational modeling
Citación
E. Besada-Portas, L. de la Torre, J. M. de la Cruz and B. de Andrés-Toro, ""Evolutionary Trajectory Planner for Multiple UAVs in Realistic Scenarios,"" in IEEE Transactions on Robotics, vol. 26, no. 4, pp. 619-634, Aug. 2010, doi: https://doi.org/10.1109/TRO.2010.2048610
Centro
E.T.S. de Ingeniería Informática
Departamento
Informática y Automática