Publication:
Coverage mission for UAVs using differential evolution and fast marching square methods

Simple item page
dc.affiliation.dptoUC3M. Departamento de Ingeniería de Sistemas y Automáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Robótica (Robotics Lab)es
dc.contributor.authorGonzález Pérez, Verónica
dc.contributor.authorMonje Micharet, Concepción Alicia
dc.contributor.authorGarrido Bullón, Luis Santiago
dc.contributor.authorMoreno Lorente, Luis Enrique
dc.contributor.authorBalaguer Bernaldo de Quirós, Carlos
dc.contributor.funderComunidad de Madrides
dc.date.accessioned2022-01-19T10:44:15Z
dc.date.available2022-01-19T10:44:15Z
dc.date.issued2020-02-01
dc.description.abstractThis research presents a novel approach for missions of coverage path planning (CPP) carried out by unmanned aerial vehicles (UAVs) in a three-dimensional environment. These missions are focused on path planning to cover a certain area in an environment in order to carry out tracking, search, or rescue tasks. The methodology followed uses an optimization process based on the differential evolution (DE) algorithm in combination with the Fast Marching Square (FM2) planner. The DE algorithm evaluates a cost function to determine what the zigzag path with the minimum cost is, according to the steering angle of the zigzag bands (alfa). This optimization process allows achieving the most optimal zigzag path in terms of distance traveled by the UAV to cover the whole area. Then, the FM2 method is applied to generate the final path according to the steering angle of the zigzag bands resulting from the DE algorithm. The approach generates a feasible path free from obstacles, keeping a fixed altitude flight over the ground. The flight level, smoothness, and safety of the path can be modified by two adjustment parameters included in our approach. Simulated experiments carried out in this work demonstrate that the proposed approach generates the most optimal zigzag path in terms of distance, safety, and smoothness to cover a certain whole area, keeping a determined flight level with successful results.en
dc.description.sponsorshipThis work was supported by the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU.en
dc.format.extent12
dc.identifier.bibliographicCitationGonzalez, V., Monje, C. A., Garrido, S., Moreno, L. & Balaguer, C. (2020). Coverage Mission for UAVs Using Differential Evolution and Fast Marching Square Methods. IEEE Aerospace and Electronic Systems Magazine, 35(2), 18–29.en
dc.identifier.doihttps://doi.org/10.1109/MAES.2020.2966317
dc.identifier.issn0885-8985
dc.identifier.publicationfirstpage18
dc.identifier.publicationissue2
dc.identifier.publicationlastpage29
dc.identifier.publicationtitleIEEE Aerospace and Electronic Systems Magazineen
dc.identifier.publicationvolume35
dc.identifier.urihttps://hdl.handle.net/10016/33911
dc.identifier.uxxiAR/0000025566
dc.language.isoengen
dc.publisherIEEEen
dc.relation.projectIDComunidad de Madrid. S2013/MIT-2748es
dc.rights© 2020, IEEE.en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaRobótica e Informática Industriales
dc.subject.otherHeuristic algorithmsen
dc.subject.otherSurface treatmenten
dc.subject.otherKinematicsen
dc.subject.otherTrajectoryen
dc.subject.otherCamerasen
dc.subject.otherTask analysisen
dc.subject.otherUnmanned aerial vehiclesen
dc.titleCoverage mission for UAVs using differential evolution and fast marching square methodsen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Coverage_AESM_2020_ps.pdf
Size:
5.53 MB
Format:
Adobe Portable Document Format
Download
Collections
DISA - LR - Artículos de Revistas