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dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.contributor.authorArana-Arexolaleiba, Nestor
dc.contributor.otherEtxeberria Garcia, Mikel
dc.contributor.otherZamalloa, Maider
dc.contributor.otherLabayen, Mikel
dc.date.accessioned2022-11-29T11:04:35Z
dc.date.available2022-11-29T11:04:35Z
dc.date.issued2022
dc.identifier.issn2169-3536en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=170353en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/5896
dc.description.abstractLocalization is one of the most critical tasks for an autonomous vehicle, as position information is required to understand its surroundings and move accordingly. Visual Odometry (VO) has shown promising results in the last years. However, VO algorithms are usually evaluated in outdoor street scenarios and do not consider underground railway scenarios, with low lighting conditions in tunnels and significant lighting changes between tunnels and railway platforms. Besides, there is a lack of GPS, and it is not easy to access such infrastructures. This research proposes a method to create a ground truth of images and poses in underground railway scenarios. Second, the EnlightenGAN algorithm is proposed to face challenging lighting conditions, which can be coupled with any state-of-the-art VO techniques. Finally, the obtained ground truth and the EnlightenGAN have been tested in a real scenario. Two different VO approaches have been used: ORB-SLAM2 and DF-VO. The results show that the EnlightenGAN enhancement improves the performance of both approaches.en
dc.description.sponsorshipGobierno Vasco-Eusko Jaurlaritzaes
dc.language.isoengen
dc.publisherIEEEen
dc.rights© 2022 The Authors © 2022 IEEEen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectLightingen
dc.subjectRail transportationen
dc.subjectCamerasen
dc.subjectLocation awarenessen
dc.subjectEstimationen
dc.subjectStandardsen
dc.subjectVisual odometryen
dc.titleVisual Odometry in Challenging Environments: An Urban Underground Railway Scenario Caseen
dc.typeinfo:eu-repo/semantics/articleen
dcterms.accessRightsinfo:eu-repo/semantics/openAccessen
dcterms.sourceIEEE Access.en
dc.description.versioninfo:eu-repo/semantics/publishedVersionen
local.contributor.groupRobótica y automatizaciónes
local.description.peerreviewedtrueen
local.description.publicationfirstpage69200en
local.description.publicationlastpage69215en
local.identifier.doihttps://doi.org/10.1109/ACCESS.2022.3187209en
local.relation.projectIDBikaintek 2018en
local.rights.publicationfeeAPCen
local.rights.publicationfeeamount1850$en
local.contributor.otherinstitutionhttps://ror.org/04m5j1k67en
local.contributor.otherinstitutionhttps://ror.org/03hp1m080es
local.contributor.otherinstitutionhttps://ror.org/000xsnr85es
local.source.detailsVol. 10. Pp. 69200-69215. July, 2022en
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore


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