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DepthLiDAR: active segmentation of environment depth map into mobile sensors

2021Journal article Open access
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dc.contributor.authorLimeira, Marcelo A.
dc.contributor.authorPiardi, Luis
dc.contributor.authorKalempa, Vivian Cremer
dc.contributor.authorLeitão, Paulo
dc.contributor.authorOliveira, Andre Schneider
dc.date.accessioned2022-01-12T17:04:08Z
dc.date.available2022-01-12T17:04:08Z
dc.date.issued2021
dc.description.abstractThis paper presents a novel approach for creating virtual LiDAR scanners through the active segmentation of point clouds. The method employs top-view point cloud segmentation in virtual LiDAR sensors that can be applied to the intelligent behavior of autonomous agents. Segmentation is correlated with the visual tracking of the agent for localization in the environmentand point cloud. Virtual LiDARsensors with different characteristicsand positions can then be generated. Thismethod is referred to as the DepthLiDAR approach, and is rigorously evaluated to quantify its performance and determine its advantages and limitations. An extensive set of experiments is conducted using real and virtual LiDAR sensors to compare both approaches. The objective is to propose a novel method to incorporate spatial perception in warehouses, aiming to achieve Industry 4.0. Thus, it is tested in a low-scale warehouse to incorporate realistic features. The analysis of the experiments shows a measurement improvement of 52.24% compared to the conventional LiDAR.pt_PT
dc.description.sponsorshipThis work was supported in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil (CAPES)–Finance Code 001 and in part by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationLimeira, Marcelo; Piardi, Luis; Kalempa, Vivian Cremer; Leitão, Paulo; Oliveira, Andre Schneider (2021). DepthLiDAR: active segmentation of environment depth map into mobile sensors. IEEE Sensors Journal. ISSN 1558-1748. 21:17, p. 19047-19057pt_PT
dc.identifier.doi10.1109/JSEN.2021.3088007pt_PT
dc.identifier.issn1558-1748
dc.identifier.urihttp://hdl.handle.net/10198/24605
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectVirtual sensorspt_PT
dc.subjectLIDARpt_PT
dc.subjectPoint cloudpt_PT
dc.subjectActive segmentationpt_PT
dc.subjectIndustry 4.0.pt_PT
dc.titleDepthLiDAR: active segmentation of environment depth map into mobile sensorspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage19057pt_PT
oaire.citation.issue17pt_PT
oaire.citation.startPage19047pt_PT
oaire.citation.titleIEEE Sensors Journalpt_PT
oaire.citation.volume21pt_PT
person.familyNamePiardi
person.familyNameLeitão
person.givenNameLuís
person.givenNamePaulo
person.identifierA-8390-2011
person.identifier.ciencia-idC51A-82DB-016F
person.identifier.ciencia-id8316-8F13-DA71
person.identifier.orcid0000-0003-1627-8210
person.identifier.orcid0000-0002-2151-7944
person.identifier.scopus-author-id35584388900
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication643e9664-ec9b-4b2f-b93c-6f3f8335fd61
relation.isAuthorOfPublication68d9eb25-ad4f-439b-aeb2-35e8708644cc
relation.isAuthorOfPublication.latestForDiscovery643e9664-ec9b-4b2f-b93c-6f3f8335fd61

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