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Point Cloud Alignment for Deposited Material Assessment in Tunnel Environments

2024-06-24Conference paper Restricted access
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datacite.subject.fosEngenharia e Tecnologia
datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorTeixeira, Abel
dc.contributor.authorCostelha, Hugo
dc.contributor.authorNeves, Carlos
dc.contributor.authorBento, Luis Conde
dc.date.accessioned2025-11-28T12:38:35Z
dc.date.available2025-11-28T12:38:35Z
dc.date.issued2024-06-24en_US
dc.date.updated2025-11-27T11:29:00Z
dc.descriptionkeywords provenientes de ieee.
dc.descriptionConference name 30th ICE IEEE/ITMC Conference on Engineering, Technology, and Innovation, ICE/ITMC 2024, Funchal
dc.descriptionConference date 24 June 2024 - 28 June 2024
dc.description.abstractThe assessment of deposited material in tunnel reinforcement operations can be performed using a 3D model generated from multiple scans. For this purpose, an accurate alignment of the scanned models is required. Aligning existing structure model with data scanned after surface deformations can be challenging, particularly if reference markers are not available or were displaced. For scenarios where the surrounding structure is largely changed, certain procedures can be adapted when processing the scanned data to achieve consistent alignment between scanned and reference structure models. This work proposes a methodology to cope with these situations, analysing the impact of different approaches. Experiments were performed in a realistic scenario related with shotcrete of railway tunnels wall surfaces, with the results showing the applicability of the developed work. The proposed procedure relies in highlighting the importance of specific points that describe the same feature in the reference and aligning PC. The proposed methodology achieved an RMS difference of 0.0173 m, which lead to a drastic improvement in the point cloud alignment compared to the use of standard ICP algorithm without data preprocessing, which achieved 0.0518 m in the studied use-case.eng
dc.description.sponsorshipFunding Agency: 10.13039/100016077-NextGeneration EU Funds 10.13039/100006129-Fundação para a Ciência e a Tecnologia
dc.description.sponsorshipFunding text This work has been supported by Project n 49, INOV.AM - Innovation in Additive Manufacturing co-funded by Recovery and Resilience Plan and NextGeneration EU Funds, www.recuperarportugal.gov.pt. This work was partly financed by Fundação para a Ciência e a Tecnologia (FCT) under the project DOI 10.54499/UIDB/00048/2020, https: //doi.org/10.54499/UIDB/00048/2020, and the R&D Unit INESC Coimbra, Advanced Robotics and Smart Factories (ROBiTECH) group, under reference UIDB/00308/2020 with DOI 10.54499/UIDB/00308/2020, as well as under the Scientific Employment Stimulus - Institutional Call CEECINST/00051/2018.
dc.description.sponsorshipPOCI-01-0247-FEDER-047075.
dc.description.versionN/A
dc.identifier.citationA. Teixeira, H. Costelha, C. Neves and L. C. Bento, "Point Cloud Alignment for Deposited Material Assessment in Tunnel Environments," 2024 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC), Funchal, Portugal, 2024, pp. 1-7, doi: 10.1109/ICE/ITMC61926.2024.10794331.
dc.identifier.doi10.1109/ice/itmc61926.2024.10794331en_US
dc.identifier.isbn979-835036243-5
dc.identifier.isbn979-8-3503-6244-2
dc.identifier.issn2693-8855
dc.identifier.issn2334-315X
dc.identifier.slugcv-prod-4437718
dc.identifier.urihttp://hdl.handle.net/10400.8/14775
dc.language.isoeng
dc.peerreviewedyes
dc.publisherieee
dc.relationInstitute for Systems Engineering and Computers at Coimbra - INESC Coimbra
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/10794331
dc.rights.uriN/A
dc.subjectPoint cloud compression
dc.subjectAdaptation models
dc.subjectTechnological innovation
dc.subjectThree-dimensional displays
dc.subjectRail transportation
dc.subjectData models
dc.subjectTrajectory
dc.subjectSurface treatment
dc.subjectRobots
dc.subjectStandards
dc.subjectPoint cloud
dc.subjectRegistration
dc.subjectTunnel scanning
dc.subjectRobotic shotcrete
dc.titlePoint Cloud Alignment for Deposited Material Assessment in Tunnel Environmentseng
dc.typeconference paperen_US
dspace.entity.typePublication
oaire.awardTitleInstitute for Systems Engineering and Computers at Coimbra - INESC Coimbra
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00308%2F2020/PT
oaire.citation.conferenceDate2024-06
oaire.citation.conferencePlaceFunchal, Portugal
oaire.citation.titleProceedings of the 30th ICE IEEE/ITMC Conference on Engineering, Technology, and Innovation: Digital Transformation on Engineering, Technology and Innovation, ICE 2024
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameCostelha
person.familyNameNeves
person.familyNameConde Bento
person.givenNameHugo
person.givenNameCarlos
person.givenNameLuis
person.identifier0000000133901858
person.identifier.ciencia-id931E-2249-DBA3
person.identifier.ciencia-idDC15-E18A-8C59
person.identifier.ciencia-idFE12-AAD0-3AB3
person.identifier.orcid0000-0003-0063-8592
person.identifier.orcid0000-0003-1733-3648
person.identifier.orcid0000-0002-9689-3637
person.identifier.ridV-4722-2017
person.identifier.ridF-4684-2014
person.identifier.ridF-7888-2013
person.identifier.scopus-author-id24775187600
person.identifier.scopus-author-id26768153200
person.identifier.scopus-author-id14070145000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.cv.cienciaid931E-2249-DBA3 | Hugo Costelha
rcaap.rightsclosedAccessen_US
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relation.isAuthorOfPublicationf87e8a37-498d-4ad4-810c-3c89d3171bf0
relation.isAuthorOfPublication0cfbb9a8-48d2-4547-bc90-01cde9d31be0
relation.isAuthorOfPublication.latestForDiscoveryf45387c3-8889-4588-9808-d2bcd2d5848d
relation.isProjectOfPublication254d9223-2e3b-4754-bae9-c98986d80921
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