The combined use of SLAM laser scanning and TLS for the 3D indoor mapping

Aino Keitaanniemi; Juho Pekka Virtanen; Petri Rönnholm; Antero Kukko; Toni Rantanen; Matti T. Vaaja

doi:10.3390/buildings11090386

The combined use of SLAM laser scanning and TLS for the 3D indoor mapping

Aino Keitaanniemi^*, Juho Pekka Virtanen, Petri Rönnholm, Antero Kukko, Toni Rantanen, Matti T. Vaaja

^*Tämän työn vastaava kirjoittaja

National Land Survey of Finland

Tutkimustuotos: Lehtiartikkeli › Article › Scientific › vertaisarvioitu

13 Sitaatiot (Scopus)

102 Lataukset (Pure)

Abstrakti

An efficient 3D survey of a complex indoor environment remains a challenging task, especially if the accuracy requirements for the geometric data are high for instance in building information modeling (BIM) or construction. The registration of non-overlapping terrestrial laser scanning (TLS) point clouds is laborious. We propose a novel indoor mapping strategy that uses a simultaneous localization and mapping (SLAM) laser scanner (LS) to support the building-scale registration of non-overlapping TLS point clouds in order to reconstruct comprehensive building floor/3D maps. This strategy improves efficiency since it allows georeferenced TLS data to only be collected from those parts of the building that require such accuracy. The rest of the building is measured with SLAM LS accuracy. Based on the results of the case study, the introduced method can locate non-overlapping TLS point clouds with an accuracy of 18–51 mm using target sphere comparison.

Alkuperäiskieli	Englanti
Artikkeli	386
Sivumäärä	18
Julkaisu	Buildings
Vuosikerta	11
Numero	9
DOI - pysyväislinkit	https://doi.org/10.3390/buildings11090386
Tila	Julkaistu - syysk. 2021
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Pääsy asiakirjaan

10.3390/buildings11090386

buildings-11-00386-v2Final published version, 6,75 MBLisenssi: CC BY

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@Quality4Roads: Tien laadun mittaaminen
Vaaja, M. T., Putkiranta, P., Kurkela, M., Keitaanniemi, A., Shafaat, O., Tuori, S. & Kauhanen, H.
01/09/2019 → 31/08/2023
Projekti: Academy of Finland: Other research funding
Osaamispohjainen kasvu 3D-digitalisaation, robotiikan, paikkatiedon ja kuvankäsittelyn sekä -laskennan yhdistetyssä teknologiamurroksessa
Hyyppä, H., Julin, A., Aho, S., Ahlavuo, M., Ingman, M., Kurkela, M., Siirala, H., Luhtala, L., Maksimainen, M., Gullmets, H., Nuikka, M., Sarlin, M., Handolin, H., Jaalama, K., El-Mahgary, S. & Vaaja, M. T.
01/01/2018 → 31/07/2021
Projekti: Academy of Finland: Strategic research funding
COMBAT: Competence-Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, Robotics, Geospatial Information and Image Processing/Computing - Point Cloud Ecosystem
Nieminen, J., Ahlavuo, M., Vaaja, M. T., Laitala, A., Julin, A., Hyyppä, H., Maksimainen, M., Lehtola, V., Ståhle, P., Haggren, H., Rantanen, T., Gullmets, H., Kauhanen, H., Jaalama, K., Virtanen, J., Ingman, M., Karvonen, S., Kurkela, M. & Luhtala, L.
01/05/2015 → 31/12/2017
Projekti: Academy of Finland: Strategic research funding

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title = "The combined use of SLAM laser scanning and TLS for the 3D indoor mapping",

abstract = "An efficient 3D survey of a complex indoor environment remains a challenging task, especially if the accuracy requirements for the geometric data are high for instance in building information modeling (BIM) or construction. The registration of non-overlapping terrestrial laser scanning (TLS) point clouds is laborious. We propose a novel indoor mapping strategy that uses a simultaneous localization and mapping (SLAM) laser scanner (LS) to support the building-scale registration of non-overlapping TLS point clouds in order to reconstruct comprehensive building floor/3D maps. This strategy improves efficiency since it allows georeferenced TLS data to only be collected from those parts of the building that require such accuracy. The rest of the building is measured with SLAM LS accuracy. Based on the results of the case study, the introduced method can locate non-overlapping TLS point clouds with an accuracy of 18–51 mm using target sphere comparison.",

keywords = "3D mapping 5, Non-overlap 2, Point clouds 4, Simultaneous localization and mapping (SLAM) 1, Terrestrial laser scanning (TLS) 3",

author = "Aino Keitaanniemi and Virtanen, {Juho Pekka} and Petri R{\"o}nnholm and Antero Kukko and Toni Rantanen and Vaaja, {Matti T.}",

note = "Funding Information: This research was funded by Aalto University School of Engineering Tenure track (Digital Photogrammetry) funding, the Academy of Finland the Strategic Research Council projects, ?Competence-Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, Robotics, Geospatial Information, and Image Processing/Computing?Point Cloud Ecosystem? (No. 293389, 314312), Academy of Finland project ?Quality4Roads? (No. 323783), project Profi5 ?Autonomous systems? (No. 326246), the European Social Fund (S21997) and the City of Helsinki Innovation fund. Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2021",

month = sep,

doi = "10.3390/buildings11090386",

language = "English",

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AU - Keitaanniemi, Aino

AU - Virtanen, Juho Pekka

AU - Rönnholm, Petri

AU - Kukko, Antero

AU - Rantanen, Toni

AU - Vaaja, Matti T.

N1 - Funding Information: This research was funded by Aalto University School of Engineering Tenure track (Digital Photogrammetry) funding, the Academy of Finland the Strategic Research Council projects, ?Competence-Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, Robotics, Geospatial Information, and Image Processing/Computing?Point Cloud Ecosystem? (No. 293389, 314312), Academy of Finland project ?Quality4Roads? (No. 323783), project Profi5 ?Autonomous systems? (No. 326246), the European Social Fund (S21997) and the City of Helsinki Innovation fund. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/9

Y1 - 2021/9

N2 - An efficient 3D survey of a complex indoor environment remains a challenging task, especially if the accuracy requirements for the geometric data are high for instance in building information modeling (BIM) or construction. The registration of non-overlapping terrestrial laser scanning (TLS) point clouds is laborious. We propose a novel indoor mapping strategy that uses a simultaneous localization and mapping (SLAM) laser scanner (LS) to support the building-scale registration of non-overlapping TLS point clouds in order to reconstruct comprehensive building floor/3D maps. This strategy improves efficiency since it allows georeferenced TLS data to only be collected from those parts of the building that require such accuracy. The rest of the building is measured with SLAM LS accuracy. Based on the results of the case study, the introduced method can locate non-overlapping TLS point clouds with an accuracy of 18–51 mm using target sphere comparison.

AB - An efficient 3D survey of a complex indoor environment remains a challenging task, especially if the accuracy requirements for the geometric data are high for instance in building information modeling (BIM) or construction. The registration of non-overlapping terrestrial laser scanning (TLS) point clouds is laborious. We propose a novel indoor mapping strategy that uses a simultaneous localization and mapping (SLAM) laser scanner (LS) to support the building-scale registration of non-overlapping TLS point clouds in order to reconstruct comprehensive building floor/3D maps. This strategy improves efficiency since it allows georeferenced TLS data to only be collected from those parts of the building that require such accuracy. The rest of the building is measured with SLAM LS accuracy. Based on the results of the case study, the introduced method can locate non-overlapping TLS point clouds with an accuracy of 18–51 mm using target sphere comparison.

KW - 3D mapping 5

KW - Non-overlap 2

KW - Point clouds 4

KW - Simultaneous localization and mapping (SLAM) 1

KW - Terrestrial laser scanning (TLS) 3

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The combined use of SLAM laser scanning and TLS for the 3D indoor mapping

Abstrakti

Pääsy asiakirjaan

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Muut tiedostot ja linkit

Sormenjälki

Projektit

@Quality4Roads: Tien laadun mittaaminen

Osaamispohjainen kasvu 3D-digitalisaation, robotiikan, paikkatiedon ja kuvankäsittelyn sekä -laskennan yhdistetyssä teknologiamurroksessa

COMBAT: Competence-Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, Robotics, Geospatial Information and Image Processing/Computing - Point Cloud Ecosystem

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