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

^*Corresponding author for this work

National Land Survey of Finland

Research output: Contribution to journal › Article › Scientific › peer-review

16 Citations (Scopus)

144 Downloads (Pure)

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.

Original language	English
Article number	386
Number of pages	18
Journal	Buildings
Volume	11
Issue number	9
DOIs	https://doi.org/10.3390/buildings11090386
Publication status	Published - Sept 2021
MoE publication type	A1 Journal article-refereed

Keywords

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

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10.3390/buildings11090386

buildings-11-00386-v2Final published version, 6.75 MBLicence: CC BY

Cite this

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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.",

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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",

volume = "11",

journal = "Buildings",

issn = "2075-5309",

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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

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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.

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

Abstract

Keywords

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@Quality4Roads: Road Distress Mapping Combining Expertise of Sensors and Point Cloud Processing, Surveying and Road Engineering

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

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

Cite this

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

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Projects

@Quality4Roads: Road Distress Mapping Combining Expertise of Sensors and Point Cloud Processing, Surveying and Road Engineering

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

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

Cite this