Drift analysis and sectional post-processing of indoor simultaneous localization and mapping (SLAM)-based laser scanning data

Aino Keitaanniemi; Petri Rönnholm; Antero Kukko; Matti Tapio Vaaja

doi:10.1016/j.autcon.2022.104700

Drift analysis and sectional post-processing of indoor simultaneous localization and mapping (SLAM)-based laser scanning data

Aino Keitaanniemi^*, Petri Rönnholm, Antero Kukko, Matti Tapio Vaaja

^*Corresponding author for this work

Finnish Geospatial Research Institute

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Abstract

Even though the SLAM laser scanners (LSs) have the required resolution for construction analysis, a drift error has been detected in georeferencing phase of the data processing. The reduction of drift error in SLAM LSs with third-party software has not been studied. This paper demonstrates the drift error behavior of commercial SLAM LSs and their correction with sectional post-processing methods, and shows that the drift error is mainly in a vertical direction, and it is largest in the middle of the trajectory. The drift error was reduced from 10.6 cm to 0.2 cm. Circa 30 s length sections have better results than larger sections with non-rigid transformation algorithm. The method has shown potential to improve the quality and cost-effectiveness of multitemporal construction documentation. In addition, locations of additional control points were analyzed to prevent drift error, with adjustments to the walking path.

Original language	English
Article number	104700
Journal	Automation in Construction
Volume	147
DOIs	https://doi.org/10.1016/j.autcon.2022.104700
Publication status	Published - Mar 2023
MoE publication type	A1 Journal article-refereed

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@Quality4Roads: Road Distress Mapping Combining Expertise of Sensors and Point Cloud Processing, Surveying and Road Engineering
Vaaja, M. T., Putkiranta, P., Kurkela, M. & Keitaanniemi, A.
01/09/2019 → 31/08/2023
Project: Academy of Finland: Other research funding
Competence-Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, Robotics, Geospatial Information and Image Processing/Computing Point Cloud Ecosystem
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
Project: 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
Project: Academy of Finland: Strategic research funding

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Matti Kurkela (Manager)
Department of Built Environment
Facility/equipment: Facility
i3 – Industry Innovation Infrastructure
Panu Sainio (Manager)
School of Engineering
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Cite this

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title = "Drift analysis and sectional post-processing of indoor simultaneous localization and mapping (SLAM)-based laser scanning data",

abstract = "Even though the SLAM laser scanners (LSs) have the required resolution for construction analysis, a drift error has been detected in georeferencing phase of the data processing. The reduction of drift error in SLAM LSs with third-party software has not been studied. This paper demonstrates the drift error behavior of commercial SLAM LSs and their correction with sectional post-processing methods, and shows that the drift error is mainly in a vertical direction, and it is largest in the middle of the trajectory. The drift error was reduced from 10.6 cm to 0.2 cm. Circa 30 s length sections have better results than larger sections with non-rigid transformation algorithm. The method has shown potential to improve the quality and cost-effectiveness of multitemporal construction documentation. In addition, locations of additional control points were analyzed to prevent drift error, with adjustments to the walking path.",

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AU - Vaaja, Matti Tapio

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Drift analysis and sectional post-processing of indoor simultaneous localization and mapping (SLAM)-based laser scanning data

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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

Equipment

3D-studio

i3 – Industry Innovation Infrastructure

Cite this