Fully automated extraction of railtop centerline from mobile laser scanning data

Digitization is an important part of efficient infrastructure maintenance. Means to achieve a digital asset database include precise 3D surveys of the physical assets and advanced automated recognition of objects of interest for documenting, maintenance and further analysis purposes. To this end, fast data collection of railway infrastructure environments can be obtained using a mobile laser scanner mounted on a service locomotive, permitting uninterruptive service. This paper presents an algorithm that extracts the railtop centerlines of up to seven parallel tracks with a single measurement pass and achieves an accuracy of 0.3 cm to 0.8 cm on non-intersecting rails, which improves the state of the art by 55%–85%. On intersecting rails, the railtop location accuracy is comparable to that of existing methods. The proposed method uses only geometric data and performs in real time in two-track railroad configurations. • Centimeter scale of rail width raises digitization accuracy requirements. • Locomotive-mounted mobile laser scanner permits uninterruptive data collection. • Local profile fitting enables sub-centimeter accuracy in rail modeling. • Guiding track centerline estimate aids runtime performance.

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Publication Details

Journal
Automation in Construction
Published
2024-10-16
DOI
https://doi.org/10.1016/j.autcon.2024.105812
Citations
6
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
1.23

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article

Fully automated extraction of railtop centerline from mobile laser scanning data

Juha M. Hyyppa, Harri Kaartinen, Antero Kukko, Matti Lehtomäki et al.
6 citations
Automation in Construction
Remote Sensing and LiDAR Applications
1.23
article

Fully automated extraction of railtop centerline from mobile laser scanning data

Juha M. Hyyppa, Harri Kaartinen, Antero Kukko, Matti Lehtomäki, Josef Taher, Aleksi Kononen
article en
6 citations

Abstract

Digitization is an important part of efficient infrastructure maintenance. Means to achieve a digital asset database include precise 3D surveys of the physical assets and advanced automated recognition of objects of interest for documenting, maintenance and further analysis purposes. To this end, fast data collection of railway infrastructure environments can be obtained using a mobile laser scanner mounted on a service locomotive, permitting uninterruptive service. This paper presents an algorithm that extracts the railtop centerlines of up to seven parallel tracks with a single measurement pass and achieves an accuracy of 0.3 cm to 0.8 cm on non-intersecting rails, which improves the state of the art by 55%–85%. On intersecting rails, the railtop location accuracy is comparable to that of existing methods. The proposed method uses only geometric data and performs in real time in two-track railroad configurations. • Centimeter scale of rail width raises digitization accuracy requirements. • Locomotive-mounted mobile laser scanner permits uninterruptive data collection. • Local profile fitting enables sub-centimeter accuracy in rail modeling. • Guiding track centerline estimate aids runtime performance.

Automation in ConstructionVol. 168
Finnish Geospatial Research Institute (FI), Aalto University (FI)
Academy of Finland, European Regional Development Fund
Affordable and clean energy
Openalex Percentile: Top 23%
Remote Sensing and LiDAR Applications
1.23
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Fully automated extraction of railtop centerline from mobile laser scanning data — Juha M. Hyyppa, Harri Kaartinen, et al. · Automation in Construction (2024) | TGRS Research Map | TGRS