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Open AccessArticle

Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System

Institut Pascal, UMR 6602, Université Clermont Auvergne, CNRS, SIGMA Clermont, F-63000 Clermont-Ferrand, France
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Sensors 2019, 19(24), 5345; https://doi.org/10.3390/s19245345
Received: 8 November 2019 / Revised: 29 November 2019 / Accepted: 1 December 2019 / Published: 4 December 2019
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
Automatic and accurate mapping and modeling of underground infrastructure has become indispensable for several important tasks ranging from urban planning and construction to safety and hazard mitigation. However, this offers several technical and operational challenges. The aim of this work is to develop a portable automated mapping solution for the 3D mapping and modeling of underground pipe networks during renovation and installation work when the infrastructure is being laid down in open trenches. The system is used to scan the trench and then the 3D scans obtained from the system are registered together to form a 3D point cloud of the trench containing the pipe network using a modified global ICP (iterative closest point) method. In the 3D point cloud, pipe-like structures are segmented using fuzzy C-means clustering and then modeled using a nested MSAC (M-estimator SAmpling Consensus) algorithm. The proposed method is evaluated on real data pertaining to three different sites, containing several different types of pipes. We report an overall registration error of less than 7 % , an overall segmentation accuracy of 85 % and an overall modeling error of less than 5 % . The evaluated results not only demonstrate the efficacy but also the suitability of the proposed solution. View Full-Text
Keywords: 3D point cloud; LiDAR; pipes; automatic detection; segmentation; portable 3D scanning system 3D point cloud; LiDAR; pipes; automatic detection; segmentation; portable 3D scanning system
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Aijazi, A.K.; Malaterre, L.; Trassoudaine, L.; Chateau, T.; Checchin, P. Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System. Sensors 2019, 19, 5345.

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