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Sensors 2015, 15(10), 26430-26456; doi:10.3390/s151026430

Development of Kinematic 3D Laser Scanning System for Indoor Mapping and As-Built BIM Using Constrained SLAM

School of Civil and Environmental Engineering, College of Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea
Present Address: Department of Photogrammetry, Nussallee 15, Bonn 53115, Germany
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 13 July 2015 / Revised: 11 October 2015 / Accepted: 13 October 2015 / Published: 16 October 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [7157 KB, uploaded 16 October 2015]   |  

Abstract

The growing interest and use of indoor mapping is driving a demand for improved data-acquisition facility, efficiency and productivity in the era of the Building Information Model (BIM). The conventional static laser scanning method suffers from some limitations on its operability in complex indoor environments, due to the presence of occlusions. Full scanning of indoor spaces without loss of information requires that surveyors change the scanner position many times, which incurs extra work for registration of each scanned point cloud. Alternatively, a kinematic 3D laser scanning system, proposed herein, uses line-feature-based Simultaneous Localization and Mapping (SLAM) technique for continuous mapping. Moreover, to reduce the uncertainty of line-feature extraction, we incorporated constrained adjustment based on an assumption made with respect to typical indoor environments: that the main structures are formed of parallel or orthogonal line features. The superiority of the proposed constrained adjustment is its reduction for uncertainties of the adjusted lines, leading to successful data association process. In the present study, kinematic scanning with and without constrained adjustment were comparatively evaluated in two test sites, and the results confirmed the effectiveness of the proposed system. The accuracy of the 3D mapping result was additionally evaluated by comparison with the reference points acquired by a total station: the Euclidean average distance error was 0.034 m for the seminar room and 0.043 m for the corridor, which satisfied the error tolerance for point cloud acquisition (0.051 m) according to the guidelines of the General Services Administration for BIM accuracy. View Full-Text
Keywords: SLAM; laser scanner; point clouds; line feature; constrained least squares adjustment SLAM; laser scanner; point clouds; line feature; constrained least squares adjustment
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Jung, J.; Yoon, S.; Ju, S.; Heo, J. Development of Kinematic 3D Laser Scanning System for Indoor Mapping and As-Built BIM Using Constrained SLAM. Sensors 2015, 15, 26430-26456.

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