ORIGINAL ARTICLE
Various scenarios of measurements using a smartphone with a LiDAR sensor in the context of integration with the TLS point cloud
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Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, ul. Oczapowskiego 2, 10-719 Olsztyn, Poland
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article
Submission date: 2024-10-17
Final revision date: 2024-12-16
Acceptance date: 2025-01-02
Publication date: 2025-01-31
Corresponding author
Joanna Janicka
Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, ul. Oczapowskiego 2, 10-719 Olsztyn, Poland
Reports on Geodesy and Geoinformatics 2025;119:14-22
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ABSTRACT
Smartphones with Light Detection and Ranging (LiDAR) sensors are increasingly used for engineering measurements. Although the processing of the acquired point clouds seems similar to the processing of point clouds measured with, for example, a terrestrial laser scanner, processing data from a smartphone requires a special approach, first of all, when it comes to methods of obtaining and registering point clouds to obtain one complete metric point cloud. The research consisted of comparing various scenarios of measuring using a smartphone with a LiDAR sensor (a smartphone held in hand, a smartphone on a selfie stick, and a smartphone mounted on a gimbal), two acquisition strategies (one direction and zigzag) and two registration methods (point to point and cloud to cloud). The aim of the study was to find the best solution for registering the obtained point cloud with referenced terrestrial laser scanning (TLS) point cloud. It turns out that how we obtain field data using a smartphone with a LiDAR sensor is important and affects the accuracy of point cloud integration. The results showed that the use of additional devices such as a gimbal supports the data acquisition process and has an impact on the point cloud registration. In the analysed case, the RMSE registration error was the smallest and amounted to 0.012 m and 0.019 m, while the largest registration error was 0.060 m and 0.065 m, for object 1 and object 2, respectively. The result obtained using the proposed methodology can be considered satisfactory.
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