Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Assessment of SLAM Scanner Accuracy for Outdoor and Indoor Surveying Tasks

Version 1 : Received: 19 April 2024 / Approved: 23 April 2024 / Online: 23 April 2024 (11:59:07 CEST)

How to cite: Gharineiat, Z.; Tarsha Kurdi, F.; Henny, K.; Gray, H.; Jamieson, A.; Reeves, N. Assessment of SLAM Scanner Accuracy for Outdoor and Indoor Surveying Tasks. Preprints 2024, 2024041484. https://doi.org/10.20944/preprints202404.1484.v1 Gharineiat, Z.; Tarsha Kurdi, F.; Henny, K.; Gray, H.; Jamieson, A.; Reeves, N. Assessment of SLAM Scanner Accuracy for Outdoor and Indoor Surveying Tasks. Preprints 2024, 2024041484. https://doi.org/10.20944/preprints202404.1484.v1

Abstract

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

Keywords

SLAM; LiDAR; accuracy assessment; indoor and outdoor; data acquisition

Subject

Environmental and Earth Sciences, Remote Sensing

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