Design and Research of Low-Cost and Self-Adaptive Terrestrial Laser Scanning for Indoor Measurement Based on Adaptive Indoor Measurement Scanning Strategy and Structural Characteristics Point Cloud Segmentation
Auteur(s): |
Zhongyue Zhang
Huixing Zhou Shun Wang Chongwen Xu Yannan Lv |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Advances in Civil Engineering, janvier 2022, v. 2022 |
Page(s): | 1-24 |
DOI: | 10.1155/2022/5681771 |
Abstrait: |
Nowadays, TLS (terrestrial laser scanning) has been a relatively mature measuring equipment categorized to indoor measuring robots, but it is not widely adopted in indoor construction measurement at present. What accounts for its limited application are as follows: (1) the high cost of high-accuracy laser LIDAR and (2) existing TLS equipment does not possess self-adaptation scanning planning and takes no account of efficiency of point cloud processing and consumption of computing power. This paper proposes a novel TLS equipment and a high-efficiency point cloud processing method customized for the novel equipment, with purpose to achieve self-adaption measurement on the basis of indoor characteristics of construction during civil engineering at low cost. This paper mainly presents two parts of innovations: (1) for planning of scanning, the novel TLS features planning sampling density of scanning according to room size and converting scanning data from poses to point clouds, and (2) for processing of point clouds, this paper proposes two novel segmentation algorithms, namely, “on-boundary segmentation algorithm” and “on-angular-distance segmentation algorithm,” based on indoor spatial structure features and characteristics of TLS. Besides, this paper presents modified RANSAC-TLS (random sample consensus-total least squares) plane fitting algorithm, on basis of TLS point cloud distribution characteristics and spatial transformation. Through actual measurement test, it is concluded that the “on-boundary segmentation algorithm” and “on-angular-distance segmentation algorithm” are suitable for point cloud segmentation in different types of scenes. The modified RANSAC-TLS have made a great improvement on accuracy of fitting versus LS (least squares), TLS (total least squares), and RANSAC-LS. Finally, this paper conducts an experiment by executing an actual measurement and then preliminarily testifies the potential and future application of the proposed novel TLS (terrestrial laser scanning) equipment, with measurement parameters from it being changed in the experiment, by comparing with one existing TLS equipment—FARO. The test thus proves the relatively high feasibility and potential of the novel TLS presented in the paper (terrestrial laser scanning) in actual indoor measurement. |
Copyright: | © 2022 Zhongyue Zhang et al. et al. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10687214 - Publié(e) le:
13.08.2022 - Modifié(e) le:
10.11.2022