An Algorithm for Fitting Sphere Target of Terrestrial LiDAR

The sphere target played a vital role in terrestrial LiDAR applications, and solving its geometrical center based on point cloud was a widely concerned problem. In this study, we proposed a newly finite random search algorithm for sphere target fitting. Based on the point cloud data and the geometri...

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Autores principales:	Yintao Shi, Gang Zhao, Maomei Wang, Yi Xu, Dadong Zhu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	light detection and ranging point cloud sphere target constraint space parameters robustness Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/3d69b9d47d3b42cabcf05ea104f5986f
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id	oai:doaj.org-article:3d69b9d47d3b42cabcf05ea104f5986f
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spelling	oai:doaj.org-article:3d69b9d47d3b42cabcf05ea104f5986f2021-11-25T18:57:22ZAn Algorithm for Fitting Sphere Target of Terrestrial LiDAR10.3390/s212275461424-8220https://doaj.org/article/3d69b9d47d3b42cabcf05ea104f5986f2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7546https://doaj.org/toc/1424-8220The sphere target played a vital role in terrestrial LiDAR applications, and solving its geometrical center based on point cloud was a widely concerned problem. In this study, we proposed a newly finite random search algorithm for sphere target fitting. Based on the point cloud data and the geometric characteristics of the sphere target, the algorithm realized the target sphere fitting from the perspective of probability and statistics with the help of parameter estimation. Firstly, an initial constraint space was constructed, and the initial center and radius were determined by finite random search. Then, the optimal spherical center and radius were determined gradually through continuous iterative optimization. We tested the algorithm with the simulated and realistic point cloud. Experimental results showed that the proposed algorithm could be effectively applied to all kinds of point cloud fitting. When the coverage rate was bigger than 30%, the fitting accuracy could reach within 0.01 mm for all kinds of point clouds. When the coverage rate was less than 20%, the fitting accuracy can reach ±1 mm, although it was reduced to a certain extent.Yintao ShiGang ZhaoMaomei WangYi XuDadong ZhuMDPI AGarticlelight detection and rangingpoint cloudsphere targetconstraint spaceparametersrobustnessChemical technologyTP1-1185ENSensors, Vol 21, Iss 7546, p 7546 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	light detection and ranging point cloud sphere target constraint space parameters robustness Chemical technology TP1-1185
spellingShingle	light detection and ranging point cloud sphere target constraint space parameters robustness Chemical technology TP1-1185 Yintao Shi Gang Zhao Maomei Wang Yi Xu Dadong Zhu An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
description	The sphere target played a vital role in terrestrial LiDAR applications, and solving its geometrical center based on point cloud was a widely concerned problem. In this study, we proposed a newly finite random search algorithm for sphere target fitting. Based on the point cloud data and the geometric characteristics of the sphere target, the algorithm realized the target sphere fitting from the perspective of probability and statistics with the help of parameter estimation. Firstly, an initial constraint space was constructed, and the initial center and radius were determined by finite random search. Then, the optimal spherical center and radius were determined gradually through continuous iterative optimization. We tested the algorithm with the simulated and realistic point cloud. Experimental results showed that the proposed algorithm could be effectively applied to all kinds of point cloud fitting. When the coverage rate was bigger than 30%, the fitting accuracy could reach within 0.01 mm for all kinds of point clouds. When the coverage rate was less than 20%, the fitting accuracy can reach ±1 mm, although it was reduced to a certain extent.
format	article
author	Yintao Shi Gang Zhao Maomei Wang Yi Xu Dadong Zhu
author_facet	Yintao Shi Gang Zhao Maomei Wang Yi Xu Dadong Zhu
author_sort	Yintao Shi
title	An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
title_short	An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
title_full	An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
title_fullStr	An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
title_full_unstemmed	An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
title_sort	algorithm for fitting sphere target of terrestrial lidar
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3d69b9d47d3b42cabcf05ea104f5986f
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An Algorithm for Fitting Sphere Target of Terrestrial LiDAR

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