Abstract
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.
Highlights
Terrestrial light detection and ranging (LiDAR), known as terrestrial laser scanning (TLS), could quickly acquire the high-resolution point cloud on the target surface by high-speed laser scanning and had brought the traditional single point measurement into the era of surface measurement
Combined with the target sphere’s point cloud and geometric characteristics, a finite random search algorithm was proposed for fast calculation of the center of the target sphere
This algorithm was suitable for all types of sphere target point cloud data and had high fitting accuracy and operation efficiency
Summary
Terrestrial light detection and ranging (LiDAR), known as terrestrial laser scanning (TLS), could quickly acquire the high-resolution point cloud on the target surface by high-speed laser scanning and had brought the traditional single point measurement into the era of surface measurement. TLS technology had the characteristics of active, non-contact, high resolution, high precision, and rapid and flexible data acquisition It could go deep into the complex field environment and realize the complete collection of the various large, irregular and non-standard entity or real scene 3D data. Part of its contour information could be obtained from any angle of view, with which the spherical center and radius could be effectively solved It was widely used in the multi-class application research of terrestrial LiDAR, such as the calibration and check of a terrestrial laser scanner, scanning accuracy evaluation, registration, and georeferencing of point clouds et al [6,7,8,9,10,11]. The sphere fitting problem was a common problem to be solved in object tracking, pattern recognition, robotics, camera calibration, and other research work [12,13,14,15,16,17]
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