Point Cloud Registration Method for Pipeline Workpieces Based on RANSAC and Improved ICP Algorithms

Aiming at the registration problem of laser-scanned workpiece point cloud data, a point cloud registration method based on RANSAC algorithm and improved ICP algorithm is proposed. Firstly, feature points are selected according to the variation law of the normal vector in the original point cloud dat...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2019-10, Vol.612 (3), p.32190
Main Authors: Xue, Shan, Zhang, Zhen, Meng, Xianyu, Lv, Qiongying, Tu, Xin
Format: Article
Language:English
Subjects:
Algorithms
Histograms
Iterative algorithms
Matching
Quaternions
Random sampling
Registration
Workpieces
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Summary:Aiming at the registration problem of laser-scanned workpiece point cloud data, a point cloud registration method based on RANSAC algorithm and improved ICP algorithm is proposed. Firstly, feature points are selected according to the variation law of the normal vector in the original point cloud data, and the initial matching point set is obtained by establishing the histogram (FPFH) of feature points. Then a random sampling consensus (RANSAC) algorithm is applied to the initial data matching. At last, the nearest point iterative algorithm (ICP) accelerated by k-d tree is used for accurate matching, and the quaternion method is used to obtain the registration parameters. The new algorithm and PCA+ICP algorithm are tested and the experimental results are compared. The results show that the new algorithm can achieve registration, and improve the speed and accuracy of registration, which provide a reference for similar problems.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/612/3/032190