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Point Cloud Registration Method Based on Laser Scanner |
CHU Haiman1,CHENG Yinbao1,LI Yaru1,LUO Zai1,JIANG Wensong1,WANG Yan2 |
1. China Jiliang University, Hangzhou, Zhejiang 310018, China
2. Shenyang Aircraft Industry (Group) Co. Ltd, Shenyang, Liaoning 110850, China |
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Abstract Aiming at the difficult problem of aligning the incomplete point cloud obtained from the actual scanning of the laser scanner,a registration method based on corresponding point pairs is proposed.Firstly,experiments are conducted by a laser scanner to obtain the measured point cloud data of the measured workpiece and configuration of Point Cloud Library environment based on Visual Studio software to investigate the point cloud alignment of real and ideal models.Secondly,the measured point cloud data are preprocessed by voxel filtering and uniform downsampling.Then,the point cloud data are aligned by corresponding point pairs to provide a better initial value of the transformation for the subsequent fine alignment.The point cloud alignment is realized based on the ICP algorithm to realize the fine alignment.Finally,the root-mean-square error is used as an evaluation index of the accuracy of the point cloud alignment to evaluate the results of the alignment,and the results are analyzed with the aid of the CloudCompare software.The visual display and analysis show that the root mean square error of the alignment can be controlled at 0.62mm in the case where the measured workpiece itself is not absolutely smooth,which proves that the method has better results for the alignment of incomplete point clouds.
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Received: 23 October 2023
Published: 25 March 2024
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[6] |
方立伟. 三维激光扫描技术在隧道工程中的应用分析 [J]. 测绘与空间地理信息, 2023, 46(2): 163-165.
|
[2] |
CHEN C, LUCA Z F, ANTONIOS T. GAPointNet: Graph attention based point neural network for exploiting local feature of point cloud [J]. Neurocomputing 2021, 438: 122-132.
|
[4] |
LIU J Y, XU Y C, LU Z, et al. PCRMLP: A Two-Stage Network for Point Cloud Registration in Urban Scenes. [J]. Sensors, 2023, 23(12): 5758.
|
|
FANG L W. Analysis of the application of 3D laser scanning technology in tunnel engineering [J]. Geomatics & Spatial Information Technology, 2023, 46(2): 163-165.
|
[7] |
张旭, 陈爱军, 沈小燕, 等. 基于线激光传感器的工件尺寸测量系统的误差补偿方法 [J]. 计量学报, 2020, 41(12): 1449-1455.
|
[8] |
谭舸, 花向红, 陶武勇, 等. 基于激光跟踪仪的多测站地面激光扫描点云配准方法 [J]. 中国激光, 2021, 48(17): 151-163.
|
[9] |
李振国, 王林, 韦征, 等. 三维激光扫描仪的精度评价分析 [J]. 浙江工业大学学报, 2023, 51(1): 27-31.
|
[10] |
LI X, CHEN X P, LI W, et al. High-accuracy calibration method for an underwater one-mirror galvanometric laser scanner [J]. Optics express, 2023, 31(4): 5973-5989.
|
[13] |
蔡志敏. 基于点云数据的精简算法研究[D]. 北京:北京建筑大学, 2014.
|
[17] |
卢恒, 徐旭松, 王树刚, 等. 基于改进ICP算法的叶片型线轮廓度误差评定 [J]. 计量学报, 2022, 43(8): 1015-1020.
|
[20] |
徐鹏, 徐方勇, 陈辉. 融合配准的多站室外大场景激光点云分割 [J]. 计量学报, 2022, 43(3): 325-330.
|
[5] |
WANG X, YUAN Y. GCMTN: Low-Overlap Point Cloud Registration Network Combining Dense Graph Convolution and Multilevel Interactive Transformer [J]. Remote Sensing, 2023, 15(15): 3908.
|
[11] |
WANG Z Y, LI Y R, TANG Y Q, et al. Enhanced precision inspection of free-form surface with an improved whale optimization algorithm [J]. Optics Express, 2021, 29(17): 26909-26924.
|
|
WANG S M, ZHANG A W, CUI Y Y, et al. Global coordinate transformation oriented point cloud alignment implementation and accuracy evaluation [J]. Geotechnical Investigation and Surveying, 2011, 39(11): 62-65.
|
|
ZHANG Y C, LI Y B, FU X B. Point Cloud Segmentation De-noising Method Based on Curvature Constraint [J]. Acta Metrologica Sinica, 2020, 41(10): 1218-1225.
|
|
ZHANG L, XIAO J, CHENG X L, et al. 3D point cloud alignment based on multi-type geometric element matching [J]. Journal of University of Chinese Academy of Sciences, 2023, 40(2): 258-267.
|
|
LU H, XU X S, WANG S G, et al. Blade profile contour error assessment based on improved ICP algorithm [J]. Acta Metrologica Sinica, 2022, 43(8): 1015-1020.
|
[19] |
SUNR Y, ZHANG E Z, MU D Q, et al. Optimization of the 3D Point Cloud Registration Algorithm Based on FPFH Features [J]. Applied Sciences, 2023, 13(5): 3096.
|
[3] |
PIOTR F, ROBERT S, JAKUB M, et al. Fast adaptive multimodal feature registration (FAMFR): an effective high-resolution point clouds registration workflow for cultural heritage interiors [J]. Heritage Science, 2023, 11(1): 190.
|
|
LI Z G, WANG L, WEI Z, et al. Evaluation and analysis of accuracy of 3D laser scanners [J]. Journal of Zhejiang University of Technology, 2023, 51(1): 27-31.
|
[16] |
高珊珊. 基于三维激光扫描仪的点云配准[D]. 南京:南京理工大学, 2008.
|
[1] |
ZHAO T M, LI L F, TIAN T, et al. APUNet: Attention-guided upsampling network for sparse and non-uniform point cloud [J]. Pattern Recognition, 2023, 143: 109796.
|
|
TAN G, HUA X H, TAO W Y, et al. A multi-station ground laser scanning point cloud alignment method based on laser tracker [J]. Chinese Journal of Lasers, 2021, 48(17): 151-163.
|
[15] |
张龙, 肖俊, 程晓龙, 等. 基于多类型几何图元匹配的三维点云配准 [J]. 中国科学院大学学报, 2023, 40(2): 258-267.
|
|
ZHANG X, CHEN A J, SHEN X Y, et al. Error Compensation Method for Workpiece Size Measurement System Based on Line Laser Sensor [J]. Acta Metrologica Sinica, 2020, 41(12): 1449-1455.
|
[14] |
张玉存, 李亚彬, 付献斌. 基于曲率约束的点云分割去噪方法 [J]. 计量学报, 2020, 41(10): 1218-1225.
|
|
XU P, XU F Y, CHEN H. Large Scene Segmentation of Outdoor Laser Point Cloud Based on Fusion and Registration [J]. Acta Metrologica Sinica, 2022, 43(3): 325-330.
|
[12] |
王书民, 张爱武, 崔营营, 等. 面向全局坐标变换的点云配准实现及精度评价 [J]. 工程勘察, 2011, 39(11): 62-65.
|
[18] |
WANG W X, ZHAO C M, ZHANG H Y. PR-Alignment: Multidimensional Adaptive Registration Algorithm Based on Practical Application Scenarios [J]. Machines, 2023, 11(2): 254.
|
|
|
|