光学精密工程2025，Vol.33Issue(13)：2136-2152,17.DOI:10.37188/OPE.20253313.2136
点云法向量与曲率关键特征配准
Key feature registration of point cloud normal vector and curvature
摘要
Abstract
To address the challenge of point cloud registration for complex feature targets,a method lever-aging point cloud normal vectors and curvature key features is proposed.Principal component analysis is utilized to compute curvature across varying neighborhood radii,facilitating effective key point selection and initial point cloud downsampling.For each key point,a seven-dimensional feature descriptor is con-structed,comprising four normal vectors and three curvature values,thereby encapsulating both angular relationships among normal vectors and curvature characteristics.Similarity between key point descriptors of source and target point clouds is assessed,and correspondences are initially established based on the ra-tio of the Euclidean minimum distance to the sub-minimum distance.The Random Sample Consensus(RANSAC)algorithm is subsequently employed to eliminate incorrect correspondences and reduce mis-matches.High-precision registration is achieved via the Iterative Closest Point(ICP)algorithm,enabling computation of the transformation matrix and quantitative evaluation of registration error.Experimental re-sults demonstrate a root mean square error(RMSE)of 3.32 mm in feature extraction and registration for complex targets,with an average error increment of 0.33 mm/(°)within a 0-50° registration range.Com-parative experiments confirm the superior robustness of the proposed method in large-angle registration of complex targets.Specifically,for space satellite targets,the RMSE of feature extraction and registration is 2.71 mm,accompanied by a Y-direction attitude angle error of 0.427°.The proposed method effectively sup-ports pose estimation and registration of space targets,indicating broad potential for practical applications.关键词
点云配准/复杂目标/法向量/曲率/误差分析Key words
point cloud registration/complex target/normal vector/curvature/error analysis分类
信息技术与安全科学引用本文复制引用
纪珍辰,艾宏旭,韩圆,姚家琦,李有治,王艳秋,郑福,王文杰,孙志斌..点云法向量与曲率关键特征配准[J].光学精密工程,2025,33(13):2136-2152,17.基金项目
国家重点研发计划资助项目(No.2023YFC2604900,No.2023YFC2604904,No.2023YFF0719800,No.2016YFE0131500) （No.2023YFC2604900,No.2023YFC2604904,No.2023YFF0719800,No.2016YFE0131500）
中国科学院科学仪器发展计划资助项目(No.YJKYYQ20190008) （No.YJKYYQ20190008）
