摘要
机载LiDAR系统与船载LiDAR系统是获取海岸带点云数据的常用方式。两种测量系统所测数据具有空间差异性和互补性,对这两类非同源点云数据进行配准具有重要意义。本研究提出一种基于三角面元的LiDAR点云配准算法,根据空间分布将目标点云分割成若干不规则的三角面元作为配准基元,利用点-面变换模型,最小化源点云中的测量点与其平面位置处的三角面元间的距离,最终实现海岸带区域点云配准。实验结果表明,配准前后的样本点距离平均误差和点-面距离均方根误差分别从3.30和1.51 m降低到0.76和0.17 m,本研究基于三角面元的点云配准方法可以有效消除海岸带非同源点云数据测量空隙、角度偏差等现象。
Airborne LiDAR and shipborne LiDAR measurement systems are commonly used methods to obtain point cloud data in coastal zones.The data measured by the two measurement systems have spatial differences and complementarity,which is of great significance for the registration of two types of non-homologous point clouds.In this paper,a point cloud registration method based on triangular facet was proposed.The target point cloud was d ivided into several irregular triangular facets according to the spatial distribution.Then,the point-area transformation model was used to minimize the distance between the measurement point in the source point cloud and the triangular facet at its plane location.Finally,the registration of coastal point clouds was achieved.The experimental results demonstrated that the mean error of sample point distance and the root mean square error of point-to-surface distance were reduced from 3.30 and 1.51 m to 0.76 and 0.17 m respectively.The registration algorithm based on triangular facets can effectively eliminate phenomena such as measurement gaps and angle deviations in non-homologous point clouds in coastal areas.
作者
程玉璐
于孝林
王贤昆
孔锁财
宿殿鹏
阳凡林
CHENG Yulu;YU Xiaolin;WANG Xiankun;KONG Suocai;SU Dianpeng;YANG Fanlin(College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590,China;Key Laboratory of Ocean Geomatics,Ministry of Natural Resources of China,Qingdao 266590,China;North Sea Survey Center,Ministry of Natural Resources of China,Qingdao 266061,China;Shandong Ruizhi Flight Control Technology Co.Ltd,Qingdao 266590,China)
出处
《山东科技大学学报（自然科学版）》
CAS
北大核心
2024年第3期41-50,共10页
Journal of Shandong University of Science and Technology(Natural Science)
基金
国家自然科学基金项目(41930535,52001189)
青岛市关键技术攻关及产业化示范类项目(23-1-3-hygg-1-hy)
中国博士后科学基金项目(2021M700155)
山东科技大学科研创新团队支持计划项目(2019TDJH103)
山东省高等学校青创科技支持计划项目(2023KJ088)。
