计算机与数字工程2024，Vol.52Issue(1)：227-232,6.DOI:10.3969/j.issn.1672-9722.2024.01.038
基于点密度调整的激光雷达点云配准改进方法
An Improved LiDAR Registration Alogrithm Based on Point Density Adjustment
摘要
Abstract
Due to the scanning mechanism,the point cloud data collected by line-scan LiDAR presents obvious stripe struc-tures.In order to guarantee the registration results,an improved LiDAR point cloud registration method based on point density ad-justment is proposed.First,the input data are transformed into a supervoxel frame by an octree algorithm and a region growing meth-od.Then,the resampling process is constrained based on the framework,and new points are projected along the normal direction.Then,the distribution of the insertion points are adjusted to minimize an energy function to make the points evenly distributed.Ex-periments show that the algorithm can improve the quality of point cloud and the registration accuracy of classical ICP algorithm and 3D-NDT algorithm.Furthermore,the registration time is reduced.关键词
点云重采样/点云配准/迭代最近点算法/正态分布转换算法/线扫激光雷达Key words
point cloud resampling/registration/ICP alogrithm/NDT alogrithm/line-scan LiDAR分类
信息技术与安全科学引用本文复制引用
王翊成,李明磊,魏大洲,吴伯春..基于点密度调整的激光雷达点云配准改进方法[J].计算机与数字工程,2024,52(1):227-232,6.基金项目
国家自然科学基金项目(编号:41801342) （编号:41801342）
中央高校基本科研业务费(编号:NZ2020008XZA20016)资助. （编号:NZ2020008XZA20016）
