激光雷达扫描数据的快速三角剖分及局部优化  

Fast triangulation and local optimization for scan data of laser radar

作　　者：未永飞[1] 杜正春[1,2] 姚振强[1,2] 

机构地区：[1]上海交通大学机械工程与动力学院,上海200240 [2]上海交通大学机械系统与振动国家重点实验室,上海200240

出　　处：《激光技术》2009年第6期642-644,647,共4页Laser Technology

基　　金：国家自然科学基金资助项目(50805094);国家九七三重点基础研究发展计划资助项目(2006CB705400)

摘　　要：为了研究3维激光雷达测量所得点云数据的三角构网,根据激光雷达逐行扫描特点,采用了改进的三角剖分方法,对点云数据进行不规则三角网格划分。基于激光雷达点云数据位置拓扑信息,分析了相邻扫描线之间数据点的相对位置关系,利用几何关系进行初步配对构网;并结合经典法则对初始网格进行局部优化,得到最终三角网;同时,对优化前后的三角网,提出一种新的评价法则进行剖分效果对比。结果表明,充分利用点云特点进行三角剖分可改进算法。所提出的剖分效果评价法可帮助检验构网质量。In order to study the triangulation for the point cloud data collected by a three-dimension laser radar, in accordance with the line-by-line characteristics of laser radar scanning, an improved Delaunay triangulation method was proposed to mesh the point cloud data as an irregular triangulation network. Based on the geometric topology location information among radar point cloud data,focusing on the position relationship between adjacent scanning line of the point data,a preliminary match network was obtained according to their geometric relationship. A reasonable triangulation network for the object surface was acquired by means of local optimization on initial mesh by Delaunay rule. Meanwhile, a new judging rule was proposed to contrast the triangulation before and after the optimization on the network. The result shows that triangulation for point cloud with full use of its own characteristics can improve the speed of the algorithm obviously ,and the rule for judging the triangulation can be used to evaluate the quality of network.

关 键 词：图像处理 三角剖分 局部优化 点云数据 激光雷达 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]