基于图搜索点对切线ICP的高精度激光点云配准方法  

A High-precision Point Cloud Registration Method Based on Graph Search Point-to-tangent ICP

作　　者：陈涛[1] 钱晓明[1] 楼佩煌[1] 彭立军 CHEN Tao;QIAN Xiaoming;LOU Peihuang;PENG Lijun(College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

机构地区：[1]南京航空航天大学机电学院,江苏南京210016

出　　处：《机器人》2024年第5期600-610,共11页Robot

基　　金：国家自然科学基金(61973154)。

摘　　要：针对基于迭代最近点的点云配准方法存在的相关点选择模型缺陷和初值敏感等问题,提出了一种基于图搜索的点对切线迭代最近点配准方法。首先,设计了一种基于图的搜索方法获取最近点,并提出更加符合观测特性的相关点点对切线模型假设,使用模拟激光射线与环境采样点切线的交点作为相关点,构建误差公式并求解。其次,实现了一种基于位姿粒子概率的粗配准方法,计算可能的位姿变换粒子并评分,将得分高的变换位姿作为精配准的初始输入位姿。最后,通过实验验证方法的可行性并与其他方法比较。结果表明,相比实验中的其他方法,本文方法能够在较短时间(100 ms)内完成两帧2维激光雷达数据的匹配并获得高精度的估计结果。To address the issues of defects in correspondence selection model and initial value sensitivity in existing ICP(iterative closest point)based point cloud registration methods,a point-to-tangent ICP registration method based on graph search is proposed.Firstly,a graph-based search method is designed to obtain the closest points and a more observationconformant hypothesis of correspondence point-to-tangent models is proposed.The intersections of simulated laser rays and the tangents of environmental sampling points are used as correspondence,then error formula is constructed and solved.Secondly,a coarse registration method based on pose particle probability is implemented to calculate possible pose transformation particles and score them,and the high-scored transformation poses are used as the initial input pose for fine registration.Finally,the feasibility of the method is verified through experiments and compared with other methods.The results show that,compared to other methods in the experiment,the proposed method can complete the matching of two frames of 2D LiDAR data in a short time(100 ms)and obtain high-precision estimation results.

关 键 词：点云配准 迭代最近点 图搜索 粒子概率 2维激光雷达 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TN958.98[自动化与计算机技术—控制科学与工程]