摘要
在室外大场景下,激光里程计由于环境复杂难以进行精确点云配准,导致运动轨迹容易产生较大累计误差。针对该问题,提出了一种基于几何与强度约束配准的改进广义迭代最近点(GICP)算法。首先,通过点云的邻域特征计算待匹配点对的平均平面度与平面相似度,构造几何权重函数减小角点和不良对应点对在GICP算法点云配准过程中的误差,以提高算法精度。然后引入对称KL(Kullback-Leibler)散度参数构建强度相似度,衡量点对的强度差异,从而增加配准约束,并采用KD-Tree加速点云匹配对搜索以提高算法效率。KITTI数据集实验结果表明,所提算法的平均定位误差较GICP、VGICP算法分别降低了58.19%、45.64%。实地实验结果表明,所提算法的平均定位误差较GICP、VGICP算法分别降低了52.58%和37.12%,且满足实时性要求。
In large outdoor scenes,it is difficult for laser odometer to accurately register point clouds due to complex environments,resulting in a large cumulative error of motion trajectory.To solve this issue,an improved generalized iterative closest point(GICP)algorithm based on geometric and intensity constraint registration is proposed.Firstly,the average flatness and plane similarity of the point pairs to be matched are calculated by the neighborhood characteristics of the point clouds,and a geometric weight function is constructed to reduce the errors of corner points and poor corresponding point pairs during the point cloud registration process of the GICP algorithm,thereby improving the accuracy of the algorithm.Secondly,a symmetric KL(Kullback Leibler)divergence parameter is introduced to construct intensity similarity and measure the intensity difference of point pairs to increase registration constraints.Additionally,KD Tree is employed to accelerate the search of point cloud matching pairs to enhance the efficiency of the algorithm.The experimental results of KITTI dataset demonstrate that the average positioning error of the proposed algorithm is reduced by 58.19%and 45.64%compared with GICP and VGICP,respectively.Field experiment results show that the average positioning error of the proposed algorithm is reduced by 52.58%and 37.12%compared with GICP and VGICP,respectively,while meeting real time requirements.
作者
许士鋆
宋文吉
张博强
刘博翔
高向川
XU Shi-yun;SONG Wen-ji;ZHANG Bo-qiang;LIU Bo-xiang;GAO Xiang-chuan(College of Electrical and Information Engineering,Zhengzhou University,Zhengzhou 450001,China;College of Mechanical and Electrical Engineering,Henan University of Technology,Zhengzhou 450001,China)
出处
《激光与红外》
北大核心
2025年第6期861-869,共9页
Laser & Infrared
基金
国家自然科学基金项目(No.61640003)
河南省重点研发专项项目(No.231111241100)
河南省科技攻关项目(No.232102211067)资助。
关键词
激光里程计
点云配准
几何
强度
广义迭代最近点
laser odometer
point cloud registration
geometry
intensity
generalized iterative closest point
