文献类型：期刊文献

中文题名：基于激光点云NDT特征的两步回环检测

英文题名：Two-step loop closure detection based on laser point cloud NDT features

作者：柴梦娜[1];刘元盛[2];任丽军[3]

第一作者：柴梦娜

机构：[1]北京联合大学智慧城市学院,北京100101;[2]北京联合大学机器人学院,北京100101;[3]北京联合大学北京市信息服务工程重点实验室,北京100101

第一机构：北京联合大学智慧城市学院

年份：2020

卷号：50

期号：1

起止页码：17-24

中文期刊名：激光与红外

外文期刊名：Laser & Infrared

收录：CSTPCD;;Scopus;北大核心:【北大核心2017】；CSCD:【CSCD2019_2020】；

基金：国家自然科学基金项目(No.61871039;No.61871038);北京联合大学人才强校优选计划项目(No.BPHR2017EZ02)资助。

语种：中文

中文关键词：同时定位与建图;NDT点云匹配;重叠网格;点云外观描述;两步回环检测

外文关键词：simultaneous localization and mapping;NDT point cloud registration;overlapping units;appearance description of point cloud;two-step loop closure detection

摘要：针对传统激光雷达配准算法进行大规模同时定位与建图(SLAM)时,存在较大累计误差的问题,本文提出一种基于正态分布变换(NDT)的两步回环检测方法,充分利用NDT配准中点云均值与方差特征,并将所提方法加入SLAM完整框架。点云匹配中采用重叠网格,首先根据各网格特征值,构建点云外观描述,进行粗回环检测。符合粗回环条件后,计算点云网格均值到坐标原点距离的方法使点云具有旋转不变性,进行精确回环检测。本文提出算法在“小旋风”智能车平台进行验证,实验表明,所提算法可以有效减小大规模建图中的累计误差,系统的鲁棒性更强,跟踪性能更好。
Since the traditional algorithm will cause great deviation when perform large-scale simultaneous mapping and localization.A two-step loop closure detection method based on normal distribution transformation(NDT)is proposed in this paper,which makes full use of NDT to register the midpoint cloud mean and variance characteristics,and adds the proposed method to the SLAM complete framework.Point cloud registration using overlapping grids.Firstly,a point cloud appearance description based on each grid feature value to implement coarse loop closure detection is constructed.If the coarse loop closure condition is met,in order to make the point cloud have rotation invariance,the distance between point cloud grid mean and coordinate origin is calculated to realize accurate loop detection.The proposed algorithm is verified on“small cyclone”autonomous car platform.Experiments show that the algorithm can effectively reduce the cumulative deviation in large-scale construction,the robustness of the system becomes stronger,and the tracking performance becomes better.