基于激光雷达与RGB-D相机融合Gmapping建图研究  

Gmapping Mapping Based on Lidar and RGB-D Camera Fusion

作　　者：李全峰 吴海波 陈江 张艺潇 Li Quanfeng;Wu Haibo;Chen Jiang;Zhang Yixiao(Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,Yunnan,China;Key Laboratory of Intelligent Manufacturing Technology for Advanced Equipment in Yunnan Province,Kunming 650500,Yunnan,China;Yunnan Advanced Equipment Intelligent Maintenance Engineering Research Center,Kunming 650500,Yunnan,China)

机构地区：[1]昆明理工大学机电工程学院,云南昆明650500 [2]云南省先进装备智能制造技术重点实验室,云南昆明650500 [3]云南省先进装备智能维护工程研究中心,云南昆明650500

出　　处：《激光与光电子学进展》2023年第12期386-393,共8页Laser & Optoelectronics Progress

基　　金：云南省人才培养基金(KKSY201701001);国家自然科学基金(51965029,52065035)。

摘　　要：针对移动机器人单激光雷达或RGB-D相机Gmapping建图时存在的障碍物检测不完全或建图效果不理想等问题,提出一种激光与相机融合Gmapping建图策略。首先,对相机点云和激光点云进行预处理,然后通过点云库(PCL)进行点云融合、滤波,采用点对线的迭代最近点(PL-ICP)算法进行相邻帧点云配准,以提高匹配精度和速率;接着,为了提高里程计精度,对视觉里程计、激光里程计采用Kalman滤波算法进行融合,对融合后的数据与轮式里程计进行动态加权二次融合;最后,在搭建好的移动机器人上验证所提方法。实验结果表明:与激光建图和相机建图方法相比,所提方法的障碍物检测率提高了32.03个百分点和19.86个百分点,地图的尺寸误差分别减小0.014 m和0.141 m,角度误差分别减小1°和3°;与原始里程计相比,里程计精度提高了0.12个百分点。This paper proposes a laser-camera fusion Gmapping mapping strategy to resolve problems of incomplete obstacle detection or unsatisfactory mapping effects when carrying lidar or an RGB-D camera on a mobile robot in Gmapping mapping.First,the camera point cloud and laser point cloud are preprocessed,and then point cloud fusion and filtering are performed by the point cloud library(PCL).The point-to-line iterative closest point(PL-ICP)algorithm is used to register the point cloud of adjacent frames to improve the matching accuracy and speed.Second,a visual odometer and a laser odometer are fused by the Kalman filtering algorithm,and the fused data and wheel odometer are dynamically weighted twice to improve the accuracy of odometers.Finally,the proposed method is verified on the built mobile robot.The experimental results show that the proposed method improves the obstacle detection rate by 32.03 percentage points and 19.86 percentage points,respectively,compared to the laser mapping and camera mapping methods,the size error of the map reduces by 0.014 m and 0.141 m,and the angle error decreases by 1°and 3°,respectively.The accuracy of the odometer is increased by 0.12 percentage points compared to the old odometer.

关 键 词：Gmapping 数据融合 里程计融合 激光雷达 RGB-D相机 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]