基于激光雷达与深度相机融合的SLAM算法  

SLAM Algorithm Based on Fusion of LiDAR and Depth Camera

作　　者：刘庆运[1,2] 杨华阳 刘涛 吴天跃[1,2] 卢超 LIU Qingyun;YANG Huayang;LIU Tao;WU Tianyue;LU Chao(School of Mechanical Engineering,Anhui University of Technology,Maanshan 243032,China;Anhui Key Laboratory of Special Heavy Duty Robot,Maanshan 243032,China)

机构地区：[1]安徽工业大学机械工程学院,马鞍山243032 [2]特种重载机器人安徽省重点实验室,马鞍山243032

出　　处：《农业机械学报》2023年第11期29-38,共10页Transactions of the Chinese Society for Agricultural Machinery

基　　金：安徽省科技重大专项项目(201903a05020029)。

摘　　要：针对单一传感器地图构建时存在环境表征不充分,无法为移动机器人自主导航提供完整环境地图等问题,本文通过将激光雷达与深度相机获取的环境信息进行互补融合,构建出更完整精确的栅格地图。首先,对传统ORB-SLAM2算法进行增强,使其具备稠密点云地图构建、八叉树地图构建以及栅格地图构建等功能。其次,为验证增强后ORB-SLAM2算法的性能,在fr1_desk1数据集和真实场景下进行测试,数据显示增强后ORB-SLAM2算法绝对位姿误差降低52.2%,相机跟踪轨迹增长14.7%,定位更加精准。然后,D435i型深度相机采用增强型ORB-SLAM2算法,激光雷达采用的Gmapping-Slam算法,按照贝叶斯估计的规则进行互补融合构建全局栅格地图。最后,搭建实验平台进行验证,并分别与深度相机和激光雷达2个传感器建图效果进行对比。实验结果表明,本文融合算法对周围障碍物的识别能力更强,可获取更完整的环境信息,地图构建更加清晰精确,满足移动机器人导航与路径规划的需要。To address the problems of inadequate environmental representation in single sensor map construction and inability to provide a complete environmental map for autonomous navigation of mobile robots,a more complete and accurate raster map was constructed by complementary fusion of environmental information obtained from LiDAR and depth cameras.Firstly,the traditional ORB-SLAM2 algorithm was enhanced to have the functions of dense point cloud map construction,octree map construction and raster map construction.Secondly,in order to verify the performance of the enhanced ORB-SLAM2 algorithm,it was tested in the fr1_desk1 dataset and real scenes,and the data showed that the absolute position error of the enhanced ORB-SLAM2 algorithm was reduced by 52.2%,and the camera tracking trajectory grew by 14.7%,which made the localization more accurate.Then the D435i type depth camera adopted the enhanced ORB-SLAM2 algorithm and the Gmapping-Slam algorithm adopted by LiDAR,and constructed the global raster map by complementary fusion according to the rules of Bayesian estimation.Finally,an experimental platform was built for validation and compared with the map building effect of the two sensors,depth camera and LiDAR,respectively.The experimental results showed that the fusion algorithm had a stronger ability to recognize the surrounding obstacles,which can obtain more complete environmental information,and the map construction was more clear and precise,which met the needs of mobile robot navigation and path planning.

关 键 词：同步定位与地图构建 深度相机 激光雷达 贝叶斯估计 全局栅格地图 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]