基于增强型ORB-SLAM 3算法的黄瓜植株稠密建图  

Cucumber Plant Thickness Construction Map Based on Enhanced ORB-SLAM 3 Algorithm

作　　者：王悦辰 周静[1,2] 黄志刚 陈勇明 王纪章 倪纪恒[1] WANG Yuechen;ZHOU Jing;HUANG Zhigang;CHEN Yongming;WANG Jizhang;NI Jiheng(School of Agricultural Engineering,Jiangsu University,Zhenjiang 212013,China;Jiangsu Province Research Centre of Intelligent Horticultural Facilities Engineering and Technology,Changshu 215555,China)

机构地区：[1]江苏大学农业工程学院,镇江212013 [2]江苏省物联网智慧园艺设施工程技术研究中心,常熟215555

出　　处：《农业机械学报》2024年第S1期270-279,共10页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金项目(32171896);江苏省重点研发计划项目(BE2002327);新疆维吾尔自治区重点研发计划专项(2022B02032);苏州市重点研发计划项目(SNG2022022)

摘　　要：为了实现温室高秆作物(黄瓜)植株的点云获取,本文提出一种稠密建图算法。该算法基于ORB-SLAM 3算法架构,通过改进特征点的提取过程,采用四叉树的提取方法使得特征点分布更为均匀,提升关键点质量。加入稠密建图线程、八叉树地图线程、栅格地图线程。稠密建图线程通过恢复单帧点云,并结合统计滤波与体素滤波进行处理,再根据黄瓜植株两侧的相机位姿将黄瓜点云从相机坐标系转移到世界坐标系下进行配准融合。相较于传统的转台式多视角配准方式,该算法解决了垄两侧点云的配准信息缺失问题,成功实现垄两侧黄瓜点云的自动配准融合,最终获得高精度的温室与黄瓜作物的点云模型。为验证本研究的实用性,进行TUM数据集与真实场景的测试,结果表明增强型ORB-SLAM 3算法运行轨迹更精准,其绝对误差平均降低21.4%。本研究可实现高秆作物的三维点云获取,能够为后续表型数据分析提供基础数据。In order to achieve the point cloud acquisition of cucumber plants in greenhouse tall crops,a dense map building algorithm was proposed.The algorithm was based on the ORB-SLAM 3 algorithm architecture.Firstly,by improving the extraction process of feature points,the quadtree extraction method was used to make the distribution of feature points more uniform and improve the quality of key points.Secondly,it added dense map building thread,octree map thread and raster map thread.The dense mapping thread usually recovered single-frame point clouds and combined statistical filtering and voxel filtering,and then transferred the cucumber point clouds from the camera coordinate system to the world coordinate system for alignment and fusion according to the camera poses on both sides of the cucumber plants.Compared with the traditional rotary multi-view alignment method,it solved the problem of missing alignment information of the point clouds on both sides of the ridge,and successfully achieved the automatic alignment and fusion of the point clouds on both sides of the ridge,and finally obtained a high-accuracy greenhouse point cloud.The algorithm solved the problem of missing information in the point cloud on both sides of the ridge,and successfully achieved the automatic alignment of cucumber point clouds on both sides of the ridge.In order to verify the practicality,the TUM dataset and the real scene were tested,and the results showed that the enhanced ORB-SLAM 3 algorithm was more accurate in running trajectory,and its absolute error was reduced by 21.4%on average.The research achieved three-dimensional point cloud acquisition of tall fescue crops and provided basic data for the subsequent analysis of phenotypic data.

关 键 词：温室 黄瓜植株 稠密建图 滤波处理 ORB-SLAM 3 

分 类 号：S642.2[农业科学—蔬菜学] TP391.41[农业科学—园艺学]