基于融合深度信息的自动喷雾车全局非线性轨迹优化方法
|
摘要
针对传统的基于深度信息的喷雾车轨迹优化方法存在定位精度差、浮点漂移、深度信息帧易丢失等问题,提出了一种融合深度信息的全局非线性轨迹优化方法。在喷雾车前进过程中使用Real Sense传感器实时获取连续彩色信息帧,提取并优化重叠区域的FAST特征点,计算BRIEF描述子,通过快速最近邻算法进行特征匹配,并使用Nanoflann算法加速特征匹配过程。在获取连续关键帧的匹配点对后,对特征点对进行校验,剔除误匹配点对,利用对极几何融合深度信息计算两相邻关键帧部分匹配点对的本质矩阵,并针对剩余匹配点对进行重投影获取重投影误差。统筹全局连续关键帧,综合所有关键帧中匹配点的重投影误差,构建图优化,并通过Dogleg算法多次迭代获取当前喷雾车的精确位姿。该方法避免了单一依赖深度信息估计喷雾车轨迹时,出现位姿估计误差较大和深度信息帧丢失导致无法定位的问题。采用本文算法估计的喷雾车行驶轨迹更加接近于真实轨迹,其偏离真实轨迹误差均值下降了1. 07 cm,方差下降了2. 14 cm,超调量降低了2. 13 cm,提高了车行驶轨迹的鲁棒性。
In the agricultural field spray application process,the traditional human spray,because of large amount of labor,toxic to human body,was gradually replaced by other spray methods. One of the most popular methods is the smart spray of mobile cars. For autonomous driving vehicles applied with intelligent variable spray,the detection and accurate positioning of feature points play an important role in autonomous driving of robots. Feature detection is equivalent to the eyes of the car to obtain plant information,road condition. Accurate positioning is equivalent to the brain of the car. After the car acquires color information and depth information,it finds its exact position and guides the car to drive independently. In the process of continuous development of the visual synchronous localization algorithm of self-propelled vehicle,the traditional path optimization based on the traditional filtering form has the phenomenon of poor positioning accuracy and floating point drift. For the stable running of the car,precise spray has a great impact. To solve this problem,a method of global nonlinear optimization with depth information was proposed. The RealSense camera was used to obtain continuous color and depth information frames in real time. Firstly,through the continuous color information frames obtained,the FAST feature points of the overlapped part were extracted,the scale invariance and rotation invariance were optimized,and the BRIEF description was calculated to obtain the feature description of two consecutive key frame repetition regions. Then,feature matching was performed by the nearest neighbor algorithm,and Nanoflann algorithm was used to accelerate the matching process. After obtaining the matching point pair of continuous key frames,the minimum distance method was used to screen the mismatched points,and the random sampling consistency method( RANSAC) based on the basic matrix was used to test the matching point pair. After eliminating the false match and obtaining the correct match point,PnP was used to calculate the pose change of continuous key frames,calculate the residual error,and build the incremental equation. Dogleg algorithm was used to estimate the pose of continuous key frames for multiple iterations and optimization to obtain the precise pose of spray car. At the same time,in the process of calculating the residual error iterative optimization,the bit-pose calculated by the RealSense acquisition depth information and the bit-pose calculated by the polar constraint solution were integrated into the iterative optimization. Compared with the single depth information correction mode,the algorithm effectively improved the positioning accuracy of the car. When the depth information collection was lost,the polar constraint compensated the process of vehicle posture estimation,and improved the robustness of accurate real-time acquisition of vehicle track.
In the agricultural field spray application process,the traditional human spray,because of large amount of labor,toxic to human body,was gradually replaced by other spray methods. One of the most popular methods is the smart spray of mobile cars. For autonomous driving vehicles applied with intelligent variable spray,the detection and accurate positioning of feature points play an important role in autonomous driving of robots. Feature detection is equivalent to the eyes of the car to obtain plant information,road condition. Accurate positioning is equivalent to the brain of the car. After the car acquires color information and depth information,it finds its exact position and guides the car to drive independently. In the process of continuous development of the visual synchronous localization algorithm of self-propelled vehicle,the traditional path optimization based on the traditional filtering form has the phenomenon of poor positioning accuracy and floating point drift. For the stable running of the car,precise spray has a great impact. To solve this problem,a method of global nonlinear optimization with depth information was proposed. The RealSense camera was used to obtain continuous color and depth information frames in real time. Firstly,through the continuous color information frames obtained,the FAST feature points of the overlapped part were extracted,the scale invariance and rotation invariance were optimized,and the BRIEF description was calculated to obtain the feature description of two consecutive key frame repetition regions. Then,feature matching was performed by the nearest neighbor algorithm,and Nanoflann algorithm was used to accelerate the matching process. After obtaining the matching point pair of continuous key frames,the minimum distance method was used to screen the mismatched points,and the random sampling consistency method( RANSAC) based on the basic matrix was used to test the matching point pair. After eliminating the false match and obtaining the correct match point,PnP was used to calculate the pose change of continuous key frames,calculate the residual error,and build the incremental equation. Dogleg algorithm was used to estimate the pose of continuous key frames for multiple iterations and optimization to obtain the precise pose of spray car. At the same time,in the process of calculating the residual error iterative optimization,the bit-pose calculated by the RealSense acquisition depth information and the bit-pose calculated by the polar constraint solution were integrated into the iterative optimization. Compared with the single depth information correction mode,the algorithm effectively improved the positioning accuracy of the car. When the depth information collection was lost,the polar constraint compensated the process of vehicle posture estimation,and improved the robustness of accurate real-time acquisition of vehicle track.
引文
[1]宋宇,刘永博,刘路,等.基于机器视觉的玉米根茎导航基准线提取方法[J/OL].农业机械学报,2017,48(2):38-44.SONG Yu,LIU Yongbo,LIU Lu,et al.Extraction method of navigation baseline of corn roots based on machine vision[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):38-44.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170205&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.02.005.(in Chinese)
[2]林桂潮,邹湘军,张青,等.基于主动轮廓模型的自动导引车视觉导航[J/OL].农业机械学报,2017,48(2):20-26.LIN Guichao,ZOU Xiangjun,ZHANG Qing,et al.Visual navigation for automatic guided vehicles based on active contour model[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):20-26.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170203&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.02.003.(in Chinese)
[3]高国琴,李明.基于K-means算法的温室移动机器人导航路径识别[J].农业工程学报,2014,30(7):25-33.GAO Guoqin,LI Ming.Navigating path recognition for greenhouse mobile robot based on K-means algorithm[J].Transactions of the CSAE,2014,30(7):25-33.(in Chinese)
[4]孟庆宽,张漫,仇瑞承,等.基于改进遗传算法的农机具视觉导航线检测[J/OL].农业机械学报,2014,45(10):39-46.MENG Qingkuan,ZHANG Man,QIU Ruicheng,et al.Navigation line detection for farm machinery based on improved genetic algorithm[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2014,45(10):39-46.http:∥www.jcsam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20141007&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2014.10.007.(in Chinese)
[5]王大帅,张俊雄,李伟,等.植保无人机动态变量施药系统设计与试验[J/OL].农业机械学报,2017,48(5):86-93.WANG Dashuai,ZHANG Junxiong,LI Wei,et al.Design and test of dynamic variable spraying system of plant protection UAV[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(5):86-93.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170510&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.05.010.(in Chinese)
[6]蒋焕煜,张利君,刘光远,等.基于PWM变量喷雾的单喷头动态雾量分布均匀性实验[J/OL].农业机械学报,2017,48(4):41-46.JIANG Huanyu,ZHANG Lijun,LIU Guangyuan,et al.Experiment on dynamic spray deposition uniformity for PWM variable spray of single nozzle[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(4):41-46.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170405&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.04.005.(in Chinese)
[7]黎永键,赵祚喜,黄培奎,等.基于DGPS与双闭环控制的拖拉机自动导航系统[J/OL].农业机械学报,2017,48(2):11-19.LI Yongjian,ZHAO Zuoxi,HUANG Peikui,et al.Automatic navigation system of tractor based on DGPS and double closedloop steering control[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):11-19.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170202&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.02.002.(in Chinese)
[8]薛金林,张顺顺.基于激光雷达的农业机器人导航控制研究[J/OL].农业机械学报,2014,45(9):55-60.XUE Jinlin,ZHANG Shunshun.Navigation of an agricultural robot based on laser radar[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2014,45(9):55-60.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20140909&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2014.09.009.(in Chinese)
[9]苏伟,赵晓凤,张明政,等.基于机载激光雷达点云的飞行障碍物提取方法研究[J/OL].农业机械学报,2017,48(增刊):79-85.SU Wei,ZHAO Xiaofeng,ZHANG Mingzheng,et al.Extracting flying obstacles using airborne Li DAR point cloud data[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(Supp.):79-85.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=2017s013&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.S0.013.(in Chinese)
[10]季宇寒,李寒,张漫,等.基于激光雷达的巡检机器人导航系统研究[J/OL].农业机械学报,2018,49(2):14-21.JI Yuhan,LI Han,ZHANG Man,et al.Navigation system for inspection robot based on Li DAR[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2018,49(2):14-21.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20180202&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2018.02.002.(in Chinese)
[11]SIADAT A,KASKE A,KLAUSMANN S,et al.An optimized segmentation method for a 2D laser-scanner applied to mobile robot navigation[J].IFAC Proceedings Volumes,1997,30(7):149-154.
[12]BORGES G A.A split-and-merge segmentation algorithm for line extraction in 2D range images[C]∥International Conference on Pattern Recognition,2000.Proceedings.IEEE,2000:441-444.
[13]武星,张颖,李林慧,等.复杂光照条件下视觉导引AGV路径提取方法[J/OL].农业机械学报,2017,48(10):15-24.WU Xing,ZHANG Ying,LI Linhui,et al.Path extraction method of vision-guided AGV under complex illumination conditions[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(10):15-24.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20171002&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.10.002.(in Chinese)
[14]武星,沈伟良,楼佩煌,等.视觉导引AGV鲁棒特征识别与精确路径跟踪研究[J/OL].农业机械学报,2016,47(7):48-56.WU Xing,SHEN Weiliang,LOU Peihuang,et al.Robust feature recognition and precise path tracking for vision-guided AGV[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(7):48-56.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20160708&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2016.07.008.(in Chinese)
[15]李盛辉,田光兆,姬长英,等.自主导航农业车辆的全景视觉多运动目标识别跟踪[J/OL].农业机械学报,2015,46(1):1-7.LI Shenghui,TIAN Guangzhao,JI Changying,et al.Multiple moving objects tracking based on panoramic vision for autonomous navigation of agricultural vehicle[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2015,46(1):1-7.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20150101&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2015.01.001.(in Chinese)
[16]田光兆,顾宝兴,IRSHAD A M,等.基于三目视觉的自主导航拖拉机行驶轨迹预测方法及试验[J].农业工程学报,2018,34(19):40-45.TIAN Guangzhao,GU Baoxing,IRSHAD A M,et al.Traveling trajectory prediction method and experiment of autonomous navigation tractor based on trinocular vision[J].Transactions of the CSAE,2018,34(19):40-45.(in Chinese)
[17]彭顺正,坎杂,李景彬.矮化密植枣园收获作业视觉导航路径提取[J].农业工程学报,2017,33(9):45-52.PENG Shunzheng,KAN Za,LI Jingbin.Extraction of visual navigation directrix for harvesting operation in short-stalked and close-planting jujube orchard[J].Transactions of the CSAE,2017,33(9):45-52.(in Chinese)
[18]白晓平,胡静涛,王卓.基于视觉伺服的联合收割机群协同导航从机定位方法[J].农业工程学报,2016,32(24):59-68.BAI Xiaoping,HU Jingtao,WANG Zhuo.Slave positioning method for cooperative navigation of combine harvester group based on visual servo[J].Transactions of the CSAE,2016,32(24):59-68.(in Chinese)
[19]GEOVANY A B,MARIE-JOSE A.Line extraction in 2D range images for mobile robotics[J].Journal of Intelligent and Robotic Systems,2004,40(3):267-297.
[20]张美娜,尹文庆,林相泽,等.RTK-DGPS融合惯性传感器的车辆导航参数计算方法[J/OL].农业机械学报,2015,46(5):7-12.ZHANG Meina,YIN Wenqing,LIN Xiangze,et al.Method for calculating navigation parameters via RTK-DGPS fusing inertial sensor for agricultural vehicle[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2015,46(5):7-12.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20150502&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2015.05.002.(in Chinese)
[21]钱晓明,张浩,王晓勇,等.基于激光扫描匹配的移动机器人相对定位技术研究[J/OL].农业机械学报,2016,47(3):14-21.QIAN Xiaoming,ZHANG Hao,WANG Xiaoyong,et al.Relative localization technology for mobile robot based on laser scan matching[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(3):14-21.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20160303&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2016.03.003.(in Chinese)
[22]江锽.基于Kinect的温室喷雾机器人视觉导航定位系统的研究[D].北京:北京林业大学,2015.JIANG Huang.Research on the vision navigation and positioning system of greenhouse spray robot based on Kinect[D].Beijing:Beijing Forestry University,2015.(in Chinese)
[23]YANG K,WANG K,CHEN H,et al.Reducing the minimum range of a RGB-depth sensor to aid navigation in visually impaired individuals[J].Appl.Opt.,2018,57(11):2809-2819.
[24]KESELMAN L,WOODFILL J I,GRUNNET-JEPSEN A,et al.Intel Real Sense stereoscopic depth cameras[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops,2017:1-10.
[25]沈跃,朱嘉慧,刘慧,等.基于深度和彩色双信息特征源的Kinect植物图像拼接[J].农业工程学报,2018,34(5):176-182.SHEN Yue,ZHU Jiahui,LIU Hui,et al.Image mosaic based on depth and color dual information feature source from Kinect[J].Transactions of the CSAE,2018,34(5):176-182.(in Chinese)
[26]NAIN N,LAXMI V,BHADVIYIA B,et al.Fast feature point detector[C]∥IEEE International Conference on Signal Image Technology and Internet Based Systems.IEEE,2008:301-306.
[27]XIAN-FENGA X U,TAN J Q.An improved multi-scale Harris feature point detection method[J].Computer Engineering,2012,38(17):174-177.
[28]CALONDER M,LEPETIT V,STRECHA C,et al.BRIEF:binary robust independent elementary features[C]∥ECCV European Conference on Computer Vision,Heraklion,Crete,Greece,2010.
[29]冯亦东,孙跃.基于SURF特征提取和FLANN搜索的图像匹配算法[J].图学学报,2015,36(4):650-654.FENG Yidong,SUN Yue.Image matching algorithm based on SURF feature extraction and FLANN search[J].Journal of Graphics,2015,36(4):650-654.(in Chinese)
[30]沈跃,潘成凯,刘慧,等.基于改进SIFF-ICP算法的Kinect植株点云配准方法[J/OL].农业机械学报,2017,48(12):183-189.SHEN Yue,PAN Chengkai,LIU Hui,et al.Method of plant point cloud registration based on Kinect of improved SIFT-ICP[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(12):183-189.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20171221&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.12.021.(in Chinese)
[31]赵红蕊,陆胜寒.基于特征尺度分布与对极几何约束的高清影像快速密集匹配方法[J].测绘学报,2018,47(6):104-112.ZHAO Hongrui,LU Shenghan.A fast dense matching method for high-definition images based on feature scale distribution and polar geometric constraints[J].Journal of Surveying and Mapping,2018,47(6):104-112.(in Chinese)
[32]颜坤,刘恩海,赵汝进,等.快速鲁棒的基础矩阵估计[J].光学精密工程,2018,26(2):461-470.YAN Kun,LIU Enhai,ZHAO Rujin,et al.A fast and robust method for fundamental matrix estimation[J].Optics and Precision Engineering,2018,26(2):461-470.(in Chinese)
[33]王新忠,韩旭,毛罕平,等.基于最小二乘法的温室番茄垄间视觉导航路径检测[J/OL].农业机械学报,2012,43(6):161-166.WANG Xinzhong,HAN Xu,MAO Hanping,et al.Navigation line detection of tomato ridges in greenhouse based on least square method[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2012,43(6):161-166.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20120629&journal_id=jcsam DOI:10.6041/j.issn.1000-1298.2012.06.029.(in Chinese)
[34]XIN G X,ZHANG X T,WANG X,et al.A RGBD SLAM algorithm combining ORB with PROSAC for indoor mobile robot[C]∥International Conference on Computer Science and Network Technology.IEEE,2016:71-74.
[2]林桂潮,邹湘军,张青,等.基于主动轮廓模型的自动导引车视觉导航[J/OL].农业机械学报,2017,48(2):20-26.LIN Guichao,ZOU Xiangjun,ZHANG Qing,et al.Visual navigation for automatic guided vehicles based on active contour model[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):20-26.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170203&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.02.003.(in Chinese)
[3]高国琴,李明.基于K-means算法的温室移动机器人导航路径识别[J].农业工程学报,2014,30(7):25-33.GAO Guoqin,LI Ming.Navigating path recognition for greenhouse mobile robot based on K-means algorithm[J].Transactions of the CSAE,2014,30(7):25-33.(in Chinese)
[4]孟庆宽,张漫,仇瑞承,等.基于改进遗传算法的农机具视觉导航线检测[J/OL].农业机械学报,2014,45(10):39-46.MENG Qingkuan,ZHANG Man,QIU Ruicheng,et al.Navigation line detection for farm machinery based on improved genetic algorithm[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2014,45(10):39-46.http:∥www.jcsam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20141007&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2014.10.007.(in Chinese)
[5]王大帅,张俊雄,李伟,等.植保无人机动态变量施药系统设计与试验[J/OL].农业机械学报,2017,48(5):86-93.WANG Dashuai,ZHANG Junxiong,LI Wei,et al.Design and test of dynamic variable spraying system of plant protection UAV[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(5):86-93.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170510&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.05.010.(in Chinese)
[6]蒋焕煜,张利君,刘光远,等.基于PWM变量喷雾的单喷头动态雾量分布均匀性实验[J/OL].农业机械学报,2017,48(4):41-46.JIANG Huanyu,ZHANG Lijun,LIU Guangyuan,et al.Experiment on dynamic spray deposition uniformity for PWM variable spray of single nozzle[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(4):41-46.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170405&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.04.005.(in Chinese)
[7]黎永键,赵祚喜,黄培奎,等.基于DGPS与双闭环控制的拖拉机自动导航系统[J/OL].农业机械学报,2017,48(2):11-19.LI Yongjian,ZHAO Zuoxi,HUANG Peikui,et al.Automatic navigation system of tractor based on DGPS and double closedloop steering control[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):11-19.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20170202&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.02.002.(in Chinese)
[8]薛金林,张顺顺.基于激光雷达的农业机器人导航控制研究[J/OL].农业机械学报,2014,45(9):55-60.XUE Jinlin,ZHANG Shunshun.Navigation of an agricultural robot based on laser radar[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2014,45(9):55-60.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20140909&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2014.09.009.(in Chinese)
[9]苏伟,赵晓凤,张明政,等.基于机载激光雷达点云的飞行障碍物提取方法研究[J/OL].农业机械学报,2017,48(增刊):79-85.SU Wei,ZHAO Xiaofeng,ZHANG Mingzheng,et al.Extracting flying obstacles using airborne Li DAR point cloud data[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(Supp.):79-85.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=2017s013&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.S0.013.(in Chinese)
[10]季宇寒,李寒,张漫,等.基于激光雷达的巡检机器人导航系统研究[J/OL].农业机械学报,2018,49(2):14-21.JI Yuhan,LI Han,ZHANG Man,et al.Navigation system for inspection robot based on Li DAR[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2018,49(2):14-21.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20180202&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2018.02.002.(in Chinese)
[11]SIADAT A,KASKE A,KLAUSMANN S,et al.An optimized segmentation method for a 2D laser-scanner applied to mobile robot navigation[J].IFAC Proceedings Volumes,1997,30(7):149-154.
[12]BORGES G A.A split-and-merge segmentation algorithm for line extraction in 2D range images[C]∥International Conference on Pattern Recognition,2000.Proceedings.IEEE,2000:441-444.
[13]武星,张颖,李林慧,等.复杂光照条件下视觉导引AGV路径提取方法[J/OL].农业机械学报,2017,48(10):15-24.WU Xing,ZHANG Ying,LI Linhui,et al.Path extraction method of vision-guided AGV under complex illumination conditions[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(10):15-24.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20171002&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.10.002.(in Chinese)
[14]武星,沈伟良,楼佩煌,等.视觉导引AGV鲁棒特征识别与精确路径跟踪研究[J/OL].农业机械学报,2016,47(7):48-56.WU Xing,SHEN Weiliang,LOU Peihuang,et al.Robust feature recognition and precise path tracking for vision-guided AGV[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(7):48-56.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20160708&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2016.07.008.(in Chinese)
[15]李盛辉,田光兆,姬长英,等.自主导航农业车辆的全景视觉多运动目标识别跟踪[J/OL].农业机械学报,2015,46(1):1-7.LI Shenghui,TIAN Guangzhao,JI Changying,et al.Multiple moving objects tracking based on panoramic vision for autonomous navigation of agricultural vehicle[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2015,46(1):1-7.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20150101&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2015.01.001.(in Chinese)
[16]田光兆,顾宝兴,IRSHAD A M,等.基于三目视觉的自主导航拖拉机行驶轨迹预测方法及试验[J].农业工程学报,2018,34(19):40-45.TIAN Guangzhao,GU Baoxing,IRSHAD A M,et al.Traveling trajectory prediction method and experiment of autonomous navigation tractor based on trinocular vision[J].Transactions of the CSAE,2018,34(19):40-45.(in Chinese)
[17]彭顺正,坎杂,李景彬.矮化密植枣园收获作业视觉导航路径提取[J].农业工程学报,2017,33(9):45-52.PENG Shunzheng,KAN Za,LI Jingbin.Extraction of visual navigation directrix for harvesting operation in short-stalked and close-planting jujube orchard[J].Transactions of the CSAE,2017,33(9):45-52.(in Chinese)
[18]白晓平,胡静涛,王卓.基于视觉伺服的联合收割机群协同导航从机定位方法[J].农业工程学报,2016,32(24):59-68.BAI Xiaoping,HU Jingtao,WANG Zhuo.Slave positioning method for cooperative navigation of combine harvester group based on visual servo[J].Transactions of the CSAE,2016,32(24):59-68.(in Chinese)
[19]GEOVANY A B,MARIE-JOSE A.Line extraction in 2D range images for mobile robotics[J].Journal of Intelligent and Robotic Systems,2004,40(3):267-297.
[20]张美娜,尹文庆,林相泽,等.RTK-DGPS融合惯性传感器的车辆导航参数计算方法[J/OL].农业机械学报,2015,46(5):7-12.ZHANG Meina,YIN Wenqing,LIN Xiangze,et al.Method for calculating navigation parameters via RTK-DGPS fusing inertial sensor for agricultural vehicle[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2015,46(5):7-12.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20150502&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2015.05.002.(in Chinese)
[21]钱晓明,张浩,王晓勇,等.基于激光扫描匹配的移动机器人相对定位技术研究[J/OL].农业机械学报,2016,47(3):14-21.QIAN Xiaoming,ZHANG Hao,WANG Xiaoyong,et al.Relative localization technology for mobile robot based on laser scan matching[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(3):14-21.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20160303&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2016.03.003.(in Chinese)
[22]江锽.基于Kinect的温室喷雾机器人视觉导航定位系统的研究[D].北京:北京林业大学,2015.JIANG Huang.Research on the vision navigation and positioning system of greenhouse spray robot based on Kinect[D].Beijing:Beijing Forestry University,2015.(in Chinese)
[23]YANG K,WANG K,CHEN H,et al.Reducing the minimum range of a RGB-depth sensor to aid navigation in visually impaired individuals[J].Appl.Opt.,2018,57(11):2809-2819.
[24]KESELMAN L,WOODFILL J I,GRUNNET-JEPSEN A,et al.Intel Real Sense stereoscopic depth cameras[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops,2017:1-10.
[25]沈跃,朱嘉慧,刘慧,等.基于深度和彩色双信息特征源的Kinect植物图像拼接[J].农业工程学报,2018,34(5):176-182.SHEN Yue,ZHU Jiahui,LIU Hui,et al.Image mosaic based on depth and color dual information feature source from Kinect[J].Transactions of the CSAE,2018,34(5):176-182.(in Chinese)
[26]NAIN N,LAXMI V,BHADVIYIA B,et al.Fast feature point detector[C]∥IEEE International Conference on Signal Image Technology and Internet Based Systems.IEEE,2008:301-306.
[27]XIAN-FENGA X U,TAN J Q.An improved multi-scale Harris feature point detection method[J].Computer Engineering,2012,38(17):174-177.
[28]CALONDER M,LEPETIT V,STRECHA C,et al.BRIEF:binary robust independent elementary features[C]∥ECCV European Conference on Computer Vision,Heraklion,Crete,Greece,2010.
[29]冯亦东,孙跃.基于SURF特征提取和FLANN搜索的图像匹配算法[J].图学学报,2015,36(4):650-654.FENG Yidong,SUN Yue.Image matching algorithm based on SURF feature extraction and FLANN search[J].Journal of Graphics,2015,36(4):650-654.(in Chinese)
[30]沈跃,潘成凯,刘慧,等.基于改进SIFF-ICP算法的Kinect植株点云配准方法[J/OL].农业机械学报,2017,48(12):183-189.SHEN Yue,PAN Chengkai,LIU Hui,et al.Method of plant point cloud registration based on Kinect of improved SIFT-ICP[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(12):183-189.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20171221&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.12.021.(in Chinese)
[31]赵红蕊,陆胜寒.基于特征尺度分布与对极几何约束的高清影像快速密集匹配方法[J].测绘学报,2018,47(6):104-112.ZHAO Hongrui,LU Shenghan.A fast dense matching method for high-definition images based on feature scale distribution and polar geometric constraints[J].Journal of Surveying and Mapping,2018,47(6):104-112.(in Chinese)
[32]颜坤,刘恩海,赵汝进,等.快速鲁棒的基础矩阵估计[J].光学精密工程,2018,26(2):461-470.YAN Kun,LIU Enhai,ZHAO Rujin,et al.A fast and robust method for fundamental matrix estimation[J].Optics and Precision Engineering,2018,26(2):461-470.(in Chinese)
[33]王新忠,韩旭,毛罕平,等.基于最小二乘法的温室番茄垄间视觉导航路径检测[J/OL].农业机械学报,2012,43(6):161-166.WANG Xinzhong,HAN Xu,MAO Hanping,et al.Navigation line detection of tomato ridges in greenhouse based on least square method[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2012,43(6):161-166.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?flag=1&file_no=20120629&journal_id=jcsam DOI:10.6041/j.issn.1000-1298.2012.06.029.(in Chinese)
[34]XIN G X,ZHANG X T,WANG X,et al.A RGBD SLAM algorithm combining ORB with PROSAC for indoor mobile robot[C]∥International Conference on Computer Science and Network Technology.IEEE,2016:71-74.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |