基于视觉导航的果园机器人控制系统的研究与设计
|
摘要
近年来,机器人技术和视觉导航技术发展迅速,在农业领域中的拓展得到了广泛的关注。对农用视觉导航机器人技术进行研究与应用,不仅能够克服农业环境中的作业困难,降低劳动强度,提高经济效益,而且对加快农业的现代化进程有着现实意义。本研究在“863”项目(2008AA100903-7)资助下,以研制的新型履带式果园微耕机为对象,研究并设计了一套基于视觉导航的果园机器人控制系统。主要工作包括:
(1)果园机器人控制系统的整体分析与设计。模块化地提出了果园机器人控制系统的体系结构并设计了其总体框架,将系统分为视觉子系统和运动控制子系统两个模块,对各子系统模块硬件进行选用与设计;
(2)视觉子系统的设计。视觉子系统采用单目摄像头,经实验结果比较,选择基于OpenCV的改进两步法作为视觉子系统的标定方法,并深入地分析了果园机器人与导航路径的位置关系,推导出导航路径与预执行任务参数间的转换方程。采用高性能的TMS320DM642芯片作为处理的核心,根据两种规范化果园环境中的道路图像特点,详细地分析与设计了相适应的图像处理算法,并提出了基于两点法和预限制双边Hough变换法的中心线导航路径提取算法,分析了算法的稳定性和实时性;
(3)运动控制子系统的设计。在运动控制子系统中,采用模糊控制法将导航路径参数(横向偏差和航向偏角)信息转换成相应的液压系统控制信号。使用MATLAB软件设计模糊控制器,并建立模糊控制系统模型,在SIMULINK环境中对模糊控制系统进行仿真,结果表明所设计的模糊控制器鲁棒强,准确性高,具有良好的控制效果,满足了设计需要;
(4)果园机器人控制系统的软件实现。果园机器人控制系统的软件设计包括以DM642为处理核心的视觉子系统软件和以单片机AT89S52为控制核心的运动控制子系统软件两部分,对各部分中根据功能划分的子模块算法进行了详细的分析与设计,并给出了部分设计的程序。
In recent years, the robot technology and visual navigation have developed rapidly, and its expansion in the agricultural field receives widespread concern. The research and application on the agricultural utility robot technology not only can solve the operational difficulties in the agricultural environment and reduce the labor intensity, but also suit the market demand, increase economic efficiency and has realistic meaning to accelerate the agricultural modernization. This paper is supported by the“863”project (2008AA100903-7) and its studying object is the new developed crawler orchard farming micro-machine. The paper researched and designed an orchard robot control system based on visual navigation. The main research work as followed:
(1) Overall design and analysis of orchard robot control system. Firstly, proposing the orchard robot platform architecture and design the overall frame of control system hierarchically and modularly. Then, dividing the robot control system into vision subsystem and motion control subsystem, and designing the hardware and selecting components.
(2) The design of vision subsystem. The vision subsystem has one single camera. The improved two-step calibration method based on OpenCV was chosen after experimental results compare of two methods. Based on analyzing in depth the position relationship between the orchard machine moving route and navigational path, the conversional equations of image information in the farming environment and planed mission parameters was derived. According the image features of the two standardized orchard road environment the article chosen, the images processing algorithm and the navigating center line extracted algorithm were analyzed and designed in detail with using the high-performance processing core of TMS320DM642.The extracting methods of navigation path based on two points and pre-limited bilateral Hough transform were proposed, and analyzed by stability and real-time.
(3) The design of motion control subsystem. The motion control system uses the fuzzy control method to convert the lateral deciation and heading angle obtained by vision subsystem to the corresponded control signal of hydraulic system. The fuzzy controller and modeling of fuzzy control system were researched and designed detailed by using the software of MATLAB. Finally, fuzzy control system was simulated in the simulation environment of SIMULINK. The result shows that the fuzzy controller run with strong robust, response with high accuracy, has good control effect and meets the basic design request.
(4) Software implementation of the orchard robot control system. The whole control system of the orchard robot was divided into the vision subsystem software which the control core was DM642 and the motion control system which the control core was AT89S52.Then, all the parts that were divided according to the functions of each subsystem were analyzed and designed detailed, and a part of procedures was given.
(1)果园机器人控制系统的整体分析与设计。模块化地提出了果园机器人控制系统的体系结构并设计了其总体框架,将系统分为视觉子系统和运动控制子系统两个模块,对各子系统模块硬件进行选用与设计;
(2)视觉子系统的设计。视觉子系统采用单目摄像头,经实验结果比较,选择基于OpenCV的改进两步法作为视觉子系统的标定方法,并深入地分析了果园机器人与导航路径的位置关系,推导出导航路径与预执行任务参数间的转换方程。采用高性能的TMS320DM642芯片作为处理的核心,根据两种规范化果园环境中的道路图像特点,详细地分析与设计了相适应的图像处理算法,并提出了基于两点法和预限制双边Hough变换法的中心线导航路径提取算法,分析了算法的稳定性和实时性;
(3)运动控制子系统的设计。在运动控制子系统中,采用模糊控制法将导航路径参数(横向偏差和航向偏角)信息转换成相应的液压系统控制信号。使用MATLAB软件设计模糊控制器,并建立模糊控制系统模型,在SIMULINK环境中对模糊控制系统进行仿真,结果表明所设计的模糊控制器鲁棒强,准确性高,具有良好的控制效果,满足了设计需要;
(4)果园机器人控制系统的软件实现。果园机器人控制系统的软件设计包括以DM642为处理核心的视觉子系统软件和以单片机AT89S52为控制核心的运动控制子系统软件两部分,对各部分中根据功能划分的子模块算法进行了详细的分析与设计,并给出了部分设计的程序。
In recent years, the robot technology and visual navigation have developed rapidly, and its expansion in the agricultural field receives widespread concern. The research and application on the agricultural utility robot technology not only can solve the operational difficulties in the agricultural environment and reduce the labor intensity, but also suit the market demand, increase economic efficiency and has realistic meaning to accelerate the agricultural modernization. This paper is supported by the“863”project (2008AA100903-7) and its studying object is the new developed crawler orchard farming micro-machine. The paper researched and designed an orchard robot control system based on visual navigation. The main research work as followed:
(1) Overall design and analysis of orchard robot control system. Firstly, proposing the orchard robot platform architecture and design the overall frame of control system hierarchically and modularly. Then, dividing the robot control system into vision subsystem and motion control subsystem, and designing the hardware and selecting components.
(2) The design of vision subsystem. The vision subsystem has one single camera. The improved two-step calibration method based on OpenCV was chosen after experimental results compare of two methods. Based on analyzing in depth the position relationship between the orchard machine moving route and navigational path, the conversional equations of image information in the farming environment and planed mission parameters was derived. According the image features of the two standardized orchard road environment the article chosen, the images processing algorithm and the navigating center line extracted algorithm were analyzed and designed in detail with using the high-performance processing core of TMS320DM642.The extracting methods of navigation path based on two points and pre-limited bilateral Hough transform were proposed, and analyzed by stability and real-time.
(3) The design of motion control subsystem. The motion control system uses the fuzzy control method to convert the lateral deciation and heading angle obtained by vision subsystem to the corresponded control signal of hydraulic system. The fuzzy controller and modeling of fuzzy control system were researched and designed detailed by using the software of MATLAB. Finally, fuzzy control system was simulated in the simulation environment of SIMULINK. The result shows that the fuzzy controller run with strong robust, response with high accuracy, has good control effect and meets the basic design request.
(4) Software implementation of the orchard robot control system. The whole control system of the orchard robot was divided into the vision subsystem software which the control core was DM642 and the motion control system which the control core was AT89S52.Then, all the parts that were divided according to the functions of each subsystem were analyzed and designed detailed, and a part of procedures was given.
引文
柏晓颖.2007.户外自主移动机器人体系结构与控制系统研究概况.装备制造技术,12:93~96
蔡自兴.机器人学.2000.北京:清华大学出版社
蔡自兴,贺汉根,陈虹.2002.未知环境中移动机器人导航控制研究的若干问题.控制与决策,17(4):385~390
陈玉,王宗和,张旭东.2008.TMS320系列DSP硬件开发系统.北京:清华大学出版社
丁丽娟,程杞元.2006.数值计算方法.北京:北京理工大学出版社
丁学恭.2006.机器人控制研究.杭州:浙江大学出版社
尔桂花,窦曰轩.2002.北京:清华大学出版社:395~412
樊长虹,卢有章,刘宏,黄上腾.2004.基于神经网络的移动机器人路径规划.计算机工程与应用,8:86~89
费业泰.2004.误差理论与数据处理.北京:机械工业出版社
郭天祥.2009.51单片机C语言教程.北京:电子工业出版社
韩峻峰,李玉惠.2003.模糊控制技术.重庆:重庆大学出版社
贾云得.2000.机器视觉.北京:科学出版社
江贵龙,金祥克,胡旭东.2006.基于模糊算法的移动机器人导航.机电工程,23(2):53~57
姜国权,柯杏,杜尚丰.2008.基于机器视觉和随机方法的作物行提取算法.农业机械学报, 39(11):85~88,93
李佳宁,易建强.2003.移动机器人体系结构研究进展.机器人,25(7):756~760
李猛,戈景刚,边丽,王泽河,王家忠.2008.面向果林的一款农用喷雾机器人的创新设计.农机化研究,5:105~108
李士勇.1998.模糊控制和智能控制理论于应用.哈尔滨:哈尔滨工业大学出版社
李鹏,王军宁.2007.摄像机标定方法综述.山西电子技术,4:77~79
李真芳,苏涛,黄小宇.2003.DSP程序开发.西安:西安电子科技大学出版社
李志红,包长春,李锦泽,侯桂凤,伦翠芬.2008.我国微型耕作机发展状况的研究.农机化研究,(9):215~216
刘华军,杨静宇,陆建峰.2006.移动机器人运动规划研究综述.中国工程科学,8(1):85~92
罗锡文,区颖刚,赵祚喜,赵新,张智刚,张志,卢广宇,李俊玲.2005.农用智能移动作业平台模型的研制.农业工程学报,21(2):83~85
马颂德,张正友.1997.计算机视觉---计算理论与算法基础.北京:科学出版社
倪小雷,卜佳俊.2006.自主移动机器人混合式体系结构的设计与实现.计算机测量与控制,14(11):1526~1528
庞晓宇.2008.移动机器人视觉导航系统的研究.[硕士学位论文].西安:西安理工大学
师黎,陈铁军,李晓媛,姚丽娜.2009.智能控制理论与应用.北京:清华大学出版社
孙庚山,兰西贵.1995.工程模糊控制.北京:机械工业出版社
孙继祥.2009.图像处理.北京:科学出版社:147~196
孙元义,张绍磊,李伟.2007.棉田喷药农业机器人的导航路径识别.清华大学学报(自然科学版),47(2):206~209
王红波.2008.移动机器人视觉导航系统研究[硕士学位论文].北京:北京交通大学,28~41,80~84,93~98
王金政,薛晓敏,路超.2010.我国苹果生产现状与发展对策.山东农业科学,(6):117~119
王跃宗,刘京会.2009.TMS320DM642 DSP应用系统设计与开发.北京:人民邮政出版社
魏晓云,陈杰,曾云.2003.DSP技术的最新发展及其应用现状.半导体技术,28(9):18~21
吴东辉,叶秀清,顾伟康.2002.基于不确定性知识的实时道路场景理解.中国图像图形学报,7(1):69~74
吴福朝,李华,胡占义.2001.基于主动视觉子系统的摄像机自标定方法研究.自动化学报,27(6):231~234
吴佳艺,杨庆华,鲍官军,高峰.2009.基于机器视觉的林间导航路径生成算法.农业机械学报,40(70:176~179
伍雪冬,蒋新华,李建兴.2007.计算机视觉传统摄像机定标方法综述.福建工程学院学报,2:57~60
西北农林科技大学.2010-12-28.农业机械远程实时监控系统.中国发明专利,201020189270.9
邢春贵,何熙文.2004.模糊控制系统的MATLAB仿真与应用.微处理机,(1):34~36
杨庆华,吴佳艺,鲍官军,高峰.2009.农林环境机器视觉导航路径生成算法及应用.农业机械学报,40(3):148~151
杨为民,李天石,贾鸿社.2004.农业机械机器视觉导航研究.农业工程学报,20(1):160~165
有马,门田,难波,吉田,近藤.2003.草莓培养采摘高定机器人(第2报).植物工场学会志,15(3):162~168
于国英,毛罕平.2007.农业智能车辆视觉导航参数提取的研究.农机化研究,(1):167~169
张广军.2005.机器视觉.北京:科学出版社
张荣辉,卢永强.2008-01-23.遥控微耕机.中国实用新型专利,200720004287
张毅,罗元,郑太雄.2007.移动机器人技术及其应用.北京:电子工业出版社:37~50
章毓晋.1999.图像工程.北京:清华大学出版社
张志斌,罗锡文,李庆,王在满,赵祚喜.2007.基于良序集和垄行结构的农机视觉导航参数提取算法.农业工程学报,23(7):122~126
赵颖,陈兵旗,王书茂.2006.基于机器视觉的耕作机器人行走目标直线检测.农业机械学报,37(4):83~86
郑丽娜.2005.视觉导航道路识别系统中图像特征直线提取方法研究.[硕士学位论文].长春:吉林大学
支勇平.2009.我国苹果栽培制度将大改革.北京农业,(4):25
中国果品流通协会.2011.我国水果产业发展状况及柑橘产销形势分析.果农之友,(1):3~5
中科院自动化所自由软件协会. 2001.Intel Corporation Open Source Computer Vision Library Reference Manual.http://www.opencv.org.cn/[2010.06.05]
周俊.2003.农用轮式移动机器人视觉导航系统的研究.[博士学位论文].南京:南京农业大学
周俊,姬长英,刘成良.2005.农用轮式移动机器人视觉导航系统.农业机械学报,36(3):90~94
庄慧忠,杜树新,吴铁军.2004.机器人路径规划及相关算法研究.科技通报,20(3):210~215
村上,大塚,井上,杉田.1999.甘蓝采摘机器人(第1报):机器人的运行速度.农业机械学会志, 61(5):85~92
村上,大塚,井上,杉田.1999.甘蓝采摘机器人(第2报):摘取实验.农业机械学会志,61(5):93-100
高木干雄,下田阳久.2004.孙卫东等译.2007.北京:科学出版社
日本机器人学会.2005.机器人技术手册.宗光华,程军实译.2007.北京:科学出版社
Alexander M Meystel,James S Albus. 2005.智能系统结构设计与控制.冯祖仁,李人厚译.北京:电子工业出版社
Automation Technology for Off-road Equipment.ATOE ,2004:369~373
Brooks R A.1986.A robust layered control system for a mobile robot.IEEE journal of Robot and Automation,RA-2(1):14
Courbon J, Mezouar Y, Martinet P. 2008. Indoor navigation of a non-holonomic mobile robot using a visual memory. AUTONOMOUS ROBOTS,25(3):253~266
EYRE J,BIER J.2000.The evolution of DSP processors from early architectures to the latest development.IEEE Signal Processing Magazine,17(2):43~51
Gary Bradski,Adrian Kaebler.2009.学习OpenCV(中文版).于仕琪,刘瑞祯译.北京:清华大学出版社
Hamner Bradley,Singh Sanjiv,Bergerman Marcel.2010.Improve Orchard Efficiency with Autonomous Utility Vehicles. American Society of Agricultural and Biological Engineers Annual International Meeting,6:4670~4685
Hamrita T K, Tollner E W, Schafer R L, Driftmier Eng.2000. Toward fulfilling the robotic farming vision: advances in sensors and controllers for agricultural applications.Industry Applications,IEEE Transactions on,4(36):1026~1032
John F Reid,Stephen W. 1987.Searcy Vision-Based Guidance of an Agricultural Tractor.IEEE:39~43
Mario M Foglia,Giulio Renina.2006.Agricultural robot for radicchio harvesting.Journal of Field Robotics,23(6-7):363~377
Marr David.1998.视觉计算理论.姚国正等译.北京:科学出版社
Nelson H C,Yung Cang Ye.1999.An Intelligent Mobile Vehicle Navigator Based on Fuzzy Logic and Reinforcement Learning.IEEE Trans on Sys Man and Cybern.PartB:Cybernetics, 29(2):314~321
Nisson N J.1999.Artificial Intelligence:A New Synthesis.北京:机械工业出版社
Pintol F A C,Reid J F,Zhang Q.2000.Vehicle Guidance Parameter Determination from Crop Row Images using Principal Component Analysis.J.agric.Engng Res,75:257~264
Poynton C A.1996.A Technical Introduction to Digital Video,WILEY,NY
Rafael C Gonzalez,Richard E Woods,Steven L Eddins.2004.Digital Image Processing Using MATLAB.第二版.阮秋琦译.数字图像处理.2005.北京:电子工业出版社
Robin R Murphy.杜军平,吴立成,胡金春译.2004.人工智能机器人学导论.北京:电子工业出版社
Rongben Wang,Youchun Xu,Libin.2002.A vision-based road edge detection algorithm. Intelligent Vehicle Symposium,IEEE,(1):141~147
Ryo Tsubota,Noboru Noguchi,Akira Mizushima.2004.Automatic Guidance with a Laser Scanner for a
Robot Tractor in an Orchard.Proceedings of the International Conference on Siegwart R,Nourbakhsh I R.
李仁厚译.2006.自主移动机器人导论.西安:西安交通大学出版社
Sonka M,Hlavac V,Boyle R.2002.Image processing analysis and machine vision.北京:人民邮电出版社
Topi M,Markus Turtinen,Matti Pietik.2003.Real-time surface inspection by texture. System Real-time Imaging,9:289~296
Tsai R Y.1987.A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses.IEEE Journal of Rbobotics and Automation,3(4):323~343
Vezhneves Vladimir aka Dead Moroz.2005.OpenCV and Matlab camera calibration toolboxes enhancement.http://graphics.cs.msu.su/en/research/calibration/[2010-06-05]
Wang Jianhua, Shi Fanhuai.2008.A new calibration model of camera lens distortion.Pattern Rencognition,(41):607~615
Wang Z S,Wu W,Xu X H.2007.Recognition and location of the internal corners of planar checkboard calibration pattern image.Appl Mathe Comput,2:894~906
Weng Juyang,Paul Cohen.1992.Camera Calibration with Distortion Models and Accuracy Evaluation. IEEE Tracnsactions on Pattern Analysis and Machine Intelligence,14(10): 965~982
Zhang Zhengyou.2000.A flexible new technique for camera calibration.IEEE Transactions on Pattern Analysis and Machine Intelligence,22(11):1330~1334
Zhang Zhengyou.2004.Camera Calibration with One-Dimensional Objects.IEEE Transactions on Pattern Analysis and Machine Intelligence,(7):161~174
蔡自兴.机器人学.2000.北京:清华大学出版社
蔡自兴,贺汉根,陈虹.2002.未知环境中移动机器人导航控制研究的若干问题.控制与决策,17(4):385~390
陈玉,王宗和,张旭东.2008.TMS320系列DSP硬件开发系统.北京:清华大学出版社
丁丽娟,程杞元.2006.数值计算方法.北京:北京理工大学出版社
丁学恭.2006.机器人控制研究.杭州:浙江大学出版社
尔桂花,窦曰轩.2002.北京:清华大学出版社:395~412
樊长虹,卢有章,刘宏,黄上腾.2004.基于神经网络的移动机器人路径规划.计算机工程与应用,8:86~89
费业泰.2004.误差理论与数据处理.北京:机械工业出版社
郭天祥.2009.51单片机C语言教程.北京:电子工业出版社
韩峻峰,李玉惠.2003.模糊控制技术.重庆:重庆大学出版社
贾云得.2000.机器视觉.北京:科学出版社
江贵龙,金祥克,胡旭东.2006.基于模糊算法的移动机器人导航.机电工程,23(2):53~57
姜国权,柯杏,杜尚丰.2008.基于机器视觉和随机方法的作物行提取算法.农业机械学报, 39(11):85~88,93
李佳宁,易建强.2003.移动机器人体系结构研究进展.机器人,25(7):756~760
李猛,戈景刚,边丽,王泽河,王家忠.2008.面向果林的一款农用喷雾机器人的创新设计.农机化研究,5:105~108
李士勇.1998.模糊控制和智能控制理论于应用.哈尔滨:哈尔滨工业大学出版社
李鹏,王军宁.2007.摄像机标定方法综述.山西电子技术,4:77~79
李真芳,苏涛,黄小宇.2003.DSP程序开发.西安:西安电子科技大学出版社
李志红,包长春,李锦泽,侯桂凤,伦翠芬.2008.我国微型耕作机发展状况的研究.农机化研究,(9):215~216
刘华军,杨静宇,陆建峰.2006.移动机器人运动规划研究综述.中国工程科学,8(1):85~92
罗锡文,区颖刚,赵祚喜,赵新,张智刚,张志,卢广宇,李俊玲.2005.农用智能移动作业平台模型的研制.农业工程学报,21(2):83~85
马颂德,张正友.1997.计算机视觉---计算理论与算法基础.北京:科学出版社
倪小雷,卜佳俊.2006.自主移动机器人混合式体系结构的设计与实现.计算机测量与控制,14(11):1526~1528
庞晓宇.2008.移动机器人视觉导航系统的研究.[硕士学位论文].西安:西安理工大学
师黎,陈铁军,李晓媛,姚丽娜.2009.智能控制理论与应用.北京:清华大学出版社
孙庚山,兰西贵.1995.工程模糊控制.北京:机械工业出版社
孙继祥.2009.图像处理.北京:科学出版社:147~196
孙元义,张绍磊,李伟.2007.棉田喷药农业机器人的导航路径识别.清华大学学报(自然科学版),47(2):206~209
王红波.2008.移动机器人视觉导航系统研究[硕士学位论文].北京:北京交通大学,28~41,80~84,93~98
王金政,薛晓敏,路超.2010.我国苹果生产现状与发展对策.山东农业科学,(6):117~119
王跃宗,刘京会.2009.TMS320DM642 DSP应用系统设计与开发.北京:人民邮政出版社
魏晓云,陈杰,曾云.2003.DSP技术的最新发展及其应用现状.半导体技术,28(9):18~21
吴东辉,叶秀清,顾伟康.2002.基于不确定性知识的实时道路场景理解.中国图像图形学报,7(1):69~74
吴福朝,李华,胡占义.2001.基于主动视觉子系统的摄像机自标定方法研究.自动化学报,27(6):231~234
吴佳艺,杨庆华,鲍官军,高峰.2009.基于机器视觉的林间导航路径生成算法.农业机械学报,40(70:176~179
伍雪冬,蒋新华,李建兴.2007.计算机视觉传统摄像机定标方法综述.福建工程学院学报,2:57~60
西北农林科技大学.2010-12-28.农业机械远程实时监控系统.中国发明专利,201020189270.9
邢春贵,何熙文.2004.模糊控制系统的MATLAB仿真与应用.微处理机,(1):34~36
杨庆华,吴佳艺,鲍官军,高峰.2009.农林环境机器视觉导航路径生成算法及应用.农业机械学报,40(3):148~151
杨为民,李天石,贾鸿社.2004.农业机械机器视觉导航研究.农业工程学报,20(1):160~165
有马,门田,难波,吉田,近藤.2003.草莓培养采摘高定机器人(第2报).植物工场学会志,15(3):162~168
于国英,毛罕平.2007.农业智能车辆视觉导航参数提取的研究.农机化研究,(1):167~169
张广军.2005.机器视觉.北京:科学出版社
张荣辉,卢永强.2008-01-23.遥控微耕机.中国实用新型专利,200720004287
张毅,罗元,郑太雄.2007.移动机器人技术及其应用.北京:电子工业出版社:37~50
章毓晋.1999.图像工程.北京:清华大学出版社
张志斌,罗锡文,李庆,王在满,赵祚喜.2007.基于良序集和垄行结构的农机视觉导航参数提取算法.农业工程学报,23(7):122~126
赵颖,陈兵旗,王书茂.2006.基于机器视觉的耕作机器人行走目标直线检测.农业机械学报,37(4):83~86
郑丽娜.2005.视觉导航道路识别系统中图像特征直线提取方法研究.[硕士学位论文].长春:吉林大学
支勇平.2009.我国苹果栽培制度将大改革.北京农业,(4):25
中国果品流通协会.2011.我国水果产业发展状况及柑橘产销形势分析.果农之友,(1):3~5
中科院自动化所自由软件协会. 2001.Intel Corporation Open Source Computer Vision Library Reference Manual.http://www.opencv.org.cn/[2010.06.05]
周俊.2003.农用轮式移动机器人视觉导航系统的研究.[博士学位论文].南京:南京农业大学
周俊,姬长英,刘成良.2005.农用轮式移动机器人视觉导航系统.农业机械学报,36(3):90~94
庄慧忠,杜树新,吴铁军.2004.机器人路径规划及相关算法研究.科技通报,20(3):210~215
村上,大塚,井上,杉田.1999.甘蓝采摘机器人(第1报):机器人的运行速度.农业机械学会志, 61(5):85~92
村上,大塚,井上,杉田.1999.甘蓝采摘机器人(第2报):摘取实验.农业机械学会志,61(5):93-100
高木干雄,下田阳久.2004.孙卫东等译.2007.北京:科学出版社
日本机器人学会.2005.机器人技术手册.宗光华,程军实译.2007.北京:科学出版社
Alexander M Meystel,James S Albus. 2005.智能系统结构设计与控制.冯祖仁,李人厚译.北京:电子工业出版社
Automation Technology for Off-road Equipment.ATOE ,2004:369~373
Brooks R A.1986.A robust layered control system for a mobile robot.IEEE journal of Robot and Automation,RA-2(1):14
Courbon J, Mezouar Y, Martinet P. 2008. Indoor navigation of a non-holonomic mobile robot using a visual memory. AUTONOMOUS ROBOTS,25(3):253~266
EYRE J,BIER J.2000.The evolution of DSP processors from early architectures to the latest development.IEEE Signal Processing Magazine,17(2):43~51
Gary Bradski,Adrian Kaebler.2009.学习OpenCV(中文版).于仕琪,刘瑞祯译.北京:清华大学出版社
Hamner Bradley,Singh Sanjiv,Bergerman Marcel.2010.Improve Orchard Efficiency with Autonomous Utility Vehicles. American Society of Agricultural and Biological Engineers Annual International Meeting,6:4670~4685
Hamrita T K, Tollner E W, Schafer R L, Driftmier Eng.2000. Toward fulfilling the robotic farming vision: advances in sensors and controllers for agricultural applications.Industry Applications,IEEE Transactions on,4(36):1026~1032
John F Reid,Stephen W. 1987.Searcy Vision-Based Guidance of an Agricultural Tractor.IEEE:39~43
Mario M Foglia,Giulio Renina.2006.Agricultural robot for radicchio harvesting.Journal of Field Robotics,23(6-7):363~377
Marr David.1998.视觉计算理论.姚国正等译.北京:科学出版社
Nelson H C,Yung Cang Ye.1999.An Intelligent Mobile Vehicle Navigator Based on Fuzzy Logic and Reinforcement Learning.IEEE Trans on Sys Man and Cybern.PartB:Cybernetics, 29(2):314~321
Nisson N J.1999.Artificial Intelligence:A New Synthesis.北京:机械工业出版社
Pintol F A C,Reid J F,Zhang Q.2000.Vehicle Guidance Parameter Determination from Crop Row Images using Principal Component Analysis.J.agric.Engng Res,75:257~264
Poynton C A.1996.A Technical Introduction to Digital Video,WILEY,NY
Rafael C Gonzalez,Richard E Woods,Steven L Eddins.2004.Digital Image Processing Using MATLAB.第二版.阮秋琦译.数字图像处理.2005.北京:电子工业出版社
Robin R Murphy.杜军平,吴立成,胡金春译.2004.人工智能机器人学导论.北京:电子工业出版社
Rongben Wang,Youchun Xu,Libin.2002.A vision-based road edge detection algorithm. Intelligent Vehicle Symposium,IEEE,(1):141~147
Ryo Tsubota,Noboru Noguchi,Akira Mizushima.2004.Automatic Guidance with a Laser Scanner for a
Robot Tractor in an Orchard.Proceedings of the International Conference on Siegwart R,Nourbakhsh I R.
李仁厚译.2006.自主移动机器人导论.西安:西安交通大学出版社
Sonka M,Hlavac V,Boyle R.2002.Image processing analysis and machine vision.北京:人民邮电出版社
Topi M,Markus Turtinen,Matti Pietik.2003.Real-time surface inspection by texture. System Real-time Imaging,9:289~296
Tsai R Y.1987.A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses.IEEE Journal of Rbobotics and Automation,3(4):323~343
Vezhneves Vladimir aka Dead Moroz.2005.OpenCV and Matlab camera calibration toolboxes enhancement.http://graphics.cs.msu.su/en/research/calibration/[2010-06-05]
Wang Jianhua, Shi Fanhuai.2008.A new calibration model of camera lens distortion.Pattern Rencognition,(41):607~615
Wang Z S,Wu W,Xu X H.2007.Recognition and location of the internal corners of planar checkboard calibration pattern image.Appl Mathe Comput,2:894~906
Weng Juyang,Paul Cohen.1992.Camera Calibration with Distortion Models and Accuracy Evaluation. IEEE Tracnsactions on Pattern Analysis and Machine Intelligence,14(10): 965~982
Zhang Zhengyou.2000.A flexible new technique for camera calibration.IEEE Transactions on Pattern Analysis and Machine Intelligence,22(11):1330~1334
Zhang Zhengyou.2004.Camera Calibration with One-Dimensional Objects.IEEE Transactions on Pattern Analysis and Machine Intelligence,(7):161~174