全区域覆盖移动机器人的边界识别研究
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摘要
本文以全区域覆盖移动机器人为研究对象,主要研究其工作区域的边界识别问题。文中,机器人采用视觉传感器和光电编码器与电子罗盘构建“环境地图信息”:在工作过程中,机器人通过传感器实时获得当前的位姿信息,并将其与存储的“环境地图信息”进行对比,判断是否到达边界。在边界识别过程中,机器人采用视觉导航方法识别、跟踪边界直线,通过边界直线检测自身的位置,并修正定位误差。
本文首先提出了边界识别方法,研究了机器人如何利用视觉传感器识别、跟踪边界;然后构建了机器人的视觉模型,通过视觉模型得到了机器人位置与图像坐标的对应关系;接着研究了图像处理方法:滤波、增强、分割、形态学运算等方法,图像经过处理后,利用Hough变换方法拟合到边界直线,然后再根据坐标变换关系得到边界直线与机器人位置的对应关系;最后设计了所需的图像采集处理系统以及边界识别系统。
本方法利用直线检测机器人的位置,提高了机器人定位的精度,使机器人一次覆盖下来的漏割区域大为减少,节约了机器人进行全区域覆盖时所需的时间,具有一定的应用价值。
This paper based on the region-wide coverage robots, mainly research how do they identify the boundary of the work area when they work. In this paper,the robot uses visual sensors and photoelectric encoder and electronic compass to establish "map information";when it works,it gets position fom sensors to compare with "map information" to detect whether the robot is reaching the boundary. In the course of its boundary identification,the robot uses visual navigation to identify and track the boundary lines,uses lines to detect its own positions and corrects wrong positions.
Fist, say the method about the identification of boundary,research how the robot identifies doundary with the visiual sensors;then establish visual model,and get the relationship between the robot's positions and the image coordinates;then research methods of image processing:filtering、enhancing、threshold segmentation、morphological operations and so on,after these finishing these methods,get boundary lines in the image through Hough transform, and get the boundary lines with the corresponding robot's positions;at last,design the image acquisition and processing system, as well as the boundary identification system.
This method uses lines to detect the robot's positions, improves the accuracy of the robot's positions, reduce the missing cut area after once covering, saves region-wide coverage's time, and has a certain value.
本文首先提出了边界识别方法,研究了机器人如何利用视觉传感器识别、跟踪边界;然后构建了机器人的视觉模型,通过视觉模型得到了机器人位置与图像坐标的对应关系;接着研究了图像处理方法:滤波、增强、分割、形态学运算等方法,图像经过处理后,利用Hough变换方法拟合到边界直线,然后再根据坐标变换关系得到边界直线与机器人位置的对应关系;最后设计了所需的图像采集处理系统以及边界识别系统。
本方法利用直线检测机器人的位置,提高了机器人定位的精度,使机器人一次覆盖下来的漏割区域大为减少,节约了机器人进行全区域覆盖时所需的时间,具有一定的应用价值。
This paper based on the region-wide coverage robots, mainly research how do they identify the boundary of the work area when they work. In this paper,the robot uses visual sensors and photoelectric encoder and electronic compass to establish "map information";when it works,it gets position fom sensors to compare with "map information" to detect whether the robot is reaching the boundary. In the course of its boundary identification,the robot uses visual navigation to identify and track the boundary lines,uses lines to detect its own positions and corrects wrong positions.
Fist, say the method about the identification of boundary,research how the robot identifies doundary with the visiual sensors;then establish visual model,and get the relationship between the robot's positions and the image coordinates;then research methods of image processing:filtering、enhancing、threshold segmentation、morphological operations and so on,after these finishing these methods,get boundary lines in the image through Hough transform, and get the boundary lines with the corresponding robot's positions;at last,design the image acquisition and processing system, as well as the boundary identification system.
This method uses lines to detect the robot's positions, improves the accuracy of the robot's positions, reduce the missing cut area after once covering, saves region-wide coverage's time, and has a certain value.
引文
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[3]魏崇竹,马孜,常江辉.移动机器人全局路径规划中可视图理论的简化,第25届中囤控制会议论文集(下册),2006
[4](美)Roland Siegwart and Illah R.Nourbakhsh.自主移动机器人导论.西安:西安交通大学出版社,2006.9
[5]李智军,吕恬生.遗传算法在自主移动机器人局部路径规划中的应用.机械设计.2000.7,(7):26-28
[6]宋勇,李贻斌,栗春,李彩虹.基于神经网络的移动机器人路径规划方法.系统工程与电子技术.2008.2,30(2):316-319
[7]吴镜开,黄远灿,王世兴.基于势场法的移动机器人避障路径规划.机器人技术.2007,23(2-2):228-230
[8]刘金会,郝静如.自主移动机器人导航定位技术研究初探.传感器世界,2005,(1):23-25
[9]章广萍.惯性导航及组合导航系统的探讨。惯性技术学术年会论文集.2007年:45-47
[10]Chung Shi Tseng,Bor Sen Chen,Huey Jian Uang.Fuzzy Tracking Control Design for Nonlinear Dynamic Systems Via T-S Fuzzy Model[J],IEEE Trans.Fuzzy System,2001,(6),(3):381-392.
[11]秦永元.惯性导航.北京:科学出版社,2006
[12]杨子俊,廖凤英,韦庆.GPS在移动机器人导航定位系统中的应用.舰船电子工程,2005,(6):5-7
[13]O Wijk,H I Christensen.Localization and navigation of a mobile robot using natural point landmarks extracted from data.Robotics and Autonomous Systems,,2000,3:131-42.
[14]李明峰,冯宝红,刘三枝.GPS定位技术及其应用.北京:国防工业出版社 2006
[15]燕学智,王树勋,马中胜,李辛.基于超声红外定位导航研制自动引导车辆系统吉林大学学报(工学版),2006.3,36(2):242-246
[16]江泽民,杨毅,付梦印,王美龄.基于平行线的室内视觉导航.机器人,2007.3,29(2):128-132
[17]Alberto Broggi.Parallel and local feature extraction:A real time approach to road boundary detection.IEEE Trans.on Image Processing,1995,4(2):217-223
[18]盛三元,王建华.基于多传感器信息融合技术的联合卡尔曼滤波器的设计及应用.情报指挥控制系统与仿真技术,2002,(2):53-57
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[22]Peless.Navigation Method and System for Autonomous Machines with Markers Defining the Working Area.US Patent,No.6,417,641 2000
[23]NAGATA KATSUYA et.Self-propelled Lawn-mowing Robot.JP9,135,606 1997
[24]丁毅,邱白晶,周宁,崔军,钱国宏.割草机器人GPS/DR组合导航系统的研究.农机化研究,2006(4):68-71
[25]Humberto Martinez Barbera,Antonio Gomez Skarmeta.A framwork for defining and learning fuzzy behaviors for autonomous mobile robots.Int J of Intelligent Systems,2002,17(1):1-20
[26]张军宇,何克忠.移动机器人THMR-V的组合定位系统.计算机工程与应用,200,(15):68-71
[27]卢卫娜,史忠科.基于单目视觉的车道线和道路边界同步检测.传感技术学报,2007,(5):172-1175
[28]ERNST D Dlckmanns.Computer Vision and Highway Automation.Vehicle System Dynamics,1999M(31):25-343.
[29]王春波,张卫东,许晓鸣.计算机视觉技术在智能交通系统中的应用.测控技术,2000,19(5):22-24
[30]吴晓明.基于计算机视觉的机器人导航综述.实验科学与技术,2007,5(5):25-28
[31]Conrad P,Foedisch M.Performance evaluation of color based road detection using neural nets and support vector machines[A].Applied Imagery Pattern Recognition Workshop[C],2003,(10):157-160
[32]李志平,谭铁牛,韩光胜,李学恩.移动机器人视觉导航.北京工业大学学报,2000.12,26:33-36
[33]陈东雷,王清元,张天顺.CCD传感器及其应用研究.传感器世界,2007,(7):22-26
[34](日)米本和也.CCD/CMOS图像传感器基础与应用.北京:科学出版社,2006
[35]韩立伟,徐德,基于直线和单特征点的移动机器人视觉推算定位法.机器人,200830(1):79-84
[36]Ma S.A self-calibration technique for active vision system.IEEE Trans Robotics and Automation,1996,12:114-120
[37]白雁兵,高艳.机器视觉系统坐标标定与计算方法.电子工艺技术,2007,28(6):354-357
[38]于殿泓.图像检测与处理技术.西安:西安电子科技大学出版社,2006.12
[39]刘文耀.数字图像采集与处理.北京:电子工业出版社,2007.8
[40]高成.Matlab图像处理与应用.北京:国防工业出版社,2007.4
[41]杨淑莹.图像模式识别——VC++技术实现.北京:清华大学出版社,北京交通大学出版社,2005.7
[42]史忠科,曹力.交通图像检测与分析.北京:科学出版社,2007.4
[43]L.G.Roberts.Machine perception of three-dimensional solids.J T Tippett,editor.Optical and Electro-Optical Information Processing.New York:MIT Press,1982:159-197
[44]Canny J.A Computational Approach to Edge Detection.IEEE Trans Pattern Anal Machine Intelligence,1986:8(6):679-698
[45]乔洁,李京华,杨志荣.基于Hough变换的道路边缘提取.交通与计算机,2008(1):62-64
[46]姜沫岐,许涵,俞鹏,段国强.DSP原理与应用.北京:机械工业出版社,2007.2
[47]王安民,程昱,徐宝根.DSP嵌入式系统开发典型案例.北京:人民邮电出版社,2007
[48](美)Rulph Chassaing.DSP原理及其C编程开发技术.北京:电子工业出版社,2005
[49]Makarenko A A,Williams S B,Durrant-Whyte H F.Decentralized certainty grid maps[C].Proceedings of the2003 IEEE RSJ International Conference on Intelligent Robots and Systems.Las Vegas:IEEE Press,2003:3258-3263.
[50]Nakanishi,M.Ogura,T.Real-time line extraction using a highly parallel Hough transform board Image Processing,1997.Proceedings,International Conference on.Volume 2,26-29.Oct.1997,Page(s):82-585 vol.2
[51]迟泽英,李坤宇,李武森,陈文建.高速DSP视频图像数字处理电路几个关键问题的研究分析.红外技术,2001 23(2):24-27
[52]Rolf Schmidt,Weisser H,Schulenberg P,et al.Autonomous driving on vehicle test tracks:overview,implementation and results[C].Proceedings of the IEEE Intelligent Vehicles Symposium.Dearborn,MI,USA:IEEE,2000:152-155
[53]Wijesoma W S,Kodagoda K R S,Balasuriya A P,et al.Road edge and lane boundary detection using laser and vision[C].IEEE/RSJ Intelligent Conference on Intelligent Robots and Systems.Maui,Hawaii,USA:IEEE,2001:1440-1445
[54]Do Hyoung Kim,Do-Yoon Kim;Hyun Seok Hong,Myung Jin Chung.An image-based control scheme for an active stereo vision system.Intelligent Robots and Systems,2004(IROS 2004).Proceedings.2004 IEEE/RSJ International Conference on Volume 4,28 Sept.-2 Oct.2004 Page(s):3375-3380 vol.4
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