基于改进型纯追踪模型的温室AGV运输平台路径追踪
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摘要
提出了一种基于改进型纯追踪算法的AGV运输平台路径追踪方法。在平台前后安装双排红外反射式光电传感器,以获取车体相对于引导线的横向偏差和航向偏差;根据偏差程度动态确定纯追踪算法的前视距离,提高了路径跟踪的精度;构建了平台运动学模型,将车体的位姿偏差信息最终转化成左右车轮的速度。仿真和实车试验表明:该方法能够解决不同初始状态的移动平台路径追踪问题,在稳定状态下,其偏差在±20mm之间,满足温室内狭窄空间的循迹运输需求。
In this paper,a path tracking method for AGV transport platform based on improved pure pursuit algorithm is proposed. The double row infrared reflective photoelectric sensor was installed before and after the platform to obtain the lateral deviation and heading deviation of the AGV relative to the navigation line. The look ahead distance of the pure tracking algorithm was dynamically determined according to the deviation degree,and the precision of the path tracking was improved. The model of the AGV movement was constructed,and the position deviation information of the car was eventually converted to the speed of the left and right wheels. The simulation and real vehicle test showed that the method cold solve the problem of path tracking in different initial states. Under the stable state,the deviation was between positive and negative 20 mm,which satisfied the requirement of tracking transportation in narrow space in greenhouse.
In this paper,a path tracking method for AGV transport platform based on improved pure pursuit algorithm is proposed. The double row infrared reflective photoelectric sensor was installed before and after the platform to obtain the lateral deviation and heading deviation of the AGV relative to the navigation line. The look ahead distance of the pure tracking algorithm was dynamically determined according to the deviation degree,and the precision of the path tracking was improved. The model of the AGV movement was constructed,and the position deviation information of the car was eventually converted to the speed of the left and right wheels. The simulation and real vehicle test showed that the method cold solve the problem of path tracking in different initial states. Under the stable state,the deviation was between positive and negative 20 mm,which satisfied the requirement of tracking transportation in narrow space in greenhouse.
引文
[1]赵晨宇,陈息坤.差速转向农业专用AGV小车的设计与模糊控制研究[J].农机化研究,2016,38(11):123-127.
[2]罗哉,唐颖奇,李冬,等.基于最优偏差路径的自动导引车纠偏方法[J].仪器仪表学报,2017,38(4):853-860.
[3] Kim J,Cho H,Kim S. Positioning and Driving Control ofFork-type Automatic Guided Vehicle With Laser Navigation[J]. International Journal of Fuzzy Logic&Intelligent Sys-tems,2013,13(4):307-314.
[4] Yu J,Lou P,Qian X,et al. An Intelligent Real-TimeMonocular Vision-Based AGV System for Accurate LaneDetecting[C]//Isecs International Colloquium on Compu-ting,Communication, Control, and Management. IEEE,2008:28-33.
[5]贺晶晶,姜平,冯晓荣.基于UWB的无人运输车的导航定位算法研究[J].电子测量与仪器学报,2016,30(11):1743-1749.
[6]张建鹏,楼佩煌,钱晓明,等.多窗口实时测距的视觉导引AGV精确定位技术研究冰[J].仪器仪表学报,2016,37(6):1356-1363.
[7]陈玉楼.自主行走拖拉机道路识别与路径导航———基于激光扫描测距[J].农机化研究,2018,40(9):227-231.
[8]张丽,李名莉.温室机器人道路识别与路径导航研究———基于红外测距[J].农机化研究,2017,39(4):221-225.
[9]郑炳坤,赖乙宗,叶峰.磁导航AGV控制系统的设计与实现[J].自动化与仪表,2014,29(3):6-10.
[10] Ailon A,Zohar I. Controllers for trajectory tracking andstring-like formation in Wheeled Mobile Robots withbounded inputs[C]//Melecon 2010-2010,IEEE Med-iterranean Electrotechnical Conference. IEEE,2010:1563-1568.
[11] Pratama P S,Gulakari A V,Setiawan Y D,et al. Trajec-tory tracking and fault detection algorithm for automaticguided vehicle based on multiple positioning modules[J].International Journal of Control Automation&Systems,2016,14(2):400-410.
[12] Coulter R C. Implementation of the Pure Pursuit PathTracking Algorithm[D]. Carnegie Mellon University,1992.
[13]熊斌,张俊雄,曲峰,等.基于BDS的果园施药机自动导航控制系统[J].农业机械学报,2017,48(2):45-50.
[14]李逃昌.基于模糊自适应纯追踪模型的农业机械路径跟踪方法[J].农业机械学报,2013,44(1):205-210.
[15]黄沛琛,罗锡文,张智刚.改进纯追踪模型的农业机械地头转向控制方法[J].计算机工程与应用,2010,46(21):216-219.
[16] Subramanian V,Burks T F. Autonomous Vehicle TurningIn the Headlands of Citrus Groves[C]//2007 Minneapo-lis,Minnesota,2007.
[17] Kelly A. A Feedforward Control Approach to the Local Nav-igation Problem for Autonomous Vehicles[D]. CarnegieMellon University,1994.
[18] Petrinec K,Kovacic Z,Marozin A. Simulator of multi-AGV robotic industrial environments[C]//IEEE Interna-tional Conference on Industrial Technology. IEEE,2009:979-983.
[2]罗哉,唐颖奇,李冬,等.基于最优偏差路径的自动导引车纠偏方法[J].仪器仪表学报,2017,38(4):853-860.
[3] Kim J,Cho H,Kim S. Positioning and Driving Control ofFork-type Automatic Guided Vehicle With Laser Navigation[J]. International Journal of Fuzzy Logic&Intelligent Sys-tems,2013,13(4):307-314.
[4] Yu J,Lou P,Qian X,et al. An Intelligent Real-TimeMonocular Vision-Based AGV System for Accurate LaneDetecting[C]//Isecs International Colloquium on Compu-ting,Communication, Control, and Management. IEEE,2008:28-33.
[5]贺晶晶,姜平,冯晓荣.基于UWB的无人运输车的导航定位算法研究[J].电子测量与仪器学报,2016,30(11):1743-1749.
[6]张建鹏,楼佩煌,钱晓明,等.多窗口实时测距的视觉导引AGV精确定位技术研究冰[J].仪器仪表学报,2016,37(6):1356-1363.
[7]陈玉楼.自主行走拖拉机道路识别与路径导航———基于激光扫描测距[J].农机化研究,2018,40(9):227-231.
[8]张丽,李名莉.温室机器人道路识别与路径导航研究———基于红外测距[J].农机化研究,2017,39(4):221-225.
[9]郑炳坤,赖乙宗,叶峰.磁导航AGV控制系统的设计与实现[J].自动化与仪表,2014,29(3):6-10.
[10] Ailon A,Zohar I. Controllers for trajectory tracking andstring-like formation in Wheeled Mobile Robots withbounded inputs[C]//Melecon 2010-2010,IEEE Med-iterranean Electrotechnical Conference. IEEE,2010:1563-1568.
[11] Pratama P S,Gulakari A V,Setiawan Y D,et al. Trajec-tory tracking and fault detection algorithm for automaticguided vehicle based on multiple positioning modules[J].International Journal of Control Automation&Systems,2016,14(2):400-410.
[12] Coulter R C. Implementation of the Pure Pursuit PathTracking Algorithm[D]. Carnegie Mellon University,1992.
[13]熊斌,张俊雄,曲峰,等.基于BDS的果园施药机自动导航控制系统[J].农业机械学报,2017,48(2):45-50.
[14]李逃昌.基于模糊自适应纯追踪模型的农业机械路径跟踪方法[J].农业机械学报,2013,44(1):205-210.
[15]黄沛琛,罗锡文,张智刚.改进纯追踪模型的农业机械地头转向控制方法[J].计算机工程与应用,2010,46(21):216-219.
[16] Subramanian V,Burks T F. Autonomous Vehicle TurningIn the Headlands of Citrus Groves[C]//2007 Minneapo-lis,Minnesota,2007.
[17] Kelly A. A Feedforward Control Approach to the Local Nav-igation Problem for Autonomous Vehicles[D]. CarnegieMellon University,1994.
[18] Petrinec K,Kovacic Z,Marozin A. Simulator of multi-AGV robotic industrial environments[C]//IEEE Interna-tional Conference on Industrial Technology. IEEE,2009:979-983.