| 基于超宽带无线定位的农业设施内移动平台路径跟踪研究 |
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| 引用本文： | 姚立健,Santosh K Pitl,杨自栋,夏坡坡,赵辰彦.基于超宽带无线定位的农业设施内移动平台路径跟踪研究[J].农业工程学报,2019,35(2):17-24. |
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| 作者姓名： | 姚立健 Santosh K Pitl 杨自栋 夏坡坡 赵辰彦 |
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| 作者单位： | 浙江农林大学工程学院;Department |
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| 基金项目： | 浙江省基础公益研究计划项目（LGN18F030001）；浙江省科技厅重大专项（2016C02G2100540）；浙江省教育厅项目（Y201636110） |
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| 摘 要： | 为实现农业设施内车辆自动导航,提出了一种基于超宽带(ultrawideband,UWB)无线定位的路径跟踪方法。运用4个基站组建UWB无线定位系统,采用加权最小二乘法(weighted least squares, WLS)法解超静定方程组,提高了移动标签的定位精度。重新定义前视距离,根据车体航向与前视直线的夹角界定车体偏差程度,并提出基于动态前视距离的改进型纯追踪模型。在MATLAB 2016a软件环境下的仿真说明该文算法优于采用固定视距的传统纯追踪算法,并进行实车试验。结果显示,在UWB定位系统的引导下,车体在不同初始状态下均能很好地收敛到期望直线,当速度为0.5 m/s时,在4种初始状态下进行直线跟踪,稳态偏差为5.4～8.4 cm,稳态偏差均值为6.3 cm。在矩形路径跟踪时,当横向偏差和航向偏差均为0的初始状态下,全程平均偏差为20.6 cm,跟踪偏差主要出现在90°转向处,最大偏差为85.5 cm,说明改进后的纯追踪算法的路径追踪质量均优于采用固定视距的传统纯追踪模型,能满足农业设施内移动平台自动导航的需求。该方法可为农业设施内车辆导航提供新思路。
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| 关 键 词： | 农业机械 控制 模型 超宽带 纯追踪 动态前视距离 路径跟踪 |
| 收稿时间： | 2018/8/10 0:00:00 |
| 修稿时间： | 2018/12/26 0:00:00 |
Path tracking of mobile platform in agricultural facilities based on ultra wideband wireless positioning |
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| Yao Lijian,Santosh K Pitl,Yang Zidong,Xia Popo and Zhao Chenyan.Path tracking of mobile platform in agricultural facilities based on ultra wideband wireless positioning[J].Transactions of the Chinese Society of Agricultural Engineering,2019,35(2):17-24. |
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| Authors: | Yao Lijian Santosh K Pitl Yang Zidong Xia Popo and Zhao Chenyan |
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| Institution: | 1. College of Engineering, Zhejiang A&F University, Hangzhou, 311300, China;,2. Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, 68583, USA;,1. College of Engineering, Zhejiang A&F University, Hangzhou, 311300, China;,1. College of Engineering, Zhejiang A&F University, Hangzhou, 311300, China; and 1. College of Engineering, Zhejiang A&F University, Hangzhou, 311300, China; |
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| Abstract: | In order to realize automatic vehicle navigation in agricultural facilities without GPS (global position system) signal, a path tracking method based on UWB (ultra wideband) positioning was proposed in this study. The test prototype uses a pure electric and four wheels mechanism with 2SW-2DW (2 steering wheels and 2 drive wheels) structure. The closed-loop system with the controller, driver, motor and encoder ensures the accuracy of the control. The indoor UWB wirelesspositioning system based on the TOA (time of arrival) principle was built by using 4 anchor nodes, and a WLS (weighted least squares) method was used to solve the statically indeterminate equations, which improved the positioning accuracy of mobile tags. The positioning error of the UWB positioning system in the 16 m×11 m rectangular center area is within 7 cm, and the positioning error of the rectangular edge is less than 12 cm, which meets the positioning requirements of path tracking test in agricultural facilities. In view of the limitation that the lookahead distance must be greater than the lateral deviation in the traditional pure pursuit model, the lookahead distance was redefined in this paper. So the scope of application of the pure pursuit model had been widened. The deviation degree of vehicle was defined quantitatively according to the angle between the heading of the vehicle and the lookahead line. The traditional pure pursuit model was improved, and a new pure pursuit model algorithm based on dynamic lookahead distance was proposed to further improve the quality of path tracking. The algorithm of path tracking was simulated and verified using MATLAB 2016a. The results showed that the average error, the maximum deviation and the stability distance of the improved algorithm with dynamic lookahead distance were better than those of the traditional pure pursuit algorithm with fixed lookahead distance, indicating that the proposed improved algorithm is effective theoretically. The real vehicle test results showed that in the guidance of UWB positioning system, the vehicle could converge to the desired path in different initial states. Linear tracking were carried out in 4 initial states. When the test prototype speed is 0.5 m/s and the signal sampling period is 10 Hz, the average deviation, maximum deviation, stable distance and adjustment time are 23.3-35.0 cm, 39.0-124.6 cm, 80.3-283.0 cm, and 6.6-13.5 s, respectively. It was also observed that the above corresponding index increased with the initial deviation of the prototype. When the prototype reaches a stable state, the steady-state deviation is 5.4-8.4 cm, and its average steady-state deviation is 6.3 cm. In the rectangular path tracking, the overall mean deviation is 20.6 cm when the initial lateral deviation and heading deviation are 0. The lateral deviation mainly occurs at 90° turning, and the maximum deviation is 85.5 cm. The path tracking quality of the improved pure tracking algorithm with dynamic lookahead distance is better than the traditional pure tracking model with fixed lookahead distance, and it can meet the requirements of mobile platforms in frequent steering for automatic navigation in the agricultural facilities. This method could provide a new idea for vehicle navigation in agricultural facilities. |
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| Keywords: | agricultural machinery control models ultra wideband pure pursuit dynamic lookahead distance path tracking |
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