基于星基增强精密单点定位的农机自动导航系统开发与测试

目的 开发基于星基增强精密单点定位的农机自动导航系统。方法 以国产雷沃TX1204拖拉机为平台,采用国产星基增强定位板卡的输出数据作为农机位置反馈量,设计位速卡尔曼滤波器对定位数据进行滤波处理,开发预瞄跟随PID路径跟踪控制算法进行导航控制,整定不同行驶速度条件下的模型控制参数,采用地基增强RTK高精度定位接收机输出数据作为参考量,搭建农机自动导航测试系统并开展系统性能测试。结果 在直线跟踪误差方面,所开发的农机自动导航系统平均误差为?0.0009436 m,标准差为0.02452 m,最大误差绝对值为0.08472 m;在邻接行误差方面,平均误差为0.0007128 m,标准差为0.02986 m,最大误差绝对值为0.15444 m。这一精度可满足大部分农机自动导航作业需求。结论 将国产星基增强精密单点定位技术用于农机自动导航是可行的;本文设计的预瞄跟随PID路径跟踪控制模型和提出的不同速度条件下PID参数与前视距离的整定方法,提高了系统对不同速度的自适应能力。     

RTK GPS mapping of transplanted row crops

This study demonstrated the feasibility of using a real-time kinematic (RTK) global positioning system (GPS) to automatically map the location of transplanted row crops. A positive-placement vegetable crop transplanter retrofitted with an RTK GPS receiver, plant, inclination, and odometry sensors, and an on-board real-time data logger were used for transplant mapping in the field during planting. Sensing the location where each plant was placed in the soil using an absolute shaft encoder mounted on the planting wheel proved to be more robust and accurate than using an infrared light beam sensor to detect the stem location of each plant immediately after planting. Field test results showed that the mean error between the plant map locations predicted by the planting data and the surveyed locations after planting was 2 cm, with 95% of the predicted plant locations being within 5.1 cm of their actual locations. Along-track errors were greater than transverse-track errors indicating that some improvement in plant map accuracy might be obtained by characterization of dynamic planting effects on final plant location. Overall, the system was capable of automatically producing a centimeter-level accuracy plant map suitable for use in precision plant care tasks such as intra-row weed control.     

Using a vision sensor system for performance testing of satellite-based tractor auto-guidance

A vision sensing system for the measurement of auto-guidance pass-to-pass and long-term errors was implemented to test the steering performance of tractors equipped with auto-guidance systems. The developed test system consisted of an optical machine vision sensor rigidly mounted on the rear of the tested tractor. The center of the drawbar hitch pin point was used as the reference from which to measure the deviation of the tractor's actual travel path from its desired path. The system was built and calibrated to a measurement accuracy of better than 2 mm. To evaluate the sensor, two auto-guidance systems equipped with RTK-level GNSS receivers were tested and the results for different travel speeds compared. Pass-to-pass and long-term errors were calculated using the relative positions of a reference at a collocated point when the tractor was operated in opposite directions within 15 min and more than 1 h apart, respectively. In addition to variations in speed, two different auto-guidance steering stabilization distances allowed for comparison of two different definitions of steady-state operation of the system. For the analysis, non-parametric cumulative distributions were generated to determine error values that corresponded to 95% of the cumulative distribution. Both auto-guidance systems provided 95% cumulative error estimates comparable to 51 mm (2 in.) claims and even smaller during Test A. Higher travel speeds (especially 5.0 m/s) significantly increased measured auto-guidance error, but no significant difference was observed between pass-to-pass and long-term error estimates. The vision sensor testing system could be used as a means to implement the auto-guidance test standard under development by the International Standard Organization (ISO). Third-party evaluation of auto-guidance performance will increase consumer awareness of the potential performance of products provided by a variety of vendors.     

Evaluation of ultrasonic sensor for variable-rate spray applications

Automatic variable-rate sprayers require accurate measurement of canopy size. An estimate of canopy size is made by measuring the distance to the canopy at several elevations above the ground; an ultrasonic sensor was used to determine canopy distance in this study. It is sometimes necessary to conduct spray operations during harsh operating conditions. In this study ultrasonic sensors were subjected to simulated environmental and operating conditions to determine their durability and accuracy. Conditions tested included exposure to extended cold, outdoor temperatures, cross winds, temperature change, dust clouds, travel speeds and spray cloud effects. The root mean square (RMS) error in a series of measurements of the distance to a simulated plant canopy was used to test for significant difference among treatments. After exposure to outdoor cold conditions for 4 months, the RMS error in distance measured by the ultrasonic sensor increased from 3.31 to 3.55 cm, which was not statistically significant. Neither the presence of dust cloud nor the changes in cross-wind speeds over a range from 1.5-7.5 m/s had significant effects on the mean RMS errors. Varying sensor travel speed from 0.8 to 3.0 m/s had no significant influence on sensor detection distances. Increasing ambient temperature from 16.7 to 41.6 °C reduced the detection distance by 5.0 cm. The physical location of the spray nozzle with respect to the ultrasonic sensor had a significant effect on mean RMS errors. The mean RMS errors of sensor distance measurements ranged from 2.3 to 83.0 cm. The RMS errors could be reduced to acceptable values by proper controlling the sensor/spray nozzles spacing on a sprayer. In addition, multiple-synchronized sensors were tested for their measurement stability and accuracy (due to possible cross-talk errors) when mounted on a prototype sprayer. It was found that isolating the pathway of the ultrasonic wave of each sensor reduced detecting interference between sensors during multiple sensor operation. Test methods presented herein may be useful in the design of standardized testing protocols for field use distance sensors.     

Development of a low-cost attitude sensor for agricultural vehicles

The objective of this research was to develop a low-cost attitude sensor for agricultural vehicles. The attitude sensor was composed of three vibratory gyroscopes and two inclinometers. A sensor fusion algorithm was developed to estimate tilt angles (roll and pitch) by least-squares method. In the algorithm, the drift error of the gyroscopes was estimated using the inclinometers. In addition to tilt angles, the attitude sensor also estimated the absolute heading angle and position with inclination error correction by integrating a GPS. Tests were conducted on a flat field, a sloping ground and a bumpy road. Results showed that the attitude sensor was able to estimate the roll angle with the maximum root mean square error of 0.43°, the pitch angle with 0.61° and the heading angle with 0.64°. Moreover, the attitude sensor dramatically improved the positioning accuracy from 25.9 cm to 3.0 cm in the sloping ground test and from 8.4 cm to 3.7 cm in the bumpy road test. The proposed technology used in the attitude sensor will help to develop advanced agricultural applications.     

谷物联合收割机在线产量监测综述——测产传感方法、产量图重建和动力学模型

为深入了解测产方法、产量图重建和动力学模型的研究内容及关键技术,对测产方法、产量图重建、谷物流的动力学模型以及产量测量中的误差等研究成果进行梳理。重点概述了测产方法的分类,介绍了不同测产方法的原理、产量图重建涉及到的关键技术和动力学模型上取得的成果;对测产方法的试验结果和优缺点进行比较;分析了测产方法、产量图重建、水分传感器、切割宽度传感器和GPS定位装置等研究的误差来源。结果表明:1)对不同方式的测产装置进行合理的安装、校准和操作,就能使测产结果达到足够的精度,建议对不同的测产方式加强误差分析并提高试验准确度。2)产量图重建过程中的部分误差通过校准可以减小甚至消除,但基于小面积地块的产量图构建及误差研究还有待加强。3)一阶动力学模型无法确定谷物混合对产量监测的影响,建议在基于非线性组合算法和反褶积算法的动力学模型上加强研究。     

Mapping soil and pasture variability with an electromagnetic induction sensor

The general objective of this study was to test a non-contact electromagnetic induction probe to evaluate the soil and pasture variability in a precision agriculture project. Assessment of the variability of soil and vegetation in a permanent pasture is the basis for management of variable rate fertilization, which is the main instrument used by farmers for improvements in permanent pasture in Alentejo, Portugal. The traditional process of sampling and evaluation of the soil is very demanding in terms of time, labour and reagents, and can derail a project of precision agriculture. This paper describes the major steps followed by the authors to simplify the methodology of soil evaluation in a permanent pasture based on measuring the apparent soil electrical conductivity. Tests were carried out in a parcel of approximately 6 ha, which was subdivided into 28 m × 28 m squares. The soil samples and the evaluation of apparent electrical conductivity were geo-referenced with a global positioning system. The geospatial data were processed by ArcGIS software and the statistical analysis resulted in significant correlation coefficient values between apparent electrical conductivity and altitude, soil pH and pasture dry matter yield.     

Centimetre-precision guidance of moving implements in the open field: a simulation based on GPS measurements

High quality and sustainable agricultural production in the open field will be supported by centimetre-precision guidance of agricultural implements. In this paper, a complete guidance system is proposed and simulated using real sensor data obtained from a real time kinematic (RTK) differential global positioning system (DGPS). This type of the satellite navigation system became available commercially in 1997 and is claimed to reach cm accuracy. It uses real time kinematics to improve the accuracy of a position fix by phase comparison of the carrier signal. The simulation primarily aims to investigate the accuracy of the guidance system that can be obtained with RTK DGPS. Using real DGPS measurement errors the simulated system showed a tracking error less than 0.005 m when the PID-controller had settled.     

基于DGPS定位与双闭环转向控制的农业自动导航系统

以东方红X-804拖拉机为平台,开发了一种基于RTK-DGPS定位和双闭环转向控制相组合的农业自动导航系统。系统主要包括RTK-DGPS接收机、姿态航向参考系统(AHRS)、转向控制器、电控液压转向装置和转向角检测传感器。设计了Kalman滤波器对定位数据进行平滑处理,同时实现航向角的校正。为实现自动转向,在拖拉机原有手动控制系统基础上加上电控比例液压阀,并设计电控单元。然后,推导了转向系统的数学模型,通过Matlab仿真工具箱得到传递函数的参数,设计了双闭环转向控制算法。最后,进行了算法验证试验和田间试验,结果表明,双闭环控制方法较好抑制了稳态时的震荡现象,方波信号的角度跟踪稳态时最大误差0.60°,平均误差0.40°,平均延时为0.20 s;设计的Kalman滤波器有助于提高定位系统的精度,横向跟踪误差不超过0.09 m,转向角度平均跟踪误差为0.43°,延时0.25 s。     

工件定位误差的分析与研究

通过对工件定位误差的综合分析与研究，发现由于分析出发点不同；定位误差计算值会有较大差别。为了在实际应用时准确、简便地进行误差分析，本文论述了几种典型的定位方式及其误差计算，并论述了各项误差分析的基本原理和总误差合成的计算方法。     

Small-radius turning performance of an articulated vehicle by direct yaw moment control

This paper reports the turning performance of an articulated vehicle in which applying direct yaw-moment control is applied to reduce the turning radius. In the proposed method, a braking force is applied to the inner tires when the articulation angle reaches its maximum in turning, which generates a yaw-moment around the vehicle's centre of gravity. The yaw-moment allows the vehicle to turn in a small radius. To evaluate the performance in tight turns, experiments were conducted using a wheel loader on paved ground. The vehicle's turning radius, yaw rate and side-slip angle were determined from the data measured using two global positioning systems and a fibre-optic gyro sensor. In addition, results of a simulation were compared with experimental results from a test vehicle. The turning radius at a braking pressure of 4 MPa was at least 0.41 m smaller than that of 0 MPa. Experimental and simulated results proved that generating a yaw-moment by applying one-sided braking forces during turning decreases the turning radius.     

Evaluating the navigation performance of multi-information integration based on low-end inertial sensors for precision agriculture

The main objective of this research was to evaluate the navigation performance of multi-information integration based on a low-end inertial measurement unit (IMU) in precision agriculture by utilizing different auxiliary information (i.e., GNSS real-time kinematic (RTK), non-holonomic constraints (NHC) and dual antenna GNSS). A series of experiments with different operation scenes (e.g., open sky in wet and dry soils) were carried out for quantitative analysis. For the position drift error during a 20-s GNSS outage, the dual-antenna GNSS-assisted approach did not provide a reduction, and the NHC reduced the maximum error in the lateral and vertical directions by over 80% in the dry soil test, but only by approximately 30% in the wet soil test. The heading error with continuous GNSS assistance can be less than 0.03° and be reduced by more than 90% with the aid of dual-antenna GNSS. Additionally, the NHC reduced the heading error from 0.54° to 0.21° and from 0.34° to 0.25° in the dry and wet soil tests respectively. The results suggested that the multi-information integration improved the positioning and orientation reliability. Moreover, the lateral positioning accuracy required for the control of agriculture autonomous vehicles was achieved at approximately 3.0 mm with over a 60% accuracy improvement brought by the dual-antenna GNSS assistance. In contrast to the vulnerability of a single system, multi-information integration can provide comprehensive navigation information with higher reliability and lower costs. Hence, multi-information fusion will be a great opportunity for agriculture to meet the high-accuracy and high-reliability requirements of precision agriculture.

     

农业信息化建设中手机地图定位误差分析

针对手机GIS在农业信息化应用中的空间位置误差,通过定性和定量分析,确定误差来源,计算误差大小。经过分析和计算,认为误差主要来源于两个方面——手机定位误差和坐标系转换误差。其中手机定位是误差主要源头;在小尺度范围内,对数据经过合理处理后可以将误差控制在5 m左右,符合农业信息化应用对精度的要求。最后根据误差的来源和大小,提出了合理的建议和方法来减小误差,提高应用精度,为普及手机GIS在农业信息化应用中提供依据和参考,以促进农业信息化进程。     

Assessing GNSS correction signals for assisted guidance systems in agricultural vehicles

Accuracy levels achieved with differential global positioning system (DGPS) receivers in agricultural operations depend upon the quality of the correction signal. This study has assessed differential signal error from a Dedicated Base Station, OmniSTAR VBS, European Geostationary Navigation Overlay System, European reference frame-IP for internet protocol (EUREF-IP) and radio navigation satellite aided technique (RASANT). These signals were utilized in guidance assisting systems for agricultural applications, such as tillage, harvesting, planting and spraying, in which GPS receivers were used under dynamic conditions. Simulations of agricultural operations on different days and at different time slots and simultaneously recording the tractor′s geo-position from a DGPS receiver and the tractor′s geo-position from a real-time kinematic (RTK) GPS allowed the comparison of the GPS correction signals. The hardware used for tractor guidance was a lightbar (Trimble model EZ-Guide Plus) system. ANOVA statistics showed a significant difference between the accuracy of the correction signals from different sources. GPS correction signal recommendations to farmers depend upon the accuracy required for the specific operation: (a) Yield monitoring and soil sampling (<1 m) are possible with all the GPS correction signals accessed in any time slot. (b) Broadcast seeding, fertilizer and herbicide application (<0.5 m) are possible for 80% of time with OmniSTAR VBS, 40% of time with RASANT and EUREF-IP and 100% of time with a dedicated base station. (c) Transplanting and drill seeding (<0.04 m) are not possible with the accuracy correction provided by any one of the systems used in this study.     

林区GPS控制网的建立及应用

该文通过试验探讨了林区GPS控制网布设的方法和一般原则,研究了基于该网的GPS单点定位、小班边界空间定位和SPOT5、QuickBird等高空间分辨率遥感图像几何精校正地面控制点采集等GPS在林业中应用的主要问题.结果表明,通过以林区GPS控制网差分基准站作为控制点求解高精度的坐标转换参数,手持式GPS单机定位最大综合误差为3.86 m;小班边界平均位移和中心位置绝对位移分别为3.23、3.72 m,小班面积测量精度达到98%以上;所采集的地面控制点综合误差小于0.5 m,完全满足SPOT5、IKONOS及QuickBird等高空间分辨率卫星图像几何精校正的要求,对SPOT5和QuickBird图像进行多项式变换几何精校正,综合误差均小于1个像元.建立林区GPS控制网后,GPS在林区应用的精度和效率大大提高.     

基于Quick Bird遥感影像的铜仁市城市绿地景观结构特征分析

以2004年9月4日Quick Bird遥感影像,辅以实时动态差分GPS RTK技术高精度定位,运用GIS技术和景观斑块谱分析方法,对铜仁市城市绿地景观结构特征进行分析。结果表明:(1)铜仁市城市绿地斑块面积5 857.96 hm2,斑块数量6 503块,规划区绿地斑块面积和斑块数量均大于中心城区;(2)在各种绿地类型中,其他绿地在斑块面积上占绝对优势,其次为农业用地和生产防护绿地,道路绿地面积最小。在斑块数量上,居住区绿地>农业用地>其他绿地>生产防护绿地>道路绿地>单位附属绿地>公园绿地;(3)按绿地斑块面积统计,大于10 000 m2的大型绿地占绝对优势,占整个绿地面积的92.44%,按斑块数量统计,小于500 m2的小型斑块占优势,占整个绿地斑块的69.72%;(4)小型斑块以居住区绿地最多,其次为农业用地和其他绿地等,公园绿地最少;中型斑块和大中型斑块以农业用地最多,大型斑块在面积上以其他绿地最多,数量上以农业用地最多;公园绿地和居住区绿地在各等级绿地斑块中,面积和斑块数量相对较小。综合分析,铜仁市在今后的城市绿地建设中,中心城区内应加强绿化力度,适当将现有的绿地扩大连片,规划区内应合理调整和规划绿地性质,丰富绿地功能特性,注重绿地结构的合理规划,将小型、中型绿地尽可能有效地连片,增加大中型绿地斑块,特别是在与人居密切相关的居住区、单位和街道等周围,增加大中型绿地、大型绿地,以满足人们生产生活对绿地的需求,同时,保护生物多样性,优化城市生态环境。     

Digital image analysis to estimate the live weight of broiler

Computer assisted digital image analysis was performed to investigate the possibility of estimating body weight of live broiler. To achieve the stated objective, 100 Arbor acres broiler chicks were reared under standard rearing condition and 1200 digital images were captured from 20 randomly selected broilers during the 7-42 days growing period. The captured images were analyzed by raster image analysis software (IDRISI 32) to determine the broiler body surface area and developed a linear equation to estimate weights of the broiler from its body surface-area pixels. The developed weight predicted equation based on surface-area pixels was log W = 1.060406(log P) + 0.173756(log A) − 2.029268 (W = estimated body weight, P = surface-area pixels and A = age at weighing) and the degree of goodness of fit of this equation was 0.999. The relative error in weight estimation of broiler chicken by image analysis, expressed in terms of percent error of the residuals from surface-area pixels was in between 0.04 and 16.47. On the other hand, the estimated body weights were not significantly (p > 0.05) difference from manually measured body weights up to 35 days of age. Thus, the development of a practical imaging system for weighing live broiler is feasible.     

混凝土强度试验误差的研究及应用

本文通过对塔里木河阿拉尔护岸工程和上游水库护坡工程混凝土抗压强度试验资料的统计、计算,推求出了试验误差及试验水平等级.为合理评定混凝土质量提出了符合本实验室、本地区的试验误差值.填补了我区这方面资料缺乏,长期没有引起试验工作者重视的空白.指出C15和C20的试验误差分别为;0.83MPa和1.12MPa,并根据两个等级混凝土的强度变异系数,确定了试验水平为“良好”.同时,对其主要影响因素进行分析,提出了改进和推广应用的见解.     

Propagation of positional measurement errors to agricultural field boundaries and associated costs

It has been argued that the upcoming targeted approach to managing field operations, or precision farming, requires that field boundaries are measured with cm level accuracy, thus avoiding losses such as wasted inputs, unharvested crops and inefficient use of the land. This paper demonstrates a method for verification of such claims, based on a statistical model that accounts for temporal correlation in positional measurement errors. Our implementation employs the Data Uncertainty Engine (DUE), which is free software that aids the user in defining probability distributions for uncertain spatial objects, and draws random samples from these distributions. A case study concerning the financial consequences of uncertain geometry for a farmer who uses a digital map to optimise field operations for 15 ha of a potato crop is presented. The error model was parameterised on measurement scenarios representing (1) the Dutch registry of agricultural fields; (2) differential GPS-based field checks for verification of area declarations; and (3) special purpose Real Time Kinematic (RTK)-GPS surveys. We found that a farmer who has a manually digitised map of the study area would benefit from a RTK-GPS survey in a single crop year if the survey would cost less than € 442. An independent test case showed that the results of the error model were consistent with field data.     

Extended-altitude, aerial mapping of crop NDVI using an active optical sensor: A case study using a Raptor™ sensor over wheat

Recently reported testing of active, optical crop sensors in low-level aircraft have demonstrated a new class of airborne sensing system that can be deployed under any ambient illumination conditions, including at night. A second-generation, high-powered, light-emitting diode system has been assembled and tested over a 80 ha field of wheat (Triticum aestevum) by mapping the normalised difference vegetation index (NDVI) at altitudes ranging from 15 to 45 m above the canopy; significantly higher altitudes than existing systems. Comparisons with a detailed on-ground NDVI survey indicated the aerial sensor values were highly correlated to the on-ground sensor (0.79 < R² < 0.85), with close to unity slope and zero offset. The maximum average deviation between aerial and on-ground NDVI values was 0.04. Sample calculations involving two exemplar algorithms, one for estimating monoculture pasture biomass and the other for estimating wheat yield, indicate such deviations to have no significant effect on prediction accuracy. The subsequent NDVI maps proved to be invariant to sensor height over the 15-45 m altitude range meaning this new sensor configuration can be deployed over undulating crops and pastures and in areas with nearby obstacles such as trees and buildings.