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| 1 | 果园环境下移动采摘机器人导航路径优化显示文摘针对移动采摘机器人在果园作业时,果树较大冠层与行人等障碍物易影响机器人行驶的突出问题,该研究提出了一种基于改进人工势场法的机器人行间导航路径优化方法。首先,通过移动采摘机器人搭载的固态激光雷达实现果园行间三维点云信息获取,运用地面平面算法去除果园地面点云,提取了果园垄行与果树冠层点云。其次,采用最小二乘法(Least Squares Method,LSM)、霍夫(Hough)变换和随机采样一致性(Random Sample Consensus,RANSAC)3种方法对果园垄行点云数据进行了垄行线和初始路径的提取。最后,通过舍弃引力势场,建立了果树冠层轮廓点云势场,优化初始路径以躲避较大的果树冠层与行人障碍物。从实时性与抗噪能力两个方面,分别对利用LSM、Hough变换和RANSAC方法所提取的初始路径结果进行了分析,结果表明3种方法均可成功提取垄行线与初始路径,其中RANSAC实时性最优,平均运行时间约为0.147×10^(-3) s,标准差为0.014×10^(-3) s,且具有较好的抗噪能力。在RANSAC提取初始路径的基础上使用改进人工势场法对初始路径进行优化,避免了传统人工势场法易陷入震荡的问题。经改进人工势场法优化后的路径将障碍物点云距导航路径的最短距离由0.156 m提高至0.863 m,且平均耗时0.059 s,标准差为0.007 s,表明该优化方法具备实时优化路径以避开障碍物的能力。该研究提出的基于改进人工势场法的机器人行间导航路径优化方法基本满足安全性与实时性要求,为移动采摘机器人在果园环境下自主导航提供了技术参考。 | 胡广锐 孔微雨 齐闯 张硕 卜令昕 周建国 陈军 | 2021 | 农业工程学报2021，37，9： | 15 |
| 2 | Development of autonomous navigation system for rice transplanter显示文摘Rice transplanting requires the operator to manipulate the rice transplanter in straight trajectories.Various markers are proposed to help experienced drivers in keeping straightforward and parallel to the previous path,which are extremely boring in terms of large-scale fields.The objective of this research was to develop an autonomous navigation system that automatically guided a rice transplanter working along predetermined paths in the field.The rice transplanter used in this research was commercially available and originally manually-operated.An automatic manipulating system was developed instead of manual functions including steering,stop,going forward and reverse.A sensor fusion algorithm was adopted to integrate measurements of the Real-Time Kinematic Global Navigation Satellite System(RTK-GNSS)and Inertial Measurement Unit(IMU),and calculate the absolute moving direction under the UTM coordinate system.A headland turning control method was proposed to ensure a robust turning process considering that the rice transplanter featured a small turning radius and a relatively large slip rate at extreme steering angles.Experiments were designed and conducted to verify the performance of the newly developed autonomous navigation system.Results showed that both lateral and heading errors were less than 8 cm and 3 degrees,respectively,in terms of following straight paths.And headland turns were robustly executed according to the required pattern. | Xiang Yin Juan Du Noboru Noguchi Tengxiang Yang Chengqian Jin | 2018 | International Journal of Agricultural and Biological Engineering2018，11，6： | 6 |
| 3 | A novel detection method of spray droplet distribution based on LIDARs显示文摘During the process of plant protection in agriculture,the distribution and deposition of droplets or fog fields could directly influence the effectiveness and efficiency of spray.The traditional method of measurement of the distribution of droplets mainly used water sensitive papers,glass containers or flour to collect data and inverse results,while a new method of measurement based on the principle of reflection of LIDAR was presented.Droplets were the major targets of the study,and four important algorithms were primarily developed,including the recognition and extraction of targets,the superposition in time-domain,the calculation of effective ranges of distribution,and the development of 3D distribution models.Combined with these algorithms,in order to eliminate the environmental noise,the methods of Fuzzy Environment Matching and Secondary Filter were created and utilized.Meanwhile,the statistics was used for analysis of the duration of scanning as well as computation of the distribution,with enough datasets but the minimum length of time.The results of the experiments showed that the relative error of measurement was less than 7%and Relative Standard Deviation was less than 16%,compared with the values of manual measurement.Furthermore,the 3D models were accurate and clarified in the wind-tunnel experiment.The completed system based on this method could adapt to the requirements of both indoor and outdoor detection.Besides,it is capable of the quantized detection of droplet distribution,providing an effective way of tests for spray technique,especially for the research of the application of plant protection by UAVs. | Zheng Yongjun Yang Shenghui Yubin Lan Clint Hoffmann Zhao Chunjiang Chen Liping Liu Xingxing Tan Yu | 2017 | International Journal of Agricultural and Biological Engineering2017，10，4： | 2 |
| 4 | Development of autonomous navigation controller for agricultural vehicles显示文摘Agricultural vehicles are adopted to undertake farming tasks by traversing along crop rows in the field.Working quality depends significantly on the driving skills of the operator.Automatic guidance has been introduced into agriculture to achieve high-accuracy path tracking during the last decades,which contributes considerably to straight-line navigation.The objective of this research was to develop an autonomous navigation controller that allowed movement autonomy for various agricultural vehicles.Three wheel-type vehicles were used as the test platform featuring automatic steering,hydrostatic transmission and speed control,which included a rice transplanter,a high-clearance sprayer and a tractor.A dual-antenna RTK-GNSS receiver was attached to the vehicles to provide spatial information on both positioning and heading by using the RTX service from Trimble.A path planning method was proposed to create a straight-line reference path by giving two points,and the target path was determined according to the vehicle initial status and working assignment.Headland turning was comprehensively taken into account by listing different turn patterns in order to realize autonomous navigation at the headland.The navigation controller hardware was fabricated for program execution,data processing and information communication with peripherals.A human-machine interface was designed for the operator to complete basic setting,path planning and navigation control by providing controls.Field experiments were conducted to evaluate the performance and versatility of the newly developed autonomous navigation controller in guiding agricultural vehicles to follow straight paths and turn at the headland.Results showed that an appropriate turn pattern was automatically executed when finishing straight-line navigation.The lateral error in straight-line tracking was no more than 6 cm,6 cm and 5 cm for the rice transplanter,the high-clearance sprayer and the tractor,respectively.And the maximum lateral RMS error was 3.10 cm,4.75 cm,2.21 cm in terms of straight-line tracking,which indicated that the newly developed autonomous navigation controller was versatile and of high robustness in guiding various agricultural vehicles. | Xiang Yin Yanxin Wang Yulong Chen Chengqian Jin Juan Du | 2020 | International Journal of Agricultural and Biological Engineering2020，13，4： | 1 |
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