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Three-Dimensional Recognition of Agricultural Crop

农作物三维识别

基本信息

批准号：
09556055
负责人：
FUJIURA Tateshi
金额：
$ 3.9万
依托单位：
Osaka Prefecture University (2000)Shimane University (1997-1999)
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B).
财政年份：
1997
资助国家：
日本
起止时间：
1997 至 2000
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-09556055/
关键词：
3-D image Recognition Robotics Farm work Laser Crop Photo Spectral Characteristics Scanning 省力化

项目摘要

The objective of this study is to develop a 3-D vision system to recognize the crop for the automation of the farm work.Cucumber for the fresh market is harvested selectively by the human labor when the size is suitable for the market. As the fruits grow rapidly, the harvesting job must be done frequently. To automate the cucumber harvesting job, a 3-D vision system was manufactured for the trial purpose and was mounted on a cucumber-harvesting robot. The 3-D vision sensor emitted an infrared laser beam. The beam was reflected by a scanning mirror toward the crop. The reflected light from the crop surface returned to the 3-D vision sensor. Further, it was reflected by another scanning mirror and was focused on a PSD (Position Sensitive Device) by a lens. The distance to each scanning point was calculated by the signals from two anodes of the PSD.The number of pixels was 7500, that is, 60 in horizontal and 125 in vertical. Experiment wis carried out using cucumber models that were made … More based on a real cucumber. The location and the size of the fruit could be measured with fairly good accuracy. The location of the peduncle could also be recognized. The 3-D vision sensor was considered to be effective for the cucumber-harvesting robot.Cucumber was cultivated by trial in following training method.(1) Inclined trellis training(2) Training along the inclined pole(3) Training by hanging the cucumber stalk keeping the stalk inclined but parallel to the crop rowCucumber fruits on the stalk that was cultivated in the style of No.3 was most visible because the fruit hanged from the stalk and the hiding probability by leaves was small. The training method was considered suitable for the cucumber-harvesting robot.Recognition experiment of the crisp head lettuce was carried out. The size of the crisp head could be recognized by processing the 3-D image.Recognition of the cherry tomato was tried by a 3-D vision sensor mounted at the end of end effector. Many of the fruits (including the fruits hidden by the leaf) could be recognized by scanning from various view points with the motion of the end effector. Less

本研究的目的是开发一种三维视觉系统来识别农作物，以实现农业工作的自动化。鲜活市场上的黄瓜是在大小适合市场的情况下由人工有选择地收获的。由于果实生长迅速，收割工作必须频繁进行。为了实现黄瓜收获作业的自动化，为试验目的制造了一个3-D视觉系统，并将其安装在黄瓜收获机器人上。3-D视觉传感器发射一束红外激光。光束被扫描镜反射到作物上。从作物表面反射的光返回到3-D视觉传感器。此外，它被另一面扫描镜反射，并通过透镜聚焦到位置敏感设备(PSD)上。每个扫描点的距离由PSD的两个阳极发出的信号计算，像素数为7500，即水平方向60个，垂直方向125个。利用…制作的黄瓜模型进行了实验更多的是基于真正的黄瓜。水果的位置和大小可以相当准确地测量出来。也可以识别出花梗的位置。采用斜架训练(2)斜杆训练(2)斜杆训练(3)悬挂黄瓜茎，使黄瓜茎倾斜但平行于作物行进行训练，3号栽培方式的黄瓜果实最明显，因为果实挂在茎上，叶片遮挡的几率很小。认为该训练方法适用于黄瓜采摘机器人，并对脆头型生菜进行了识别实验。通过对3-D图像的处理来识别脆头的大小，并通过安装在末端执行器末端的3-D视觉传感器对樱桃番茄进行识别。随着末端执行器的运动，许多水果(包括被树叶隐藏的水果)可以通过从不同的角度扫描来识别。较少