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首页> 外文期刊>Computers and Electronics in Agriculture >Robotic harvesting of Gerbera Jamesonii based on detection and three-dimensional modeling of cut flower pedicels
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Robotic harvesting of Gerbera Jamesonii based on detection and three-dimensional modeling of cut flower pedicels

机译:基于切花梗的检测和三维建模的非洲菊

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Within the present study, a system for the automated harvest of Gerbera jamesonii pedicels with the help of image analytic methods was developed. The study can be divided mainly into two parts: the development of algorithms for the identification of pedicels in digital images and the development of procedures for harvesting these pedicels with a robot. Images of plants were taken with a stereo camera system, which consisted of two high-resolution CCD-cameras with near-infrared filters. The plant was positioned on a rotatable working desk and images of eight different positions were shot. The developed image processing algorithm segmented the potential pedicel regions in the images, removed noise, differentiated overlapping pedicels by using different algorithms and combined the remaining regions to pedicel objects. From the data of both images and eight plant positions three-dimensional models of the pedicels were created by triangulation. The remaining parts of the plants were modeled in a simple fashion. The evaluated 3D model is used to calculate spatial coordinates for the applied robot control. For harvesting the pedicels, an industrial robot with six axes (plus an additional linear axis) was used. A pneumatic harvest grabber was developed, which harvested the pedicels by cutting them off. In order to guarantee the collision free path of the robot, a path planning module was integrated, which includes the three-dimensional model of the plant and the test facility. With the applied techniques it was possible to correctly detect all pedicels on about 72% of the images. Regarding the whole image series of the respective plant, all pedicels could be detected in at least one photographing position in 97% of all cases. In the harvest experiments 80% of all pedicels could be harvested. The harvest rates decreased with increasing numbers of pedicels on a plant. Therefore, 98% of the pedicels could be harvested of plants with one or two pedicels, but only 51% were harvested of plants with five or more pedicels. In horticultural practice, an identification system for evaluating the stage of maturity should be included. An implementation for harvesting pedicels of different species with similar basic characteristics is imaginable.
机译:在本研究中,开发了借助图像分析方法自动收获非洲菊花梗的系统。该研究主要分为两个部分:数字图像中的花梗鉴定算法的开发和机器人收割这些花梗的程序的开发。用立体相机系统拍摄植物图像,该系统由两个带有近红外滤镜的高分辨率CCD相机组成。将工厂放置在可旋转的办公桌上,并拍摄了八个不同位置的图像。所开发的图像处理算法通过使用不同的算法对图像中潜在的花梗区域进行分割,去除噪声,区分重叠的花梗,并将其余区域组合到花梗对象中。根据图像数据和八个植物位置,通过三角剖分创建了花梗的三维模型。植物的其余部分以简单的方式建模。评估后的3D模型用于计算所应用的机器人控件的空间坐标。为了收获花梗,使用了具有六个轴(加上一个附加的线性轴)的工业机器人。开发了一种气动收割机,将花梗剪下来以收割花梗。为了保证机器人的无碰撞路径,集成了路径规划模块,其中包括工厂和测试设施的三维模型。利用所应用的技术,可以正确地检测大约72%的图像上的所有花梗。关于相应植物的整个图像系列,在所有病例的97%中,可以在至少一个拍摄位置检测到所有花梗。在收获实验中,可以收获所有花梗的80%。随着植物上花梗数量的增加,收获率下降。因此,可以收获98%的有花梗的植物有一个或两个花梗,但是只有51%的花梗可以收获的植物有五个或更多个花梗。在园艺实践中,应包括用于评估成熟阶段的识别系统。可以想到一种用于收获具有相似基本特征的不同物种的花梗的实施方案。

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