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Rose Stem Branch Point Detection and Cutting Point Location for Rose Harvesting Robot

机译:玫瑰干枝点检测和玫瑰收获机器人的切割点位置

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The primary objective of the study is to develop a method that can locate the proper location of cutting point of rose stem for robotic rose harvesting. Stem tracking and cutting operation are achieved using with the help of stereo vision techniques. The cutting point has a vital importance for cut rose harvesting in greenhouse which affects the efficiency of new shoot from the cut stem. In agricultural process, the cutting point depends on thickness of stem and eye on stem. Locating the eye is difficult by image processing thus another relation for cut point estimation was performed. The relation between thickness and cut length can lead to relation for cut point estimation. 239 data is collected from a greenhouse and linear relation with some deviation was acquired. To perform this relation, branch point location algorithm was developed. The proposed algorithm has three steps: branch point detection; thickness calculation; and cutting length estimation. The algorithm for branch detection performs quite well to detect and locate the position of the point when there occur no overlapping. The results of branch point detection are adequate for implementing to the robot.
机译:该研究的主要目标是开发一种方法,可以找到玫瑰杆切割点的正确位置,以便机器人升升收获。在立体声视觉技术的帮助下,使用阀杆跟踪和切割操作。切割点对温室中的升级收获至关重要,这影响了从切割杆的新芽的效率。在农业过程中,切削点取决于茎和眼睛的厚度。通过图像处理难以定位眼睛是困难的,因此进行了切割点估计的另一关系。厚度和切割长度之间的关系可以导致切割点估计的关系。从温室收集239个数据,并获得了一些偏差的线性关系。要执行此关系,开发了分支点定位算法。所提出的算法有三个步骤:分支点检测;厚度计算;和切割长度估计。分支检测的算法表现得非常好,以检测和定位在没有重叠时点的位置。分支点检测的结果足以实现机器人。

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