熊俊涛,何志良,汤林越,林睿,刘振.非结构环境中扰动葡萄采摘点的视觉定位技术[J].农业机械学报,2017,48(4):29-33,81.
XIONG Juntao,HE Zhiliang,TANG Linyue,LIN Rui,LIU Zhen.Visual Localization of Disturbed Grape Picking Point in Non-structural Environment[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(4):29-33,81.
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非结构环境中扰动葡萄采摘点的视觉定位技术   [下载全文]
Visual Localization of Disturbed Grape Picking Point in Non-structural Environment   [Download Pdf][in English]
投稿时间:2016-07-27  
DOI:10.6041/j.issn.1000-1298.2017.04.003
中文关键词:  葡萄  扰动  采摘点  视觉定位
基金项目:国家自然科学基金项目(31201135)、广东省科技计划项目(2015A020209123)和广州市科技计划项目(201506010081)
作者单位
熊俊涛 华南农业大学 
何志良 华南农业大学 
汤林越 华南农业大学 
林睿 华南农业大学 
刘振 华南农业大学 
中文摘要:非结构环境下采摘机器人对扰动葡萄采摘点的视觉识别定位有实际应用价值。首先基于“挠性杆-铰链-刚性杆-质量球”模型对葡萄串形态进行分析,将其扰动状态分解为XOY和YOZ 2个平面的类单摆运动,对扰动葡萄进行视频拍摄,通过对视频中多帧葡萄图像进行Otsu阈值分割得到果实和果梗,并计算出各帧图像中葡萄串的质心;对各帧图像的葡萄串质心进行曲线拟合,计算出葡萄类单摆运动的周期与摆角,从而确定当前扰动葡萄是否适合视觉定位;对可实现视觉定位的扰动葡萄,选取类单摆中间位置质心点对应的葡萄图像,对葡萄串上方矩形区域进行Canny边缘检测,再利用霍夫直线拟合结合角度约束法实现扰动葡萄采摘点的定位。视觉定位试验结果表明:自然环境中不同光照下扰动葡萄采摘点的视觉定位准确率达80%以上,为采摘机器人应用于实际生产提供了理论基础。
XIONG Juntao  HE Zhiliang  TANG Linyue  LIN Rui  LIU Zhen
South China Agricultural University,South China Agricultural University,South China Agricultural University,South China Agricultural University and South China Agricultural University
Key Words:grape  disturbance  picking point  vision localization
Abstract:The picking robot in unstructured environment has practical value in visual localization of disturbed grape. Firstly, the shape of grape was analyzed based on model of “flexible rod-hinge-rigid rod-mass ball” and its disturbed state was decomposed into pendulum of XOY plane and YOZ plane, and then fruit and stalk of grape were obtained by Otsu function from multi frame image in video of which captured disturbed grape. Then centroid of grape in each frame image was calculated, and curve fitting of grape centroid of each frame image was made. The period of grape pendulum movement and swing angle were calculated to judge whether current disturbed of the grape was suitable for visual positioning. For disturbed grape that can achieve visual positioning, choosing grape images corresponding to location in the middle of centroid point of pendulum motion, Canny edge detection was carried out on the upper rectangular region. The method of Hough line fitting and angle constraint were used to localize picking point of disturbed grape. Experiment results of visual localization showed that the accuracy of visual localization for disturbed grape picking points under different illuminations were more than 80% in natural environment, which provided theoretical basis for the application of picking robot in practical production.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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