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Design and Test of a Sorting Device Based on Machine Vision

机译:基于机器视觉的排序装置的设计与测试

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摘要

At present, the sorting of agricultural products in China mainly relies on manual labour, which results in low efficiency, and the development of corresponding automatic equipment lags behind. The grasping method based on machine vision has been widely used in industry, and can provide a reference for the automatic sorting of agricultural products. In this paper, an automatic sorting device for agricultural products was designed. The grasping mechanism adopted a 4-degree-of-freedom (4-DOF) manipulator, and the machine vision control system adopted a monocular camera, which can realize the positioning and classification of the grasp-target. First, the geometric model of the manipulator was established, and the kinematics model of the manipulator was established via the Denavit-Hartenberg (D-H) parameter method. Next, the kinematics analysis and verification were carried out. Then, Zhang Zhengyou calibration method was used to calibrate the camera. An image processing method based on histogram correction was proposed. Based on this, a target positioning algorithm based on the pinhole imaging principle and a target classification algorithm based on the area threshold were established. Finally, an automatic sorting test platform for agricultural products using a visual servo was built. Target classification, positioning and sorting tests were conducted using tomatoes and oranges as the test objects. The test results show that the success rate of the target positioning is close to 98%, that of the target classification is close to 98% and that of the grasping is close to 95%. Furthermore, the sorting time of a single target object can be as fast as 1 second, which can meet the requirements of automatic sorting for common agricultural products. The automatic sorting device for agricultural products has a simple structure, reliable performance and low costs. The structure and algorithms proposed in this paper are simple, reliable, and highly efficient and thus can easily realize technology transplantation. These relevant methods provide a theoretical reference for the development of an automatic sorting device for agricultural products.
机译:目前,中国农产品的分类主要依赖于体力劳动,从而导致低效率,以及相应的自动设备的开发后面滞后。基于机器视觉的抓握方法已广泛应用于工业中,可以为农产品的自动分选提供参考。本文设计了一种用于农产品的自动分选装置。抓握机构采用了一种自由度(4-DOF)操纵器,机器视觉控制系统采用单眼摄像头,可以实现掌握目标的定位和分类。首先,建立了操纵器的几何模型,并且通过Denavit-Hartenberg(D-H)参数方法建立了操纵器的运动学模型。接下来,进行了运动学分析和验证。然后,张正友校准方法用于校准相机。提出了一种基于直方图校正的图像处理方法。基于此,建立了基于针孔成像原理的目标定位算法和基于面积阈值的目标分类算法。最后,建立了使用视觉伺服电厂的自动分拣测试平台。使用西红柿和橙子作为测试对象进行目标分类,定位和分类测试。测试结果表明,目标定位的成功率接近98%,目标分类的接近98%,抓取性接近95%。此外,单个目标物体的分选时间可以像1秒一样快,这可以满足普通农产品的自动排序的要求。农产品的自动分选装置具有简单的结构,性能可靠,成本低。本文提出的结构和算法简单,可靠,高效,因此可以容易地实现技术移植。这些相关方法为农产品的自动分选装置开发提供了理论参考。

著录项

  • 来源
    《Quality Control, Transactions》 |2020年第2020期|27178-27187|共10页
  • 作者单位

    Shandong Agr Univ Coll Mech & Elect Engn Tai An 271018 Shandong Peoples R China|Shandong Prov Key Lab Hort Machinery & Equipment Tai An 271018 Shandong Peoples R China;

    Shandong Agr Univ Coll Mech & Elect Engn Tai An 271018 Shandong Peoples R China;

    Shandong Agr Univ Coll Mech & Elect Engn Tai An 271018 Shandong Peoples R China;

    Shandong Agr Univ Coll Mech & Elect Engn Tai An 271018 Shandong Peoples R China|Shandong Prov Key Lab Hort Machinery & Equipment Tai An 271018 Shandong Peoples R China;

    Shandong Agr Univ Coll Mech & Elect Engn Tai An 271018 Shandong Peoples R China|Shandong Prov Key Lab Hort Machinery & Equipment Tai An 271018 Shandong Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Machine vision; manipulator; target positioning; target classification; automatic sorting;

    机译:机器视觉;操纵器;目标定位;目标分类;自动排序;
  • 入库时间 2022-08-18 21:58:55

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