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Smart Agriculture ›› 2020, Vol. 2 ›› Issue (4): 56-64.doi: 10.12133/j.smartag.2020.2.4.202010-SA001

• 专刊--农业机器人与智能装备 • 上一篇    下一篇

天然橡胶割胶机器人视觉伺服控制方法与割胶试验

周航(), 张顺路, 翟毅豪, 王松, 张春龙(), 张俊雄, 李伟   

  1. 中国农业大学 工学院,北京 100083
  • 收稿日期:2020-10-13 修回日期:2020-12-27 出版日期:2020-12-30
  • 基金资助:
    国家重点研发计划(2016YFD0701501)
  • 作者简介:周 航(1991-),男,博士研究生,研究方向为农业机器人和激光雷达遥感。E-mail:zh2018@cau.edu.cn
  • 通信作者:

Vision Servo Control Method and Tapping Experiment of Natural Rubber Tapping Robot

ZHOU Hang(), ZHANG Shunlu, ZHAI Yihao, WANG Song, ZHANG Chunlong(), ZHANG Junxiong, LI Wei   

  1. College of Engineering, China Agricultural University, Beijing 100083, China
  • Received:2020-10-13 Revised:2020-12-27 Online:2020-12-30

摘要:

自动化割胶不仅可以把胶工从繁重的体力劳动和恶劣的工作环境中解放出来,还能降低对胶工的技术依赖,极大地提高生产效率。实现非结构环境下作业信息自主获取及割胶位置伺服控制是割胶机器人的关键技术。针对工作环境复杂多变、作业信息叠加交互、目标背景特征相近、亚毫米级作业精度要求等技术难点,本研究以人工橡胶林中橡胶树为割胶对象研发割胶机器人,通过建立割胶轨迹的空间数学模型,规划机器人快速接近和远离操作空间的运动路径;采用双目立体视觉技术获取树干和割线结构参数,融合机器人运动学、机器视觉技术和多传感器反馈控制技术研制了割胶机器人模块化样机。割胶机器人主要由轨道式机器人移动平台、多关节机械臂、双目立体视觉系统和末端执行器等组成。在海南天然橡胶林进行的割胶试验结果表明,在割胶机器人切割1 mm厚的橡胶树皮时,耗皮量误差约为0.28 mm,切割深度误差约为0.49 mm。该研究可为探索天然橡胶树的自动化割胶作业提供技术参考。

关键词: 天然橡胶, 机器人, 轨迹规划, 图像处理, 信息融合, 视觉伺服控制

Abstract:

Automated rubber tapping not only frees the workers from heavy physical labor and harsh working conditions, but also reduces the dependence on the workers' skills and greatly increases tapping efficiency. The key technologies for tapping robots are the independent acquisition of operational information and servo control of the tapping position in unstructured environments. In this study, taking rubber tree in rubber plantations as object, incorporating robot kinematics, machine vision technology and multi-sensor feedback control technology, a modular prototype of a rubber tapping robot was developed. The rubber tapping robot was mainly composed of an orbital mobile platform, a multi-joint robotic arm, a binocular stereo vision system and an end-effector. The binocular stereo vision and structured light system were used to obtain the structural parameters of the rubber trunk and secant. A six-joint tandem robotic arm was used for the planning and realization of complex rubber tapping trajectories. An multi-sensor fusion end-effector was developed to complete the identification of the starting point, the measurement of cut compensation and the tapping operation. To address the technical difficulties in rubber tapping operations, such as complex and variable environment, superimposed interaction of operational information, similar target background features and sub-millimeter operational accuracy requirements, the spatial mathematical model of the rubber tapping trajectory was established to plan the robot's movement path for fast approaching and moving away from the operation space. The results of the field tests conducted at a natural rubber plantation in Hainan province showed that the accuracy in bark consumption was about 0.28 mm and the accuracy in cutting depth was about 0.49 mm when the rubber tapping robot cut 1 mm thick bark. Compared to manual operations, the continuity of the chips and the flatness of the rubber output surface were improved significantly. This research could provide a positive reference and development direction for exploring automated rubber tapping operations.

Key words: natural rubber, robot, trajectory planning, image processing, information fusion, vision servo control

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