• DocumentCode
    2874672
  • Title

    A vision system based crop rows for agricultural mobile robot

  • Author

    Jiang, Guoquan ; Zhao, Cuijun

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
  • Volume
    11
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    In a machine vision-based autonomous navigation system for agricultural field mobile robot, obtaining guidance information from crop row structure is the key in achieving accurate control of the robot. This paper presents a new method for robust recognition of plant rows based on the Hough transform. It used a camera to find a path from structured agricultural fields to automatically navigate a mobile robot following crop rows. Firstly, the camera calibration was applied to obtain the relationship between the image coordinates and the world coordinates. Secondly, pattern recognition and image processing were used to obtain quasi navigation baseline. And lastly, the real navigation line was extracted from quasi navigation baseline via Hough transform. Experimental results indicate that this method has a simple robust algorithm, low-level requirements for software and hardware, and ultimately can meet the requirement for agricultural robot´s works in the field.
  • Keywords
    Hough transforms; agriculture; calibration; cameras; image recognition; mobile robots; path planning; robot vision; Hough transform; agricultural field mobile robot; autonomous navigation system; camera calibration; crop row structure; image processing; machine vision; pattern recognition; plant row recognition; quasinavigation baseline; Agriculture; Cameras; Machine vision; Mobile robots; Navigation; Robot vision systems; Transforms; Hough Transform (HT); camera calibration; machine vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5623244
  • Filename
    5623244