IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/6616090.html
   My bibliography  Save this article

A LiDAR-Aided Inertial Positioning Approach for a Longwall Shearer in Underground Coal Mining

Author

Listed:
  • Jiangtao Zheng
  • Sihai Li
  • Nan Li
  • Qiangwen Fu
  • Shiming Liu
  • Gongmin Yan

Abstract

The absolute three-dimensional position of a longwall shearer is fundamental to longwall mining automation. The positioning of the longwall shearer is usually realized by the inertial navigation system (INS) and odometer (OD). However, the position accuracy of this positioning approach gradually decreases over time due to the gyro drift. To further increase the positioning accuracy of the shearer, this paper proposes a positioning approach based on the INS and light detection and ranging (LiDAR). A Kalman filter (KF) model based on the observation provided by detecting hydraulic supports which are part of the longwall face, using the LiDAR, is established. The selection scheme of the point features is studied through a set of simulations. In addition, compared with that of the approach based on the INS and OD, the shearer positioning accuracy obtained using the proposed approach is higher. When the shearer moves along a 350 m track for 6 cutting cycles and lasts about 7.1 h, both east and north position errors can be maintained within 0.2 m and the height error within 0.1 m.

Suggested Citation

  • Jiangtao Zheng & Sihai Li & Nan Li & Qiangwen Fu & Shiming Liu & Gongmin Yan, 2021. "A LiDAR-Aided Inertial Positioning Approach for a Longwall Shearer in Underground Coal Mining," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-15, February.
  • Handle: RePEc:hin:jnlmpe:6616090
    DOI: 10.1155/2021/6616090
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/6616090.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2021/6616090.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2021/6616090?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:6616090. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.