• DocumentCode
    2381882
  • Title

    Mining GPS data for extracting significant places

  • Author

    Agamennoni, Gabriel ; Nieto, Juan ; Nebot, Eduardo

  • Author_Institution
    Australian Center for Field Robot., Univ. of Sydney, Sydney, NSW, Australia
  • fYear
    2009
  • fDate
    12-17 May 2009
  • Firstpage
    855
  • Lastpage
    862
  • Abstract
    This paper addresses the problem of safety in mining applications. It presents new metrics that can be used to determine dangerous situations during mine operation in real time. It also presents a fast and robust algorithm for extracting significant places from information logged by a state-of-the-art collision avoidance system. Determining significant places provides valuable context information in a variety of applications such as map building, vehicle tracking and user assistance. In our case, we are interested in obtaining context information as a preliminary step towards improving mining safety. The algorithm presented here is validated with experimental data obtained from a fleet of haulage vehicles operating in various open pit mines.
  • Keywords
    Global Positioning System; collision avoidance; data handling; geographic information systems; mining; safety; GPS data; collision avoidance system; context information; dangerous situations; haulage vehicles; mine operation; mining safety; significant places extraction; Australia; Content addressable storage; Context-aware services; Data mining; Feedback; Global Positioning System; Road accidents; Road vehicles; Safety; Vehicle driving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
  • Conference_Location
    Kobe
  • ISSN
    1050-4729
  • Print_ISBN
    978-1-4244-2788-8
  • Electronic_ISBN
    1050-4729
  • Type

    conf

  • DOI
    10.1109/ROBOT.2009.5152475
  • Filename
    5152475