• DocumentCode
    2059385
  • Title

    Prior-knowledge assisted fast 3D map building of structured environments for steel bridge maintenance

  • Author

    Sehestedt, Stephan ; Paul, Gay ; Rushton-Smith, David ; Dikai Liu

  • Author_Institution
    Fac. of Eng., Univ. of Technol., Sydney, NSW, Australia
  • fYear
    2013
  • fDate
    17-20 Aug. 2013
  • Firstpage
    1040
  • Lastpage
    1046
  • Abstract
    Practical application of a robot in a structured, yet unknown environment, such as in bridge maintenance, requires the robot to quickly generate an accurate map of the surfaces in the environment. A consistent and complete map is fundamental to achieving reliable and robust operation. In a real-world and field application, sensor noise and insufficient exploration oftentimes result in an incomplete map. This paper presents a robust environment mapping approach using prior knowledge in combination with a single depth camera mounted on the end-effector of a robotic manipulator. The approach has been successfully implemented in an industrial setting for the purpose of steel bridge maintenance. A prototype robot, which includes the presented map building approach in its software package, has recently been delivered to industry.
  • Keywords
    bridges (structures); end effectors; industrial manipulators; maintenance engineering; solid modelling; steel; structural engineering computing; end effectors; environment mapping approach; prior-knowledge assisted fast 3D map building; robotic manipulators; sensors; software package; steel bridge maintenance; Bridges; Iterative closest point algorithm; Maintenance engineering; Robot sensing systems; Service robots; Steel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering (CASE), 2013 IEEE International Conference on
  • Conference_Location
    Madison, WI
  • ISSN
    2161-8070
  • Type

    conf

  • DOI
    10.1109/CoASE.2013.6653892
  • Filename
    6653892