• DocumentCode
    3368529
  • Title

    A cloud computing approach to complex robot vision tasks using smart camera systems

  • Author

    Bistry, Hannes ; Zhang, Jianwei

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Hamburg, Hamburg, Germany
  • fYear
    2010
  • fDate
    18-22 Oct. 2010
  • Firstpage
    3195
  • Lastpage
    3200
  • Abstract
    In this paper we show our work on enabling service robot systems to distribute parts of the image processing functions to different off-board computer systems in the working environment of the robot. Thus complex algorithms can be carried out on high performance systems circumventing the restrictions considering space and power consumption that a mobile platform imposes. As high resolution cameras provide a huge amount of image data and the bandwidth of a wireless network connection is strongly limited, we are using intelligent camera systems on the mobile robot platform to execute parts of the image processing functions directly on the robot. This way only preprocessed image information will be transmitted instead of raw image data. We are using a flexible modular software framework that allows us to split image processing tasks into a pipeline of modular functions that can run on different systems. We show how our approach can be used to enable a service robot system to speed up high resolution SIFT-based object detection.
  • Keywords
    cameras; cloud computing; mobile robots; robot vision; service robots; SIFT based object detection; cloud computing approach; complex robot vision; flexible modular software framework; image data; image processing functions; intelligent camera systems; mobile robot platform; off board computer systems; power consumption; raw image data; service robot systems; smart camera systems; wireless network connection; working environment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on
  • Conference_Location
    Taipei
  • ISSN
    2153-0858
  • Print_ISBN
    978-1-4244-6674-0
  • Type

    conf

  • DOI
    10.1109/IROS.2010.5653660
  • Filename
    5653660