• DocumentCode
    1846918
  • Title

    Real-Time Obstacle Detection for an Autonomous Wheelchair Using Stereoscopic Cameras

  • Author

    Nguyen, T.H. ; Nguyen, J.S. ; Pham, D.M. ; Nguyen, H.T.

  • Author_Institution
    Univ. of Technol., Sydney
  • fYear
    2007
  • fDate
    22-26 Aug. 2007
  • Firstpage
    4775
  • Lastpage
    4778
  • Abstract
    This paper is concerned with the development of a real-time obstacle avoidance system for an autonomous wheelchair using stereoscopic cameras by severely disabled people. Based on the left and right images captured from stereoscopic cameras mounted on the wheelchair, the optimal disparity is computed using the Sum of Absolute Differences (SAD) correlation method. From this disparity, a 3D depth map is constructed based on a geometric projection algorithm. A 2D map converted from this 3D map can then be employed to provide an effective obstacle avoidance strategy for this wheelchair. Experiment results obtained in a practical environment show the effectiveness of this real-time implementation.
  • Keywords
    cameras; collision avoidance; correlation methods; handicapped aids; stereo image processing; 3D depth map; autonomous wheelchair; geometric projection algorithm; obstacle avoidance; optimal disparity; real-time obstacle detection; severely disabled people; stereoscopic cameras; sum of absolute differences correlation method; Australia; Calibration; Cameras; Correlation; Face detection; Image converters; Mobile robots; Real time systems; Robot vision systems; Wheelchairs; Algorithms; Avoidance Learning; Computer Systems; Cybernetics; Disabled Persons; Humans; Personal Autonomy; Photography; Vision Disparity; Wheelchairs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
  • Conference_Location
    Lyon
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-0787-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2007.4353407
  • Filename
    4353407