• DocumentCode
    3449581
  • Title

    Sensor fusion for autonomous outdoor navigation using neural networks

  • Author

    Davis, Ian Lane ; Stentz, Anthony

  • Author_Institution
    Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    3
  • fYear
    1995
  • fDate
    5-9 Aug 1995
  • Firstpage
    338
  • Abstract
    For many navigation tasks, a single sensing modality is sufficiently rich to accomplish the desired motion control goals; for practical autonomous outdoor navigation, a single sensing modality is a crippling limitation on what tasks can be undertaken. Using a neural network paradigm particularly well suited to sensor fusion the authors have successfully performed simulated and real-world navigation tasks that required the use of multiple sensing modalities
  • Keywords
    computerised navigation; feedforward neural nets; mobile robots; motion control; multilayer perceptrons; path planning; sensor fusion; autonomous outdoor navigation; motion control goals; multiple sensing modalities; neural networks; real-world navigation tasks; sensor fusion; Charge coupled devices; Charge-coupled image sensors; Hidden Markov models; Mobile robots; Motion control; Navigation; Neural networks; Remotely operated vehicles; Roads; Sensor fusion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems 95. 'Human Robot Interaction and Cooperative Robots', Proceedings. 1995 IEEE/RSJ International Conference on
  • Conference_Location
    Pittsburgh, PA
  • Print_ISBN
    0-8186-7108-4
  • Type

    conf

  • DOI
    10.1109/IROS.1995.525906
  • Filename
    525906