• DocumentCode
    757692
  • Title

    High-resolution terrain map from multiple sensor data

  • Author

    Kweon, In So ; Kanade, Takeo

  • Author_Institution
    Vision & Autonomous Syst. Center, Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    14
  • Issue
    2
  • fYear
    1992
  • fDate
    2/1/1992 12:00:00 AM
  • Firstpage
    278
  • Lastpage
    292
  • Abstract
    The authors present 3-D vision techniques for incrementally building an accurate 3-D representation of rugged terrain using multiple sensors. They have developed the locus method to model the rugged terrain. The locus method exploits sensor geometry to efficiently build a terrain representation from multiple sensor data. The locus method is used to estimate the vehicle position in the digital elevation map (DEM) by matching a sequence of range images with the DEM. Experimental results from large-scale real and synthetic terrains demonstrate the feasibility and power of the 3-D mapping techniques for rugged terrain. In real world experiments, a composite terrain map was built by merging 125 real range images. Using synthetic range images, a composite map of 150 m was produced from 159 images. With the proposed system, mobile robots operating in rugged environments can build accurate terrain models from multiple sensor data
  • Keywords
    computational geometry; computer vision; computerised navigation; computerised pattern recognition; mobile robots; 3D vision; computerised navigation; digital elevation map; locus method; mobile robots; multiple sensor data; robot vision; sensor geometry; synthetic range images; terrain map; terrain models; Geometry; Image sensors; Machine vision; Motion estimation; Navigation; Robot kinematics; Robot sensing systems; Robot vision systems; Shadow mapping; Vehicles;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.121795
  • Filename
    121795