• DocumentCode
    3331330
  • Title

    Analysis of data fusion methods in certainty grids application to collision danger monitoring

  • Author

    Puente, E.A. ; Moreno, L. ; Salichs, M.A. ; Gachet, D.

  • Author_Institution
    Dept. Ingenieria de Sistemas y Autom., Univ., Politecnica de Madrid, Spain
  • fYear
    1991
  • fDate
    28 Oct-1 Nov 1991
  • Firstpage
    1133
  • Abstract
    The authors focus on the use of the occupancy grid representation to maintain and combine the information acquired from sensors about the environment. This information is subsequently used to monitor the robot collision danger risk and take into account that risk in starting the appropriate maneuver. The occupancy grid representation uses a multidimensional tessellation of space into cells, where each cell stores some information about its state. A general model associates a random vector that encodes multiple properties in a cell state. If the cell property is limited to occupancy, it is usually called occupancy grid. Two main approaches have been used to model the occupancy of a cell: probabilistic estimation and the Dempster-Shafer theory of evidence. Probabilistic estimation and some combination rules based on the Dempster-Shafter theory of evidence are analyzed and their possibilities compared
  • Keywords
    artificial intelligence; mobile robots; monitoring; navigation; probability; signal processing; Dempster-Shafer theory of evidence; artificial intelligence; autonomous mobile robots; certainty grids; collision danger monitoring; data fusion; multidimensional tessellation; probabilistic estimation; signal processing; Buildings; Data analysis; Fuses; Geometry; Mobile robots; Monitoring; Recursive estimation; Remotely operated vehicles; Sensor fusion; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, Control and Instrumentation, 1991. Proceedings. IECON '91., 1991 International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    0-87942-688-8
  • Type

    conf

  • DOI
    10.1109/IECON.1991.239281
  • Filename
    239281