• DocumentCode
    3240829
  • Title

    AGV decision making subsystem based on modified Dempster-Shafer evidence theory and fuzzy logic

  • Author

    Liu, Yuqiang ; Huang, Wu-Ling ; Sun, Tao ; Zhu, Fenghua

  • Author_Institution
    State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China
  • fYear
    2012
  • fDate
    24-27 July 2012
  • Firstpage
    169
  • Lastpage
    174
  • Abstract
    The AGV decision making subsystem directly affects the performance of the vehicle. The information it uses can be classified into “Objective Information” and “Subjective Information” two major groups. To fuse these two kinds of information, we propose a novel framework for decision in this paper. In the framework, an effective method based on the modified Dempster-Shafer evidence theory was used to make the fusion of the objective and subjective information. In addition, we used fuzzy logic to quantify the subjective information. The experiment shows the proposed method can solve the vagueness and uncertainty of information and achieve decision exactly and credibly.
  • Keywords
    case-based reasoning; decision making; fuzzy logic; mobile robots; pattern classification; road vehicles; sensor fusion; uncertainty handling; AGV decision making subsystem; autonomous ground vehicle; fuzzy logic; information classification; information uncertainty; modified Dempster-Shafer evidence theory; objective information fusion; subjective information fusion; vehicle performance; Cameras; Cognition; Decision making; Fuses; Fuzzy logic; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Electronics and Safety (ICVES), 2012 IEEE International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4673-0992-9
  • Type

    conf

  • DOI
    10.1109/ICVES.2012.6294284
  • Filename
    6294284