• DocumentCode
    2641542
  • Title

    Fuzzy Critic for intelligent planning by genetic algorithm

  • Author

    Shibata, Takanori ; Fukuda, Toshio ; Tanie, Kazuo

  • Author_Institution
    Mech. Eng. Lab., Tsukuba, Japan
  • fYear
    1993
  • fDate
    27-29 Sep 1993
  • Firstpage
    78
  • Lastpage
    85
  • Abstract
    A new strategy for motion planning is proposed. The strategy applies a genetic algorithm (GA) to optimize the motion planning. To evaluate the planned motion, the strategy also applies fuzzy logic to a fitness function. The fitness function is referred to as Fuzzy Critic. The Fuzzy Critic evaluates plans as populations in the GA with respect to multiple factors. Depending on the goals of the tasks, human operators can easily determine inference rules in the Fuzzy Critic because of the fuzzy logic. The strategy determines a path for a mobile robot which moves from a starting point to a goal point, while avoiding obstacles in a work space and picking up loads on the way. Simulation illustrates the effectiveness of the proposed strategy
  • Keywords
    fuzzy control; fuzzy logic; genetic algorithms; inference mechanisms; intelligent control; mobile robots; path planning; position control; Fuzzy Critic; fitness function; fuzzy logic; genetic algorithm; inference rules; intelligent planning; mobile robot; motion planning; obstacle avoidance; simulation; Fuzzy logic; Genetic algorithms; Humans; Intelligent robots; Mobile robots; Motion planning; Neural networks; Orbital robotics; Robot kinematics; Strategic planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies and Factory Automation, 1993. Design and Operations of Intelligent Factories. Workshop Proceedings., IEEE 2nd International Workshop on
  • Conference_Location
    Palm Cove-Cairns, Qld.
  • Print_ISBN
    0-7803-0985-5
  • Type

    conf

  • DOI
    10.1109/ETFA.1993.396426
  • Filename
    396426