• DocumentCode
    3029989
  • Title

    Cognitive Map approach for mobility path optimization using multiple objectives genetic algorithm

  • Author

    Krishnan, Prajindra Sankar ; Paw, Johnny Koh Siaw ; Kiong, Tiong Sieh

  • Author_Institution
    Dept. of Electron. & Commun. Eng., Univ. Tenaga Nasional, Kajang
  • fYear
    2009
  • fDate
    10-12 Feb. 2009
  • Firstpage
    267
  • Lastpage
    272
  • Abstract
    This paper describes the evolutionary planning strategies for mobile robot to move along the streamlined collision-free paths in a known static environment. The Cognitive Map method is combined with genetic algorithm to derive the mobile robot optimal moving path towards its goal functions. In this study, multi-objectives genetic algorithm (MOGA) is utilized due to there are more than one objective need to be achieved while planning for the robot moving path. Goal-factor and obstacle-factor are the key parameters incorporated in the MOGA fitness functions. The simulation results showed that the hybrid Cognitive Map approach with MOGA is capable of navigating a robot situated among non-moving obstacles. The proposed hybrid method demonstrates good performance in planning and optimizing mobile robot moving path with stationary obstacles and goal.
  • Keywords
    evolutionary computation; genetic algorithms; mobile robots; path planning; cognitive map; evolutionary planning strategies; mobile robot; mobility path optimization; multiple objectives genetic algorithm; Ant colony optimization; Artificial intelligence; Cognitive robotics; Genetic algorithms; Mobile robots; Navigation; Optimization methods; Path planning; Robotics and automation; Robustness; Cognitive Map Approach; Mobile Robots; Multiple Objective Genetic Algorithm; Path Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Autonomous Robots and Agents, 2009. ICARA 2009. 4th International Conference on
  • Conference_Location
    Wellington
  • Print_ISBN
    978-1-4244-2712-3
  • Electronic_ISBN
    978-1-4244-2713-0
  • Type

    conf

  • DOI
    10.1109/ICARA.2000.4803970
  • Filename
    4803970