• DocumentCode
    161991
  • Title

    A study on Unscented SLAM with path planning algorithm integration

  • Author

    Hong Khac Nguyen ; Wongsaisuwan, Manop

  • Author_Institution
    Dept. of Electr. Eng., Chulalongkorn Univ., Bangkok, Thailand
  • fYear
    2014
  • fDate
    14-17 May 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper considers a framework of Unscented SLAM in integration with A* algorithm to build a map of an unknown environment and guide the robot to reach a prescribed destination so that the robot is able to become truly autonomous. In Simultaneous Localization and Mapping problem (SLAM), the use of Unscented Kalman Filter (UKF) aims at reducing the disadvantages as a result of linearization in the typical Extended Kalman Filter (EKF) approach. When the map is available, to provide the robot an ability to navigate in its environment, A* path planning algorithm will be applied to direct the robot to the desired goal by finding an appropriate path between starting point and destination. Simulation tests are executed to illustrate the performance of this framework.
  • Keywords
    Kalman filters; SLAM (robots); mobile robots; navigation; nonlinear filters; path planning; A* path planning algorithm; autonomous robot; extended Kalman filter; navigation; simultaneous localization and mapping problem; unscented Kalman filter; unscented SLAM; Kalman filters; Mobile robots; Path planning; Robot kinematics; Simultaneous localization and mapping; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2014 11th International Conference on
  • Conference_Location
    Nakhon Ratchasima
  • Type

    conf

  • DOI
    10.1109/ECTICon.2014.6839824
  • Filename
    6839824