• DocumentCode
    2031192
  • Title

    Invariant filtering for simultaneous localization and mapping

  • Author

    Deans, Matthew C. ; Hebert, Martial

  • Author_Institution
    Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1042
  • Abstract
    This paper presents an algorithm for simultaneous localization and map building for a mobile robot moving in an unknown environment. The robot can measure only the bearings to identifiable targets and its own relative motion. The approach is to recursively estimate features of the environment which are invariant to the robot pose in order to decouple the pose error from the map error. The highly nonlinear nature of this problem requires more explicit reasoning about the spatial relationships between landmarks and between the robot and landmarks than those used in previous methods
  • Keywords
    filtering theory; mobile robots; recursive estimation; spatial variables measurement; invariant filtering; map building; mobile robot; recursive feature estimation; simultaneous localization; simultaneous mapping; spatial relationships; Extraterrestrial measurements; Filtering; Mobile robots; Nonlinear filters; Position measurement; Recursive estimation; Robot kinematics; Simultaneous localization and mapping; Stochastic processes; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-5886-4
  • Type

    conf

  • DOI
    10.1109/ROBOT.2000.844737
  • Filename
    844737