• DocumentCode
    2338213
  • Title

    Analysis of multirobot localization uncertainty propagation

  • Author

    Roumeliotis, Stergios I. ; Rekleitis, Ioannis M.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Minnesota Univ., MN, USA
  • Volume
    2
  • fYear
    2003
  • fDate
    27-31 Oct. 2003
  • Firstpage
    1763
  • Abstract
    This paper deals with the problem of cooperative localization for the case of large groups of mobile robots. A Kalman filter estimator is implemented and tested for this purpose. The focus of this paper is to examine the effect on localization accuracy of the number N of participating robots and the accuracy of the sensors employed. More specifically, we investigate the improvement in localization accuracy per additional robot as the size of the team increases. Furthermore, we provide an analytical expression for the upper bound on the positioning uncertainty increase rate for a team of N robots as a function of N, the odometric and orientation uncertainty for each robot, and the accuracy of a robot tracker measuring relative positions between pairs of robots. The analytical results derived in this paper are validated in simulation for different test cases.
  • Keywords
    Kalman filters; Riccati equations; cooperative systems; covariance matrices; mobile robots; multi-robot systems; uncertainty handling; Kalman filter estimator; Ricatti equation; cooperative localization; covariance matrix; homogeneous robot team; mobile robots; multirobot localization; uncertainty propagation; Analytical models; Computer science; Mechanical engineering; Mobile robots; Position measurement; Riccati equations; Robot sensing systems; Testing; Uncertainty; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on
  • Print_ISBN
    0-7803-7860-1
  • Type

    conf

  • DOI
    10.1109/IROS.2003.1248899
  • Filename
    1248899