• DocumentCode
    1722006
  • Title

    Theoretical and experimental study of uncertain set based moving target localization using multiple robots

  • Author

    Gu, Feng ; Wang, Zheng ; He, Yuqing ; Han, Jianda ; Wang, Yuechao

  • Author_Institution
    State Key Lab. of Robot., Grad. Sch. of Chinese Acad. of Sci., Shenyang, China
  • fYear
    2011
  • Firstpage
    1646
  • Lastpage
    1651
  • Abstract
    In this paper, multiple robots cooperation based moving target localization problem is researched. Different from traditional statistics based architecture, the concept of uncertain set is utilized in this paper to formulate the so called Cooperative Enhanced Set Membership Filter based cooperative localization algorithm. One of the most attracting advantages of this method is that it assumes the measurement errors are modeling as unknown-but-bounded set, instead of requiring the errors´ covariance to be obtainable beforehand, which is general in statistics based algorithm, such as Kalman Filter and Particle Filter. Furthermore, some strategies, which is originated from the update process of the ESMF algorithm itself, are proposed to improve the computational efficiency and localization accuracy. Finally, an original experimental scenario is designed with respect to an indoor multiple-rotorcraft-platform and the results are listed out and analyzed in detail to verify the feasibility and validity of the proposed algorithm.
  • Keywords
    Kalman filters; aircraft control; helicopters; mobile robots; multi-robot systems; particle filtering (numerical methods); path planning; robot vision; set theory; statistical analysis; ESMF algorithm; Kalman filter; computational efficiency improvement; cooperative enhanced set membership filter; cooperative localization algorithm; enhanced set-membership filter; indoor multiple-rotorcraft-platform; localization accuracy improvement; measurement errors; moving target localization problem; multiple robots cooperation; particle filter; statistics based architecture; uncertain set; unknown-but-bounded set; Ellipsoids; Estimation; Mathematical model; Measurement errors; Measurement uncertainty; Prediction algorithms; Robots;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on
  • Conference_Location
    Karon Beach, Phuket
  • Print_ISBN
    978-1-4577-2136-6
  • Type

    conf

  • DOI
    10.1109/ROBIO.2011.6181525
  • Filename
    6181525