• DocumentCode
    2371284
  • Title

    Localization for mobile robot teams using maximum likelihood estimation

  • Author

    Howard, Andrew ; Matark, M.J. ; Sukhatme, Gaurav S.

  • Author_Institution
    Comput. Sci. Dept., Univ. of Southern California, SC, USA
  • Volume
    1
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    434
  • Abstract
    This paper describes a method for localizing the members of a mobile robot team, using only the robots themselves as landmarks, that is, we describe a method whereby each robot can determine the relative range, bearing and orientation of every other robot in the team, without the use of GPS, external landmarks, or instrumentation of the environment. Our method assumes that each robot is able to measure the relative pose of nearby robots, together with changes in its own pose. Using a combination of maximum likelihood estimation and numerical optimization, we can subsequently infer the relative pose of every robot in the team. This paper describes the basic formalism, its practical implementation, and presents experimental results obtained using a team of four mobile robots.
  • Keywords
    cooperative systems; formal specification; maximum likelihood estimation; mobile robots; multi-robot systems; optimisation; path planning; probability; bearing; formalism; localization; maximum likelihood estimation; mobile robot team; optimization; orientation; probability; Computer science; Global Positioning System; Instruments; Laboratories; Maximum likelihood estimation; Mobile computing; Mobile robots; Motion measurement; Robot kinematics; Robot sensing systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2002. IEEE/RSJ International Conference on
  • Print_ISBN
    0-7803-7398-7
  • Type

    conf

  • DOI
    10.1109/IRDS.2002.1041428
  • Filename
    1041428