• DocumentCode
    2473547
  • Title

    Multiscan-based map optimizer for RFID map-building with low-accuracy measurements

  • Author

    Tanaka, Kanji

  • Author_Institution
    Kyushu Univ., Japan
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper studies the problem of mobile robot map-building using a low-accuracy RFID sensor. In recent years, there has been increasing number of mobile robot systems using RFID landmarks. A difficulty arises from the fact that the characteristics of RFID sensors are quite electrically-sensitive, which makes the map-building process difficult to converge. Our solution is to integrate a robust multiscan-based online sensor model within an SGD framework of map-optimization, which significantly improves the convergence and accuracy.
  • Keywords
    gradient methods; intelligent robots; mobile robots; optimisation; radiofrequency identification; robust control; sensor fusion; stochastic processes; unsupervised learning; RFID sensor; data association; low-accuracy measurement; mobile robot map-building; multiscan-based map optimizer; optimization; robust control; stochastic gradient descent framework; unsupervised learning; Convergence; Detectors; Educational technology; Mobile robots; Particle filters; Particle measurements; Radiofrequency identification; Robot sensing systems; Robustness; Sensor phenomena and characterization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4761035
  • Filename
    4761035