• DocumentCode
    2836944
  • Title

    Research on the adaptive mechanisms in particle filter

  • Author

    Jinxia, Yu ; Yongli, Tang ; Wenjing, Liu

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2010
  • fDate
    26-28 May 2010
  • Firstpage
    1316
  • Lastpage
    1321
  • Abstract
    Particle filter based on the adaptive mechanisms has become a key issue for the recursive Bayesian estimation problem with non-linear, non-Gaussian and multi-modal distribution. Aimed at the inherent deficiency in particle filter and combined with the up-to-date research and application in the mobile robot field, some key technologies in current study are respectively summarized from the adaptive mechanism of sample size, the resampling strategy, proposal distribution, motion / likelihood model and the integration with other methods. At the same time, the main challenges that need to be solved in this field are concluded and some future trends about the technology of these difficulties are also presented.
  • Keywords
    Bayes methods; Monte Carlo methods; particle filtering (numerical methods); research and development; sampling methods; likelihood model; mobile robot; motion model; multimodal distribution; nonGaussian distribution; nonlinear distribution; particle filteradaptive mechanisms; proposal distribution; recursive Bayesian estimation problem; resampling strategy; Bayesian methods; Computer science; Equations; Image communication; Image processing; Mobile robots; Monte Carlo methods; Particle filters; Proposals; Recursive estimation; Adaptive Mechanisms; Motion / Likelihood Model; Particle Filter; Proposal Distribution; Resampling; Sample Size;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2010 Chinese
  • Conference_Location
    Xuzhou
  • Print_ISBN
    978-1-4244-5181-4
  • Electronic_ISBN
    978-1-4244-5182-1
  • Type

    conf

  • DOI
    10.1109/CCDC.2010.5498180
  • Filename
    5498180