Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Rao-Blackwellised RFS Bayesian SLAM

    Access Status
    Fulltext not available
    Authors
    Mullane, J.
    Vo, Ba-Ngu
    Adams, M.
    Vo, Ba Tuong
    Date
    2011
    Type
    Book Chapter
    
    Metadata
    Show full item record
    Citation
    Mullane J. and Vo B.N. and Adams M., Vo B.T. 2011. Rao-Blackwellised RFS Bayesian SLAM, in Random Finite Sets for Robot Mapping and SLAM. Springer Tracts in Advanced Robotics, vol 72, pp. 97-126. Berlin: Springer.
    Source Title
    Springer Tracts in Advanced Robotics
    DOI
    10.1007/978-3-642-21390-8_6
    School
    School of Electrical Engineering and Computing
    URI
    http://hdl.handle.net/20.500.11937/60486
    Collection
    • Curtin Research Publications
    Abstract

    This chapter proposes an alternative Bayesian framework for feature-based SLAM, again in the general case of uncertain feature number and data association. As in Chapter 5, a first order solution, coined the probability hypothesis density (PHD) SLAM filter, is used, which jointly propagates the posterior PHD of the map and the posterior distribution of the vehicle trajectory. In this chapter however, a Rao-Blackwellised (RB) implementation of the PHD-SLAM filter is proposed based on the GM PHD filter for the map and a particle filter for the vehicle trajectory, with initial results presented in [56] and further refinements in [57] .

    Related items

    Showing items related by title, author, creator and subject.

    • Estimation with random finite sets
      Mullane, J.; Vo, Ba-Ngu; Adams, M.; Vo, B. (2011)
      The previous chapter provided the motivation to adopt an RFS representation for the map in both FBRM and SLAM problems. The main advantage of the RFS formulation is that the dimensions of the measurement likelihood and ...
    • Circumventing the Feature Association Problem in SLAM
      Adams, M.; Mullane, J.; Vo, Ba-Ngu (2013)
      In autonomous applications, a vehicle requires reliable estimates of its location and information about the world around it. To capture prior knowledge of the uncertainties in a vehicle's motion response to input commands ...
    • A Random-Finite-Set Approach to Bayesian SLAM
      Mullane, J.; Vo, Ba-Ngu; Adams, M.; Vo, Ba Tuong (2011)
      This paper proposes an integrated Bayesian frame work for feature-based simultaneous localization and map building (SLAM) in the general case of uncertain feature number and data association. By modeling the measurements ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.