• DocumentCode
    2255395
  • Title

    WiSLAM: Improving FootSLAM with WiFi

  • Author

    Bruno, Luigi ; Robertson, Patrick

  • Author_Institution
    Dept. of Inf. & Electr. Eng., Univ. of Salerno, Fisciano, Italy
  • fYear
    2011
  • fDate
    21-23 Sept. 2011
  • Firstpage
    1
  • Lastpage
    10
  • Abstract
    We address Simultaneous Localization and Mapping (SLAM) for pedestrians by means of WiFi signal strength measurements. In our system odometric data from foot mounted Inertial Measurements Units are fused with received signal strength (RSS) measurements of IEEE 802.11. To do this, we assign a probabilistic model to RSS measurements, and adopt the Bayesian framework on which FootSLAM and PlaceSLAM are based. Computational aspects are also accounted in order to provide a practical implementation of the algorithm. Simulative and experimental examples of WiSLAM are shown to underline the effectiveness of our proposal.
  • Keywords
    Bayes methods; SLAM (robots); probability; wireless LAN; Bayesian framework; FootSLAM; IEEE 802.11; PlaceSLAM; WiFi signal strength measurements; WiSLAM; foot mounted inertial measurements units; odometric data; probabilistic model; received signal strength measurements; simultaneous localization and mapping; Accuracy; Approximation methods; Bayesian methods; IEEE 802.11 Standards; Position measurement; Simultaneous localization and mapping; Bayesian algorithm; Inertial Measurements Units; Received Signal Strengths; SLAM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Indoor Positioning and Indoor Navigation (IPIN), 2011 International Conference on
  • Conference_Location
    Guimaraes
  • Print_ISBN
    978-1-4577-1805-2
  • Electronic_ISBN
    978-1-4577-1803-8
  • Type

    conf

  • DOI
    10.1109/IPIN.2011.6071916
  • Filename
    6071916