• DocumentCode
    2181267
  • Title

    Solving ambiguities in MDS relative localization

  • Author

    Di Franco, Carmelo ; Melani, Alessandra ; Marinoni, Mauro

  • Author_Institution
    Scuola Superiore Sant´Anna, Pisa, Italy
  • fYear
    2015
  • fDate
    27-31 July 2015
  • Firstpage
    230
  • Lastpage
    236
  • Abstract
    Monitoring teams of mobile nodes is becoming crucial in a growing number of activities. Where it is not possible to use fixed references or external measurements, one of the possible solutions involves deriving relative positions from local communication. Well-known techniques such as trilateration and multilateration exist to locate a single node although such methods are not designed to locate entire teams. The technique of Multidimensional Scaling (MDS), however, allow us to find the relative coordinates of entire teams starting from the knowledge of the inter-node distances. However, like every relative-localization technique, it suffers from geometrical ambiguities including rotation, translation, and flip. In this work, we address such ambiguities by exploiting the node velocities to correlate the relative maps at two consecutive instants. In particular, we introduce a new version of MDS, called enhanced Multidimensional Scaling (eMDS), which is able to handle these types of ambiguities. The effectiveness of our localization technique is then validated by a set of simulation experiments and our results are compared against existing approaches.
  • Keywords
    Kalman filters; Mathematical model; Minimization; Noise measurement; Sensors; Standards; Stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Robotics (ICAR), 2015 International Conference on
  • Conference_Location
    Istanbul, Turkey
  • Type

    conf

  • DOI
    10.1109/ICAR.2015.7251461
  • Filename
    7251461