Mobile Robot Localization using Soft-reduced Hypotheses Tracking

  • L. Banjanović-Mehmedović
  • I. Petrović
  • E. Ivanjko
Conference paper


Mobile robot localization is the problem of determining the pose (position and orientation) of a mobile robot under complex measurement uncertainties. The Soft-reduced Hypotheses Tracking algorithm introduced here is based on the modified multiple model and exploits a soft gating of the measurements to reduce the computational requirements of the approach. The position part is based on an x- and y-histograms scan matching procedure, where x- and y-histograms are extracted directly from local occupancy grid maps using probability scalar transformation. The orientation part is based on the proposed obstacle vector transformation combined with polar histograms. Proposed algorithms are tested using a Pioneer 2DX mobile robot.


Mobile Robot Sequential Monte Carlo Global Localization Occupancy Grid Mobile Robot Localization 
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Copyright information

© Springer 2007

Authors and Affiliations

  • L. Banjanović-Mehmedović
    • 1
  • I. Petrović
    • 2
  • E. Ivanjko
    • 2
  1. 1.University of TuzlaFaculty of Electrical EngineeringTuzlaBosnia and Herzegovina
  2. 2.University of Zagreb, Faculty of Electrical Engineering and ComputingZagrebCroatia

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