Exploiting Distinguishable Image Features in Robotic Mapping and Localization

Patric Jensfelt, John Folkesson , Danica Kragic and Henrik I. Christensen


Simultaneous localization and mapping (SLAM) is an important research area in robotics. Lately, systems that use a single bearing-only sensors have received significant attention and the use of visual sensors have been strongly advocated. In this paper, we present a framework for 3D bearing only SLAM using a single camera. We concentrate on image feature selection in order to achieve precise localization and thus good reconstruction in 3D. In addition, we demonstrate how these features can be managed to provide real-time performance and fast matching to detect loop-closing situations. The proposed vision system has been combined with an extended Kalman Filter (EKF) based SLAM method. A number of experiments have been performed in indoor environments which demonstrate the validity and effectiveness of the approach. We also show how the SLAM generated map can be used for robot localization. The use of vision features which are distinguishable allows a straightforward solution to the ``kidnapped-robot'' scenario. q

BibTeX Entry:

  author =       {Patric Jensfelt and John Folkesson and Danica Kragic and Henrik I. Christensen},
  title =        {Exploiting Distinguishable Image Features in Robotic Mapping
and Localization},
  booktitle =    {1st European Robotics Symposium (EUROS-06)},
  year =         2006,
  editor =       {Henrik I. Christensen},
  address =      {Palermo, Italy},
  month =        mar

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