Landmark Based Global Self-localization of Mobile Soccer Robots

  • Abdul Bais
  • Robert Sablatnig
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3852)


We present a stereo vision based global self-localization strategy for tiny autonomous mobile robots in a well-known dynamic environment. Global localization is required for an initial startup or when the robot loses track of its pose during navigation. Existing approaches are based on dense range scans, active beacon systems, artificial landmarks, bearing measurements using omni-directional cameras or bearing/range calculation using single frontal cameras, while we propose feature based stereo vision system for range calculation. Location of the robot is estimated using range measurements with respect to distinct landmarks such as color transitions, corners, junctions and line intersections. Unlike methods based on angle measurement, this method requires only two distinct landmarks. Simulation results show that robots can successfully localize themselves whenever two distinct landmarks are observed. As such marked minimization of landmarks for vision based self-localization of robots has been achieved.


Mobile Robot Global Coordinate System Color Patch Landmark Point Robot Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Abdul Bais
    • 1
  • Robert Sablatnig
    • 2
  1. 1.Institute of Computer TechnologyVienna University of TechnologyViennaAustria
  2. 2.Pattern Recognition and Image Processing Group, Institute of Computer Aided AutomationVienna University of TechnologyViennaAustria

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