Experimental comparison of techniques for localization and mapping using a bearing-only sensor

  • Matthew Deans
  • Martial Hebert
Conference paper
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 271)


We present a comparison of an extended Kalman filter and an adaptation of bundle adjustment from computer vision for mobile robot localization and mapping using a bearing-only sensor. We show results on synthetic and real examples and discuss some advantages and disadvantages of the techniques. The comparison leads to a novel combination of the two techniques which results in computational complexity near Kalman filters and performance near bundle adjustment on the examples shown.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Matthew Deans
    • 1
  • Martial Hebert
    • 1
  1. 1.Carnegie Mellon UniversityPittsburghUSA

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