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Using an Image Retrieval System for Vision-Based Mobile Robot Localization

  • Jürgen Wolf
  • Wolfram Burgard
  • Hans Burkhardt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2383)

Abstract

In this paper we present a vision-based approach to mobile robot localization, that integrates an image retrieval system with Monte-Carlo localization. The image retrieval process is based on features that are invariant with respect to image translations, rotations, and limited scale. Since it furthermore uses local features, the system is robust against distortion and occlusions which is especially important in populated environments. The sample-based Monte-Carlo localization technique allows our robot to efficiently integrate multiple measurements over time. Both techniques are combined by extracting for each image a set of possible view-points using a two-dimensional map of the environment. Our technique has been implemented and tested extensively using data obtained with a real robot. We present several experiments demonstrating the reliability and robustness of our approach.

Keywords

Mobile Robot Reference Image Image Retrieval Visibility Area Left Image 
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 2002

Authors and Affiliations

  • Jürgen Wolf
    • 1
  • Wolfram Burgard
    • 2
  • Hans Burkhardt
    • 2
  1. 1.Department of Computer ScienceUniversity of HamburgHamburgGermany
  2. 2.Department of Computer ScienceUniversity of FreiburgFreiburgGermany

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