Henrik Andreasson, André Treptow and Tom Duckett

Localization for Mobile Robots using Panoramic Vision, Local Features and Particle Filter

Proc. ICRA-2005, IEEE International Conference on Robotics and Automation


Abstract

In this paper we present a vision-based approach to self-localization that uses a novel scheme to integrate feature-based matching of panoramic images with Monte Carlo localization. A specially modified version of Lowe's SIFT algorithm is used to match features extracted from local interest points in the image, rather than using global features calculated from the whole image.
Experiments conducted in a large, populated indoor environment (up to 5 persons visible) over a period of several months demonstrate the robustness of the approach, including kidnapping and occlusion of up to 90% of the robot's field of view.

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Bibtex 

@INPROCEEDINGS{andreasson04localization,
  TITLE = {Localization for Mobile Robots using Panoramic Vision, Local Features and Particle Filter},
  AUTHOR = {Andreasson, Henrik and Treptow, Andr\'{e} and Duckett, Tom},
  BOOKTITLE = {IEEE International Conference on Robotics and Automation (ICRA 2005)},
  ADDRESS = {Barcelona, Spain},
  YEAR = {2005},
  DATE = {April, 18 -- 22}
}