Hashem Tamimi, Alaa Halawani, Hans Burkhardt and Andreas Zell
Appearance-based Localization of Mobile
Robots using Local Integral Invariants
In Proc. of the 9th International Conference on Intelligent Autonomous Systems (IAS-9), Tokyo, Japan, March 7 - 9, 2006.
Abstract
In appearance-based localization, the robot environment is implicitly
represented as a database of features derived from a set of images collected at
known positions in a training phase. For localization the features of the image, observed
by the robot, are compared with the features stored in the database. In this
paper we propose the application of the integral invariants to the robot localization
problem on a local basis. First, our approach detects a set of interest points in the
image using a Difference of Gaussian (DoG)-based interest point detector. Then, it
finds a set of local features based on the integral invariants around each of the interest
points. These features are invariant to similarity transformation (translation,
rotation, and scale). Our approach proves to lead to significant localization rates
and outperforms a previous work.
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Bibtex
@INPROCEEDINGS{Tamimi05-ams,
AUTHOR = "Hashem {Tamimi} and Alaa {Halawani} and Hans {Burkhardt} and Andreas {Zell}
TITLE = "Appearance-based Localization of Mobile Robots using Local Integral Invariants",
BOOKTITLE= "In Proc. of the 9th International Conference on Intelligent Autonomous Systems (IAS-9)",
ADDRESS ="Tokyo, Japan", ,
YEAR = "2006",
pages ="181--188"}