Global image features are well-suited for the visual self-localization of mobile robots. They are fast to compute, to compare and do not require much storage space. Especially when using small mobile robots with limited processing capabilities and low-resolution cameras, global features can be preferred to local features. In this paper, we compare the accuracy and computation times of different global image features when localizing small mobile robots. We test the methods under realistic conditions, taking illumination changes and translations into account. By employing a particle filter and reducing the image resolution, we speed up the localization process considerably.
[pdf]
@inproceedings{Hofmeister2010CompEff,
author = {Marius Hofmeister and Philipp Vorst and Andreas Zell},
title = {A Comparison of Efficient Global Image Features for Localizing Small
Mobile Robots},
booktitle = {ISR/ROBOTIK 2010 (Proceedings of the joint conference of ISR 2010
(41st International Symposium on Robotics) and ROBOTIK 2010 (6th
German Conference on Robotics))},
year = {2010},
pages = {143--150},
month = jun,
publisher = {VDE Verlag},
abstract = {Global image features are well-suited for the visual self-localization
of mobile robots. They are fast to compute, to compare and do not
require much storage space. Especially when using small mobile robots
with limited processing capabilities and low-resolution cameras,
global features can be preferred to local features. In this paper,
we compare the accuracy and computation times of different global
image features when localizing small mobile robots. We test the methods
under realistic conditions, taking illumination changes and translations
into account. By employing a particle filter and reducing the image
resolution, we speed up the localization process considerably.},
isbn = {978-3-8007-3273-9},
url = {http://www.cogsys.cs.uni-tuebingen.de/publikationen/2010/hofmeister2010isr.pdf}
}