F. Dellaert, W. Burgard D. Fox, and S. Thrun
Using the Condensation Algorithm
for Robust, Vision-based Mobile Robot Localization
Proc. of the IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (CVPR'99)
Abstract
To navigate reliably in indoor environments, a mobile robot must know where
it is. This includes both the ability of globally localizing the robot from
scratch, as well as tracking the robot's position once its location is known.
Vision has long been advertised as providing a solution to these problems,
but we still lack efficient solutions in unmodified environments. Many existing
approaches require modification of the environment to function properly,
andthose that work within unmodified environments seldomly address the problem
of global localization. In this paper we present a novel, vision-based localization
method based on the Condensation algorithm (Isard 96,Isard98), a Bayesian
filtering method that uses a sampling-based density representation.We show
how the Condensation algorithm can be used in a novel way to track the position
of the camera platform rather than tracking an object in the scene. In addition,
it can also be used to globally localize the camera platform, given a visual
map of the environment. Based on these two observations, we present a vision-based
robot localization method that provides a solution to a difficult and open
problem in the mobile robotics community. As evidencefor the viability of
our approach, we show both global localization and tracking results in the
context of a state of the art robotics application.
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Bibtex
@INPROCEEDINGS{Del99Usi,
AUTHOR = {Dellaert, F. and Burgard, W. and Fox, D. and
Thrun, S.},
TITLE = {Using the Condensation Algorithm for Robust,
Vision-based Mobile RobotLocalization},
YEAR = {1999},
BOOKTITLE = {Proc.~of the IEEE ComputerSocietyConference on Computer
Vision and Pattern Recognition}
}