Exploiting Distinguishable Image Features in Robotic Mapping
and Localization
Patric Jensfelt, John Folkesson , Danica Kragic and Henrik I. Christensen
Abstract:
Simultaneous localization and mapping (SLAM) is an important research
area in robotics. Lately, systems that use a single bearing-only
sensors have received significant attention and the use of visual
sensors have been strongly advocated. In this paper, we present a
framework for 3D bearing only SLAM using a single camera. We
concentrate on image feature selection in order to achieve precise
localization and thus good reconstruction in 3D. In addition, we
demonstrate how these features can be managed to provide real-time
performance and fast matching to detect loop-closing situations. The
proposed vision system has been combined with an extended Kalman
Filter (EKF) based SLAM method. A number of experiments have been
performed in indoor environments which demonstrate the validity and
effectiveness of the approach. We also show how the SLAM generated map
can be used for robot localization. The use of vision features which
are distinguishable allows a straightforward solution to the
``kidnapped-robot'' scenario.
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BibTeX Entry:
@InProceedings{Jensfelt06b,
author = {Patric Jensfelt and John Folkesson and Danica Kragic and Henrik I. Christensen},
title = {Exploiting Distinguishable Image Features in Robotic Mapping
and Localization},
booktitle = {1st European Robotics Symposium (EUROS-06)},
year = 2006,
editor = {Henrik I. Christensen},
address = {Palermo, Italy},
month = mar
}
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