Title:
Exploiting Distinguishable Image Features in Robotic Mapping and Localization
Exploiting Distinguishable Image Features in Robotic Mapping and Localization
Author(s)
Jensfelt, Patric
Folkesson, John
Kragic, Danica
Christensen, Henrik I.
Folkesson, John
Kragic, Danica
Christensen, Henrik I.
Advisor(s)
Editor(s)
Collections
Supplementary to
Permanent Link
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.
Sponsor
Date Issued
2006-03
Extent
Resource Type
Text
Resource Subtype
Article