The M-space Feature Representation for SLAM
John Folkesson , Patric Jensfelt and Henrik I. Christensen
Abstract:
In this paper a new feature representation for Simultaneous
Localization and Mapping (SLAM) is discussed. The representation
addresses feature symmetries and constraints explicitly to make the
basic model numerically robust. In previous SLAM work, complete
initialization of features is typically performed prior to
introduction of a new feature into the map. This results in delayed
use of new data. To allow early use of sensory data the new feature
representation addresses the use of features that initially have
been partially observed. This is achieved by explicitly modelling
the sub-space of a feature that has been observed.
In addition to accounting for the special properties of each feature
type, the commonalities can be exploited in the new representation
to create a feature framework that allows for interchanging of SLAM
algorithms, sensor and features. Experimental results are presented
using a low-cost web-cam, a laser range scanner and combinations
thereof.
BibTeX Entry:
@Article{Folkesson07a,
author = {John Folkesson and Patric Jensfelt and Henrik Christensen},
title = {The M-space Feature Representation for SLAM},
journal = {IEEE Transactions on Robotics},
year = 2007,
volume = 23,
number = 5,
pages = {1024--1035},
month = oct
}
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