Title:
The M-Space Feature Representation for SLAM
The M-Space Feature Representation for SLAM
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Author(s)
Folkesson, John
Jensfelt, Patric
Christensen, Henrik I.
Jensfelt, Patric
Christensen, Henrik I.
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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 subspace 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.
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Date Issued
2007-10
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Text
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Article