Title:
Closing the Loop with Graphical SLAM
Closing the Loop with Graphical SLAM
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Author(s)
Folkesson, John
Christensen, Henrik I.
Christensen, Henrik I.
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Abstract
The problem of simultaneous localization and mapping
(SLAM) is addressed using a graphical method. The main
contributions are a computational complexity that scales well with
the size of the environment, the elimination of most of the linearization
inaccuracies, and a more flexible and robust data association.
We also present a detection criteria for closing loops.We show how
multiple topological constraints can be imposed on the graphical
solution by a process of coarse fitting followed by fine tuning. The
coarse fitting is performed using an approximate system. This approximate
system can be shown to possess all the local symmetries.
Observations made during the SLAM process often contain symmetries,
that is to say, directions of change to the state space that
do not affect the observed quantities. It is important that these
directions do not shift as we approximate the system by, for example,
linearization. The approximate system is both linear and
block diagonal. This makes it a very simple system to work with
especially when imposing global topological constraints on the solution.
These global constraints are nonlinear. We show how these
constraints can be discovered automatically.We develop a method
of testing multiple hypotheses for data matching using the graph.
This method is derived from statistical theory and only requires
simple counting of observations. The central insight is to examine
the probability of not observing the same features on a return to
a region. We present results with data from an outdoor scenario
using a SICK laser scanner.
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Date Issued
2007-08
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