Francesco Savelli and Benjamin Kuipers. 2004.
Loop-closing and planarity in topological map-building.
IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS-04),
Loop-closing has long been recognized as a critical issue when
building maps of large-scale environments from local observations.
Topological mapping methods abstract the problem of determining the
topological structure of the environment (i.e., how loops are closed)
from the problem of determining the metrical layout of places in
the map and dealing with noisy sensors. A recently developed
incremental topological mapping algorithm generates all possible
topological maps consistent with the experienced sequence of actions
and observations and the topological axioms. These are then ordered by
a preference criterion such as minimality or probability, to
determine the single best map for continued planning and exploration.
This paper presents the planarity constraint and analyzes its impact
on the search-tree of all topological maps consistent with
(non-metrical) exploration experience. Experimental studies
demonstrate excellent results even in artificial environments where
loop-closing is particularly difficult due to large amounts of
perceptual aliasing and structural symmetry.
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