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Summary: Abstract
In this paper a new localization approach combining the
metric and topological paradigm is presented. The main idea
is to connect local metric maps by means of a global topolog-
ical map. This allows a compact environment model which
does not require global metric consistency and permits both
precision and robustness. The method uses a 360 degree la-
ser scanner in order to extract lines for the metric localiza-
tion and doors, discontinuities and hallways for the
topological approach. The approach has been widely tested
in a 50 x 25 m portion of the institute building with the new
fully autonomous robot Donald Duck. 25 randomly generat-
ed test missions have been performed with a success ratio of
96% and a mean error at the goal point of 9 mm for an over-
all trajectory length of 1.15 km. Future work will focus on a
similar hybrid approach for simultaneous localization and
automatic mapping.
1. Introduction
Perceiving the environment remains a fundamental task for
autonomous mobile systems. More precisely, localization
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