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Summary: Abstract
This paper discusses mobile robot localization by
means of geometric features from a laser range
finder and a CCD camera. The features are line
segments from the laser scanner and vertical edges
from the camera. Emphasis is put on sensor
models with a strong physical basis. For both
sensors, uncertainties in the calibration and
measurement process are adequately modeled and
propagated through the feature extractors. This
yields observations with their first order covari-
ance estimates which are passed to an extended
Kalman filter for fusion and position estimation.
Experiments on a real platform show that
opposed to the use of the laser range finder only, the
multisensor setup allows the uncertainty to stay
bounded in difficult localization situations like
long corridors and contributes to an important
reduction of uncertainty, particularly in the orien-
tation. The experiments further demonstrate the
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