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counter, 1827.6 for the EKF filter. It therefore works
correctly in a practical scenario.
6 CONCLUSIONS
This paper presents a sensor fusion algorithm for a
wheel mounted accelerometer and gyroscope based
odometry sensor. In contrast to existing approaches
using ad hoc methods to derive wheel angles, the
presented solution uses an Extended Kalman filter as
a principled estimator for locally linear systems ob-
served by noisy sensors. The power of this algo-
rithm is demonstrated by the overall positve results of
a number of experiments using real hardware under
normal as well as extreme conditions, and by simula-
tion experiments to compare the filter output against
a well known true state. The filter adapts dynamically
to saturation of the gyroscope and of the centrifugal
force accelerometer at high speed and continues to
work with even a single accelerometer. Embedded
in a small hardware component, it will provide a very
simple way of belated or temporary installation for
existing vehicles.
ACKNOWLEDGEMENTS
The author wishes to thank Hui Shi for her intensive
rereading, Christian Mandel and Christoph Budelman
for providing the prototype sensor, and Bernd Krieg-
Br¨uckner as the initiator for this work and coordinator
of the (collaborative)project ASSAM (EU AAL Joint
Programme AAL-2011-4-062, Call 4 ICT Based So-
lutions for Advancement of Older Persons’ Mobility.
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