Abstract
Based on autarkic data from a low-cost, 6-axes inertial measurement unit (IMU), which is fixed onto and power-supplied by the motorcycles battery, we reconstruct forward velocity and elementary driving behavior of a motorcycle using a Hidden Markov Model (HMM). The notorious drift problem of integrated IMU data is mastered by using the voltage fluctuations of the motorcycle’s battery as a stabilizing external signal. Despite the structural simplicity of the algorithm and the relatively low performance of the IMU, the proposed off-line estimator is, after a short learning phase, accurate for a large class of motorcycles.
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© 2011 Springer-Verlag Berlin Heidelberg
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Munzinger, N., Filliger, R., Bays, S., Hug, K. (2011). HMM Based Autarkic Reconstruction of Motorcycle Behavior from Low-Cost Inertial Measurements. In: Meyer, G., Valldorf, J. (eds) Advanced Microsystems for Automotive Applications 2011. VDI-Buch. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21381-6_12
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DOI: https://doi.org/10.1007/978-3-642-21381-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21380-9
Online ISBN: 978-3-642-21381-6
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