A System for Orientation and Acceleration Estimation in an Artificial Vestibular System

Conference: MikroSystemTechnik - KONGRESS 2011
10/10/2011 - 10/12/2011 at Darmstadt, Deutschland

Proceedings: MikroSystemTechnik

Pages: 4Language: englishTyp: PDF

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Al-Jawad, A.; Romanovas, M.; Klingbeil, L.; Traechtler, M. (Institut für Mikro- und Informationstechnik der Hahn-Schickard-Gesellschaft e.V (HSG-IMIT), Wilhelm-Schickard-Straße 10, 78052, Villingen-Schwenningen, Germany)
Mergner, T.; Fennell, L. (Universität Freiburg, Neurozentrum, Neurologie, Breisacher Str. 64, 79106 Freiburg, Germany)
Manoli, Y. (Universität Freiburg, IMTEK Institut für Mikrosystemtechnik, Fritz-Hüttinger-Professur für Mikroelektronik, Georges-Köhler-Allee 103, 79110 Freiburg, Germany)

We present an error-state formulation of a Kalman filter used for an artificial self-contained vestibular system. The Kalman filter is used in this work as a data fusion algorithm where the acceleration and angular rates signals are combined in order to obtain the correct estimation of the applied linear acceleration and the inclination angle. The paper compares a biologically inspired approach expressed as a complementary filter (CF) to a merely engineering approach for the fusion problem. The latter is expressed in a form of an Extended Kalman filter (EKF) and both methods are based on signals from low-cost MEMS sensors. Each of the presented schemes acts as an artificial vestibular sensor and can be employed as a part of the higher level systems such as the stance control.