Orientation Estimation by Means of Extended Kalman Filter, Quaternions, and Charts
In this paper, an orientation estimation algorithm is presented. This algorithm is based on the Extended Kalman Filter, and uses quaternions as the orientation descriptor. For the filter update, measures from an inertial measurement unit (IMU) are used. The IMU consists in a triaxial angular rate sensor, and an also triaxial accelerometer.
Quaternions describing orientations live in the unit sphere of R^4. Knowing that this space is a manifold, and applying some basic concepts regarding these mathematical objects, an algorithm that reminds the also called ''Multiplicative Extended Kalman Filter'' arises in a natural way.
The algorithm is tested in a simulated experiment, and in a real one.
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