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2016 | OriginalPaper | Buchkapitel

Naive Kalman Filtering for 3D Object Orientation

verfasst von : Robert Bieda, Rafal Grygiel, Adam Galuszka

Erschienen in: Innovative Simulation Systems

Verlag: Springer International Publishing

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Abstract

In the paper Naive Kalman filter is introduced and presented for estimating orientation in 3D space. Using the assumption of Bayesian classification systems, the angular velocity vector is treated as three separate events. Therefore, three independent Kalman filters are used to estimate Euler angles for each RPY coordinate system. Data fusion is presented for real IMU sensor which integrated data from triaxial gyroscope, accelerometer and magnetometer.

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Metadaten
Titel
Naive Kalman Filtering for 3D Object Orientation
verfasst von
Robert Bieda
Rafal Grygiel
Adam Galuszka
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-21118-3_23