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Naive Kalman Filtering for 3D Object Orientation

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Book cover Innovative Simulation Systems

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 33))

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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Acknowledgements

This work has been supported by NCBIR grant No. for the first and second author and by Institute of Automatic Control BK grant No. 214/RAu1/2013 for the third author in the year 2014.

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Authors and Affiliations

  1. Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Robert Bieda, Rafal Grygiel & Adam Galuszka

Authors
  1. Robert Bieda
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  2. Rafal Grygiel
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  3. Adam Galuszka
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Corresponding author

Correspondence to Robert Bieda .

Editor information

Editors and Affiliations

  1. Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland

    Aleksander Nawrat

  2. Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland

    Karol Jędrasiak

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Bieda, R., Grygiel, R., Galuszka, A. (2016). Naive Kalman Filtering for 3D Object Orientation. In: Nawrat, A., Jędrasiak, K. (eds) Innovative Simulation Systems. Studies in Systems, Decision and Control, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-319-21118-3_23

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  • DOI: https://doi.org/10.1007/978-3-319-21118-3_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21117-6

  • Online ISBN: 978-3-319-21118-3

  • eBook Packages: EngineeringEngineering (R0)

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