Abstract
Several applications require the tracking of attitude and position of a body based on velocity data. It is tempting to use direction cosine matrices (DCM), for example, to track attitude based on angular velocity data, and to integrate the linear velocity data separately in a suitable frame. In this chapter we make the case for using bivectors as the attitude tracking method of choice since several features make their performance and flexibility superior to that of DCMs, Euler angles or even rotors. We also discuss potential advantages in using CGA to combine the integration of angular and linear velocities in one step, as the features that make bivectors attractive for tracking rotations extend to bivectors that represent general displacements.
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Notes
- 1.
Miller’s algorithm is used for computing the update rotation Φ directly from gyroscope data. This algorithm is of order 5 and only has to be evaluated on every third sample.
- 2.
Modern gyroscope output bandwidths are typically 100–400 Hz.
- 3.
Which is effectively Chasles’ theorem; see also Chap. 5 in this volume.
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Acknowledgements
We would like to thank the Council for Scientific and Industrial Research in South Africa for sponsoring this research.
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Candy, L., Lasenby, J. (2011). Attitude and Position Tracking. In: Dorst, L., Lasenby, J. (eds) Guide to Geometric Algebra in Practice. Springer, London. https://doi.org/10.1007/978-0-85729-811-9_6
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