E Partial Observation with the Kalman Filter

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Nonlinear Kalman Filtering for Force-Controlled Robot Tasks

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 19))

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Abstract

This appendix contains the proofs of Lemmas 7.1 and 7.2. These lemmas state that, for static systems, (i) a Kalman Filter can be run on only the observable state variables; and (ii) the full state estimate and covariance matrix (i.e., including the unobservable state variables) can be calculated at any time based on the full initial state estimate and covariance matrix and the new state estimate and covariance matrix of the observed part of the state.

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Lefebvre, T., Bruyninckx, H., De Schutter, J. E Partial Observation with the Kalman Filter. In: Nonlinear Kalman Filtering for Force-Controlled Robot Tasks. Springer Tracts in Advanced Robotics, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11533054_15

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  • DOI: https://doi.org/10.1007/11533054_15

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28023-1

  • Online ISBN: 978-3-540-31504-9

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