DocumentCode :
3530335
Title :
Intrinsic filtering on SO(3) with discrete-time observations
Author :
Barrau, Axel ; Bonnabel, Silvere
Author_Institution :
Centre de Robot., MINES ParisTech, Paris, France
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
3255
Lastpage :
3260
Abstract :
This paper proposes a stochastic approach to the problem of intrinsic filtering on the special orthogonal group SO(3). The continuous-time dynamics with discrete measurements problem is cast into a rigorous stochastic and geometric framework. It is shown that under some specific conditions on the noises´ distributions, the problem admits an exact time discretization. A discrete-time filter is proposed. It is a mere transposition of a linear discrete-time Kalman filter where the addition in ℝn has been replaced with the group multiplication law on SO(3). The state error is proved to be a Markov chain, and not to depend on the problem inputs, as in the theory of continous-time symmetry-preserving deterministic observers on Lie groups. The gain tuning exploits the Perrin formula on rotational Brownian motion. Monte-Carlo simulations illustrate the interest of the approach.
Keywords :
Kalman filters; Lie groups; Markov processes; Monte Carlo methods; discrete time filters; filtering theory; geometry; observers; Lie groups; Markov chain; Monte-Carlo simulations; Perrin formula; SO(3); continous-time symmetry-preserving deterministic observers; continuous-time dynamics; discrete measurements problem; discrete-time filter; discrete-time observations; exact time discretization; geometric framework; group multiplication; intrinsic filtering; linear discrete-time Kalman filter; noise distributions; rotational Brownian motion; special orthogonal group; state error; stochastic approach; stochastic framework; Equations; Kalman filters; Mathematical model; Noise; Observers; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6760380
Filename :
6760380
Link To Document :
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