Stochastic system identification in SO(3) | IEEE Conference Publication | IEEE Xplore

Stochastic system identification in SO(3)


Abstract:

Despite the considerable literature on attitude estimation, the kinematic models used are all deterministic. The only stochastic aspect enters through observational noise...Show More

Abstract:

Despite the considerable literature on attitude estimation, the kinematic models used are all deterministic. The only stochastic aspect enters through observational noise. Accordingly we introduce a stochastic kinematic model, namely an Ornstein-Uhlenbeck process that evolves in SO(3) and discuss joint estimation of angular velocity as well as noise parameters in such a context for apparently the first time. In particular we develop an estimation algorithm and also discuss for the first time convergence with probability 1 of the estimators. Neither of these issues are trivial because the manifold constraint induces underlying singularities.
Date of Conference: 15-18 December 2015
Date Added to IEEE Xplore: 11 February 2016
ISBN Information:
Conference Location: Osaka, Japan

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