György Max(1*), Béla Lantos(2)

(1) 
(2) 
(*) Corresponding Author

A Comparison of Advanced Non-linear State Estimation Techniques for Ground Vehicles


Abstract


This paper presents a comparative examination of state-of-the-art non-linear state estimation techniques. First, the Sigma- Point (SPKF) stochastic estimators are investigated on the basis of the Unscented Transformation. This is followed by the technique of non-linear symmetry-preserving observers for non-linear dynamics on the basis of symmetrical LIE groups. The variety of the deterministic and stochastic state estimation algorithms is studied the kinematics of ground vehicles. Two cases are described that deal with the reliability of path tracking, the convergence and speed of off-line calibration.

Keywords


state estimation; invariant observers; unscented KALMAN filter; vehicle kinematics

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