A comparison of Bayesian filters for orientation estimation

Abstract

This work presents an empirical study that compares the performance of Bayesian filters for orientation estimation using data provided by an Inertial Measurement Unit. A two-stages measure ment update was implemented for different variants of Kalman and particles filters using quaternions as orientation representation method. Empirical results show that all tested algorithms converge to the correct orientation even if the initial orientation is unknown