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The Kalman filter is considered as an optimal filter with the hypothesis of gaussian noise and linear model. For nonlinear model several approaches have been proposed and Unscented Kalman Filter (UKF) seems to be one of the most accurate. In this study, we wonder if an appropriate constraint can enhance the efficiency of UKF. We propose a new algorithm called Constrained Sigma Points (CGS) that constrained...
With the increasing percentage of embedded devices dedicated to analyse motion (robotic, IoT), it is crucial to assess which nonlinear fusion algorithm fits to a given application. We wonder if it is possible to design a framework for an extensive comparison of attitude fusion algorithms. In a simulated environment, we tested different patterns of motion, different types of noise and different algorithms,...
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