Робастный алгоритм инерциальной видеонавигации с использованием относительных оценок положения
Abstract
The paper presents a loosely coupled approach for the improvement of state estimaion in autonomous inertial navigation, augmented via image_based relative motion estimation. The proposed approach uses a novel pose estimation technique based on the minimization of an entropy like cost function which is robust by nature to the presence of noise and outliers in the visual features. Experimental evidence of the performance of this approach is given and compared to a state of the art algorithm. An indirect Kalman filter is used for navigation in the framework of stochastic cloning. The robust relative pose estimation given by our novel technique is used to feed a relative position fix to the navigation filter. The simulation results are presented and compared with the results obtained via the classical RANSAC based direct linear transform approach.
About the Authors
Ф. Ди Корато
Университет Пизы
Italy
Italy
М. Инноченти
Университет Пизы
Italy
Italy
Л. Поллини
Университет Пизы
Italy
Italy
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, , . Giroskopiya i Navigatsiya. 2012;20(4):50-70. (In Russ.)
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