Observability analysis of navigation system using point-based visual and inertial sensors |
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Authors: | Guohu Feng Xinsheng Huang |
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Affiliation: | College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, China |
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Abstract: | A matrix Kalman filter (MKF) has been implemented for a navigation system using point-based visual and inertial sensors. The observability conditions have been proved by the observability rank criterion based on Lie derivatives. The conditions are: (a) at least one degree of rotational freedom is excited and (b) at least three observed points are not collinear where any two points are linearly independent. Experimental results have demonstrated that the proposed algorithm obtains the same accurate as the line-based algorithm. |
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Keywords: | Matrix Kalman filter Lie derivatives Observability of nonlinear systems Point feature Vision |
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