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• W75000147 abstract "In this paper we present a new method to address the monocular SLAM problem by a non-Gaussian filtering approach. In the proposed method, the distribution of a robot position is efficiently sampled based on the method offered by the unscented Kalman filter. Attached to each sample, for each landmark, a line segment is considered to represent the uncertainty of the landmark. In another word, the robot position distribution is acceptably assumed Gaussian and the distributions of landmarks are assumed to be uniform over line segments. We offer a near to optimal method to trim the line segments and reduce their uncertainties lengths at each time step. The high performance of the algorithm will be proved through simulation and experimental results." @default.
• W75000147 created "2016-06-24" @default.
• W75000147 creator A5057318202 @default.
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• W75000147 date "2013-01-01" @default.
• W75000147 modified "2023-10-16" @default.
• W75000147 title "A New Non-Gaussian Filtering Approach to Monocular SLAM Problem" @default.
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• W75000147 doi "https://doi.org/10.1007/978-3-642-40852-6_56" @default.
• W75000147 hasPublicationYear "2013" @default.
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