The Spherical Simplex Unscented Transformation for a FastSLAM
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概要
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This paper proposes an unscented transformation for a FastSLAM framework. The unscented transformation is used to estimate robot poses in conjunction with generic particle filter used in standard FastSLAM framework. This method can estimate robot poses more consistently and accurately than the use of single standard particle filters, especially when involving highly nonlinear models or non-Gaussian noises. In addition, our algorithm avoids the calculation of the Jacobian for motion model which could be extremely difficult for high order systems. We proposed two different sampling strategies known as a symmetrical and a spherical simplex to unscented transformation to estimate robot poses in FastSLAM framework. Simulation results are shown to validate the performance goals.
- 一般社団法人 日本機械学会の論文
著者
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Watanabe Keigo
Department Of Advanced Systems Control Engineering Graduate School Of Science And Engineering Saga U
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MAEYAMA Shoichi
Department of Intelligent Mechanical Systems, Graduate School of Natural Science and Technology, Okayama University
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RAZALI Saifudin
Department of Intelligent Mechanical Systems, Graduate School of Natural Science and Technology, Okayama University
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