Novel Information Matrix Sparsification Approach for Practical Implementation of Simultaneous Localization and Mapping
Simultaneous localization and mapping (SLAM) is a fundamental issue in mobile robotics because it is the basis of higher-level tasks of robots. Recently, more and more research has been proposed that aims to enhance the efficiency of SLAM solutions from the viewpoint of the information
matrix. This paper presents a novel, efficient SLAM approach by using the characters of the information matrix. Our approach eliminates many of the elements in the information matrix while maintaining the consistency. The large complex environment simulation, as well as outdoor car park experiment
verifies the validity of our approach. The proposed sparsification method provides an efficient way to obtain a consistent estimation with provable upper bounds of sparsification errors.
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Document Type: Research Article
Department of Computer Science and Systems Engineering, Graduate School of Engineering, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Japan;, Email: [email protected]
New Huadu Cooperation Limited, No. 100, Century Avenue, Pudong New Area, Shanghai 200-120, P. R. China
Department of Automation, School of Electronic, Information and Electrical Engineering, Shanghai Jiaotong University, 800 Dongchuan Road, Shanghai 200-240, P. R. China
Department of Computer Science and Systems Engineering, Graduate School of Engineering, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Japan
Publication date: 01 April 2010