A robust general Voronoi graph based SLAM for a hyper symmetric environment
In this paper, an algorithm for hyper symmetric environment simultaneous localization and mapping (SLAM) is developed based on the generalized Voronoi graph. The hyper symmetric environment is a challenging environment for the SLAM and the most difficult problem on this is a data association. To red...
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Published in | Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453) Vol. 1; pp. 218 - 223 vol.1 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
2003
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Abstract | In this paper, an algorithm for hyper symmetric environment simultaneous localization and mapping (SLAM) is developed based on the generalized Voronoi graph. The hyper symmetric environment is a challenging environment for the SLAM and the most difficult problem on this is a data association. To redeem this problem, we propose three techniques. The first one is a breadth first node navigation algorithm which highly reduces the complexity of the data association. The second scheme is an odometry calibration method which converts untrustable odometry into reliable one. The third method is a multi layered data association scheme. We integrate above three techniques into one framework and propose a SLAM algorithm for the hyper symmetric environment. The simulation result shows that the proposed algorithm can successfully cover a large hyper symmetric environment under 20% odometry uncertainty. |
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AbstractList | In this paper, an algorithm for hyper symmetric environment simultaneous localization and mapping (SLAM) is developed based on the generalized Voronoi graph. The hyper symmetric environment is a challenging environment for the SLAM and the most difficult problem on this is a data association. To redeem this problem, we propose three techniques. The first one is a breadth first node navigation algorithm which highly reduces the complexity of the data association. The second scheme is an odometry calibration method which converts untrustable odometry into reliable one. The third method is a multi layered data association scheme. We integrate above three techniques into one framework and propose a SLAM algorithm for the hyper symmetric environment. The simulation result shows that the proposed algorithm can successfully cover a large hyper symmetric environment under 20% odometry uncertainty. |
Author | SungOn Lee SangRok Oh BumJae You Wan Kyun Chung Nakju Lett Doh |
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PublicationTitle | Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453) |
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Snippet | In this paper, an algorithm for hyper symmetric environment simultaneous localization and mapping (SLAM) is developed based on the generalized Voronoi graph.... |
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SubjectTerms | Biomechatronics Calibration Intelligent systems Mechanical engineering Navigation Robots Robustness Simultaneous localization and mapping Topology Uncertainty |
Title | A robust general Voronoi graph based SLAM for a hyper symmetric environment |
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