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 inProceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453) Vol. 1; pp. 218 - 223 vol.1
Main Authors Nakju Lett Doh, Wan Kyun Chung, SungOn Lee, SangRok Oh, BumJae You
Format Conference Proceeding
LanguageEnglish
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.
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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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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StartPage 218
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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