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.
Original language | English |
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Pages | 218-223 |
Number of pages | 6 |
Publication status | Published - 2003 |
Externally published | Yes |
Event | 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States Duration: 2003 Oct 27 → 2003 Oct 31 |
Other
Other | 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems |
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Country/Territory | United States |
City | Las Vegas, NV |
Period | 03/10/27 → 03/10/31 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications