DocumentCode
2237080
Title
Results for outdoor-SLAM using sparse extended information filters
Author
Liu, Yufeng ; Thrun, Sebastian
Author_Institution
Sch. of Comput. Sci., Carnegie Mellon Univ., DC, USA
Volume
1
fYear
2003
fDate
14-19 Sept. 2003
Firstpage
1227
Abstract
In [Thrun, S., et al., 2001], we proposed the sparse extended information filter for efficiently solving the simultaneous localization and mapping (SLAM) problem. In this paper, we extend this algorithm to handle data association problems and report real-world results, obtained with an outdoor vehicle. We find that our approach performs favorably when compared to the extended Kalman filter solution from which it is derived.
Keywords
Kalman filters; information filters; maximum likelihood estimation; mobile robots; path planning; road vehicles; data association; extended Kalman filter; outdoor simultaneous localization; outdoor simultaneous mapping; real-world results; sparse extended information filters; Computational modeling; Computer science; Covariance matrix; Inertial navigation; Information filters; Matrix decomposition; Robot sensing systems; Simultaneous localization and mapping; Standards development; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on
ISSN
1050-4729
Print_ISBN
0-7803-7736-2
Type
conf
DOI
10.1109/ROBOT.2003.1241760
Filename
1241760
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