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
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;
Conference_Titel :
Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on
Print_ISBN :
0-7803-7736-2
DOI :
10.1109/ROBOT.2003.1241760
