AB  - The main contribution of this paper is a theoretical analysis of the Extended Kalman Filter (EKF) based solution to the simultaneous localisation and mapping (SLAM) problem. The convergence properties for the general nonlinear two-dimensional SLAM are provided. The proofs clearly show that the robot orientation error has a significant effect on the limit and/or the lower bound of the uncertainty of the landmark location estimates. Furthermore, some insights to the performance of EKF SLAM and a theoretical analysis on the inconsistencies in EKF SLAM that have been recently observed are given. © 2006 IEEE.
AU  - Shoudong, H
AU  - Dissanayake, G
DA  - 2006/12/27
DO  - 10.1109/ROBOT.2006.1641746
EP  - 417
JO  - Proceedings - IEEE International Conference on Robotics and Automation
PY  - 2006/12/27
SP  - 412
TI  - Convergence analysis for extended Kalman filter based SLAM
VL  - 2006
Y1  - 2006/12/27
Y2  - 2026/05/25
ER  -