Title :
Convergence analysis for extended Kalman filter based SLAM
Author :
Huang, Shoudong ; Dissanayake, Gamini
Author_Institution :
ARC Centre of Excellence for Autonomous Syst., Univ. of Technol., Sydney, NSW
Abstract :
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
Keywords :
Kalman filters; convergence; nonlinear filters; nonlinear systems; path planning; position control; robots; convergence analysis; extended Kalman filter; nonlinear two-dimensional SLAM; robot orientation error; simultaneous localisation and mapping; Australia; Computer errors; Content addressable storage; Convergence; Performance analysis; Predictive models; Robots; Simultaneous localization and mapping; Uncertainty; Upper bound;
Conference_Titel :
Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9505-0
DOI :
10.1109/ROBOT.2006.1641746
