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

fYear

2006

fDate

15-19 May 2006

Firstpage

412

Lastpage

417

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1050-4729

Print_ISBN

0-7803-9505-0

Type

conf

DOI

10.1109/ROBOT.2006.1641746

Filename

1641746