Analysis of positioning uncertainty in Simultaneous Localization and Mapping (SLAM)

Anastasios I. Mourikis, Stergios I. Roumeliotis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

This paper studies the time evolution of the covariance of the position estimates in single-robot Simultaneous Localization And Mapping (SLAM). A closed-form expression is derived, that establishes a functional relation between the noise parameters of the robot's proprioceptive and exteroceptive sensors, the number of features being mapped, and the attainable accuracy of SLAM. Furthermore, it is demonstrated how prior information about the spatial density of landmarks can be utilized in order to compute a tight upper bound on the expected covariance of the positioning errors. The derived closed-form expressions enable the prediction of SLAM positioning performance, without resorting to extensive simulations, and thus offer an analytical tool for determining the sensor characteristics required to achieve a desired degree of accuracy. Simulation experiments are conducted, that corroborate the presented theoretical analysis.

Original languageEnglish (US)
Title of host publication2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Pages13-20
Number of pages8
StatePublished - Dec 1 2004
Event2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - Sendai, Japan
Duration: Sep 28 2004Oct 2 2004

Publication series

Name2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Volume1

Other

Other2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Country/TerritoryJapan
CitySendai
Period9/28/0410/2/04

Fingerprint

Dive into the research topics of 'Analysis of positioning uncertainty in Simultaneous Localization and Mapping (SLAM)'. Together they form a unique fingerprint.

Cite this