Analysis and improvement of the consistency of extended Kalman filter based SLAM

Guoquan P. Huang, Anastasios I. Mourikis, Stergios I. Roumeliotis

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

110 Scopus citations

Abstract

In this work, we study the inconsistency of EKF-based SLAM from the perspective of observability. We analytically prove that when the Jacobians of the state and measurement models are evaluated at the latest state estimates during every time step, the linearized error-state system model of the EKF-based SLAM has observable subspace of dimension higher than that of the actual, nonlinear, SLAM system. As a result, the covariance estimates of the EKF undergo reduction in directions of the state space where no information is available, which is a primary cause of inconsistency. To address this issue, a new "First Estimates Jacobian" (FEJ) EKF is proposed, which is shown to perform better in terms of consistency. In the FEJ-EKF, the filter Jacobians are calculated using the first-ever available estimates for each state variable, which insures that the observable subspace of the error-state system model is of the same dimension as that of the underlying nonlinear SLAM system. The theoretical analysis is validated through extensive simulations.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Robotics and Automation, ICRA 2008
Pages473-479
Number of pages7
DOIs
StatePublished - Sep 18 2008
Event2008 IEEE International Conference on Robotics and Automation, ICRA 2008 - Pasadena, CA, United States
Duration: May 19 2008May 23 2008

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other2008 IEEE International Conference on Robotics and Automation, ICRA 2008
CountryUnited States
CityPasadena, CA
Period5/19/085/23/08

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