On the consistency analysis of A-SLAM for UAV navigation

A. E. Oguz, Hakan Temeltas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

Simultaneous Localization and Mapping (SLAM) is a good choice for UAV navigation when both UAV's position and region map are not known. Due to nonlinearity of kinematic equations of a UAV, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are employed. In this study, EKF and UKF based A-SLAM concepts are discussed in details by presenting the formulations and simulation results. The UAV kinematic model and the state-observation models for EKF and UKF based A-SLAM methods are developed to analyze the filters' consistencies. Analysis during landmark observation exhibits an inconsistency in the form of a jagged UAV trajectory. It has been found that unobservable subspaces and the Jacobien matrices used for linearization are two major sources of the inconsistencies observed. UKF performs better in terms of filter consistency since it does not require the Jacobien matrix linearization.

Original languageEnglish
Title of host publicationUnmanned Systems Technology XVI
PublisherSPIE
ISBN (Print)9781628410211
DOIs
Publication statusPublished - 2014
EventUnmanned Systems Technology XVI - Baltimore, MD, United States
Duration: 6 May 20148 May 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9084
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceUnmanned Systems Technology XVI
Country/TerritoryUnited States
CityBaltimore, MD
Period6/05/148/05/14

Keywords

  • A-SLAM
  • Consistency
  • EKF
  • Kalman filter
  • SLAM
  • UKF

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