Paper
3 June 2014 On the consistency analysis of A-SLAM for UAV navigation
Author Affiliations +
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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Ersan Oguz and Hakan Temeltas "On the consistency analysis of A-SLAM for UAV navigation", Proc. SPIE 9084, Unmanned Systems Technology XVI, 90840R (3 June 2014); https://doi.org/10.1117/12.2053258
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Unmanned aerial vehicles

Error analysis

Filtering (signal processing)

Kinematics

Matrices

Nonlinear filtering

Process modeling

Back to Top