Positioning

Volume 4, Issue 1 (February 2013)

ISSN Print: 2150-850X   ISSN Online: 2150-8526

Google-based Impact Factor: 1  Citations  

Correction of Inertial Navigation System’s Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map

HTML  XML Download Download as PDF (Size: 4174KB)  PP. 89-108  
DOI: 10.4236/pos.2013.41010    5,033 Downloads   8,358 Views  Citations

ABSTRACT

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.

Share and Cite:

Kupervasser, O. and Rubinstein, A. (2013) Correction of Inertial Navigation System’s Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map. Positioning, 4, 89-108. doi: 10.4236/pos.2013.41010.

Cited by

[1] A method for stabilization of drone flight controlled by autopilot with time delay
2020
[2] ALGORITHMS DEVELOPED FOR TWO PROTOTYPES OF AIRBORNE VISION-BASED CONTROL OF GROUND ROBOTS
2020
[3] Using Deep Learning for Visual Navigation of Drone with Respect to 3D Ground Objects
2020
[4] АВТОНОМНАЯ ПЕРСОНАЛЬНАЯ ИНФОРМАЦИОННО- ИЗМЕРИТЕЛЬНАЯ СИСТЕМА НАЗЕМНОГО ПОЗИЦИОНИРОВАНИЯ С КОРРЕКЦИЕЙ УГЛОВ НАКЛОНА ПО ОПОРНОЙ ПОВЕРХНОСТИ
THESIS, 2019
[5] A method for stabilization of ground robot path controlled by airborne autopilot with time delay
… workshop on Functional …, 2019
[6] A positivity-based approach to delay-dependent stability of systems of second order equations
2019
[7] Autopilot to maintain movement of a drone in a vertical plane at a constant height in the presence of vision-based navigation
2018
[8] Robust positioning of drones for land use monitoring in strong terrain relief using vision-based navigation
2018
[9] Localization of Airborne Platform Using Digital Elevation Model With Adaptive Weighting Inspired by Information Theory
2018

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.