Fusion of Fixation And Odometry for Vehicle Navigation
Fusion of Fixation and Odometry for Vehicle Navigation.
In ICRA, 1638-1643, 1999
Online Version
A pdf version is available for download.
Abstract
This paper deals with the problem of determining the position and orientation of an autonomous guided vehicle (AGV) by fusing odometry with the information provided by a vision system. The main idea is to exploit the ability of pointing a camera in different directions, to fixate on a point of the environment while the AGV is moving. By fixating on a landmark, one can improve the navigation accuracy even if the scene coordinates of the landmark are unknown. This is a major improvement over previous methods which assume that the coordinates of the landmark are known, since any point of the observed scene can be selected as a landmark, and not just pre-measured points. This work argues that fixation is basically a simpler procedure than previously mentioned methods. The simplification comes from the fact that only one point needs to be tracked as opposed to multiple points in other methods. This disposes of the need to be able to identify which of the landmarks is currently being tracked, through a matching algorithm or by other means. We support our findings with both experimental and simulation results.
Keywords
- Navigation,
- Pattern Matching,
- Algorithms,
- Computer Vision,
- Computational Methods,
- Computer Simulation.
Co-authors
Bibtex Entry
@inproceedings{AdamRR99i,
title = {Fusion of Fixation and Odometry for Vehicle Navigation.},
author = {Amit Adam and Ehud Rivlin and Hector Rotstein},
year = {1999},
booktitle = {ICRA},
pages = {1638-1643},
keywords = {Navigation; Pattern matching; Algorithms; Computer vision; Computational methods; Computer simulation},
abstract = {This paper deals with the problem of determining the position and orientation of an autonomous guided vehicle (AGV) by fusing odometry with the information provided by a vision system. The main idea is to exploit the ability of pointing a camera in different directions, to fixate on a point of the environment while the AGV is moving. By fixating on a landmark, one can improve the navigation accuracy even if the scene coordinates of the landmark are unknown. This is a major improvement over previous methods which assume that the coordinates of the landmark are known, since any point of the observed scene can be selected as a landmark, and not just pre-measured points. This work argues that fixation is basically a simpler procedure than previously mentioned methods. The simplification comes from the fact that only one point needs to be tracked as opposed to multiple points in other methods. This disposes of the need to be able to identify which of the landmarks is currently being tracked, through a matching algorithm or by other means. We support our findings with both experimental and simulation results.}
}