Localization of mobile robots with omnidirectional vision using Particle Filter and iterative SIFT

Tamimi, Hashem and Andreasson, Henrik and Treptow, André and Duckett, Tom and Zell, Andreas (2006) Localization of mobile robots with omnidirectional vision using Particle Filter and iterative SIFT. Robotics and Autonomous Systems, 54 (9). pp. 758-765. ISSN 0921-8890

Full content URL: http://dx.doi.org/10.1016/j.robot.2006.04.018

Documents
Tamimi Andreasson Treptow Duckett Zell 2006.pdf

Request a copy
[img] PDF
Tamimi Andreasson Treptow Duckett Zell 2006.pdf - Whole Document
Restricted to Repository staff only

1MB
Item Type:Article
Item Status:Live Archive

Abstract

The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot localization. Still, the number of features extracted with this approach is immense, especially when dealing with omnidirectional vision. In this work, we propose a new approach that reduces the number of features generated by SIFT as well as their extraction and matching time. With the help of a Particle Filter, we demonstrate that we can still localize the mobile robot accurately with a lower number of features.

Keywords:Robot localization, Scale Invariant Feature Transform, Omnidirectional vision, Particle Filter
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
Divisions:College of Science > School of Computer Science
ID Code:28030
Deposited On:28 Jul 2017 09:42

Repository Staff Only: item control page