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

被引：49

作者：

Tamimi, Hashem ^{[1
]}

Andreasson, Henrik

Treptow, Andre

Duckett, Tom

Zell, Andreas

机构：

[1] Univ Tubingen, Dept Comp Sci, D-72076 Tubingen, Germany

[2] Univ Orebro, Dept Technol, AASS, S-70182 Orebro, Sweden

[3] Lincoln Univ, Dept Comp & Informat, Lincoln LN6 7TS, England

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 2006年 / 54卷 / 09期

关键词：

robot localization; Scale Invariant Feature Transform; omnidirectional vision; Particle Filter;

D O I：

10.1016/j.robot.2006.04.018

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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. (C) 2006 Elsevier B.V. All rights reserved.

引用

页码：758 / 765

页数：8

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