Edge-based features from onmidirectional images for robot localization

被引：0

作者：

Vlassis, N ^{[1
]}

Motomura, Y ^{[1
]}

Hara, I ^{[1
]}

Asoh, H ^{[1
]}

Matsui, T ^{[1
]}

机构：

[1] Univ Amsterdam, RWCP, Autonomous Learning Funct SNN, NL-1098 SJ Amsterdam, Netherlands

来源：

2001 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS I-IV, PROCEEDINGS | 2001年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a method for extracting low-dimensional features from omnidirectional Images to be used for robot localization and navigation. Edge detection is combined with thresholding to locate sharp edge pixels, the coordinates of which are led into a Parzen density estimator to compute the edge spatial density. The use of the Fast Fourier Transform makes this density estimate feasible in real-time,,while Principal Component Analysis further drops the dimensionality of the resulting feature vector to a manageable number. We show experimental results from a Nomad XR4000 robot in an office environment.

引用

页码：1579 / 1584

页数：6

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