Overhead vision system for mobile robot orientation detection

Robot cooperation and coordination is absolutely necessary in many industrial applications. The computation of a mobile robot position and orientation is a common task in the area of computing vision and image processing. For a successful application, it is important that the position and orientatio...

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Main Author:	Fadzilah, Hashim
Format:	Thesis
Language:	English
Subjects:	Mobile robot Neural network Vision system
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/12180/1/p.1-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/12180/2/Full%20Text.pdf
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id	my-unimap-12180
record_format	uketd_dc
spelling	my-unimap-121802011-06-05T04:30:31Z Overhead vision system for mobile robot orientation detection Fadzilah, Hashim Robot cooperation and coordination is absolutely necessary in many industrial applications. The computation of a mobile robot position and orientation is a common task in the area of computing vision and image processing. For a successful application, it is important that the position and orientation of the mobile robot are properly determined. Computing the orientation is not a straightforward technique. Number of methods has already been studied by many researchers. These methods include the concepts of geometric moments, complex moments, and principal component analysis. In this work, a simple procedure for determining the orientation of the mobile robot using overhead vision system is presented and analysed. Cameras are used to capture the images of mobile robot at various orientations. The images are preprocessed and important features are extracted to be used in the proposed methods. In this research, simple methods to extract the features from the preprocessed images are developed. The extracted features are then used as the inputs to a simple feed forward neural network. The orientation of each image is measured manually and used as a target vector. A simple neural network model is developed to estimate the orientation of the mobile robot. Simulation results show that the proposed algorithms can be used to estimate the orientation of the mobile robot accurately. Universiti Malaysia Perlis 2010 Thesis en http://dspace.unimap.edu.my/123456789/12180 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/12180/3/license.txt 6d85309ac2d6010b51a3dbb867347884 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/12180/1/p.1-24.pdf 4f0e59af857a15070ec31bc51bd5d6a9 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/12180/2/Full%20Text.pdf fd531d273844d977783ac24b9eebb55b Mobile robot Neural network Vision system School of Computer & Communication Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
topic	Mobile robot Neural network Vision system
spellingShingle	Mobile robot Neural network Vision system Fadzilah, Hashim Overhead vision system for mobile robot orientation detection
description	Robot cooperation and coordination is absolutely necessary in many industrial applications. The computation of a mobile robot position and orientation is a common task in the area of computing vision and image processing. For a successful application, it is important that the position and orientation of the mobile robot are properly determined. Computing the orientation is not a straightforward technique. Number of methods has already been studied by many researchers. These methods include the concepts of geometric moments, complex moments, and principal component analysis. In this work, a simple procedure for determining the orientation of the mobile robot using overhead vision system is presented and analysed. Cameras are used to capture the images of mobile robot at various orientations. The images are preprocessed and important features are extracted to be used in the proposed methods. In this research, simple methods to extract the features from the preprocessed images are developed. The extracted features are then used as the inputs to a simple feed forward neural network. The orientation of each image is measured manually and used as a target vector. A simple neural network model is developed to estimate the orientation of the mobile robot. Simulation results show that the proposed algorithms can be used to estimate the orientation of the mobile robot accurately.
format	Thesis
author	Fadzilah, Hashim
author_facet	Fadzilah, Hashim
author_sort	Fadzilah, Hashim
title	Overhead vision system for mobile robot orientation detection
title_short	Overhead vision system for mobile robot orientation detection
title_full	Overhead vision system for mobile robot orientation detection
title_fullStr	Overhead vision system for mobile robot orientation detection
title_full_unstemmed	Overhead vision system for mobile robot orientation detection
title_sort	overhead vision system for mobile robot orientation detection
granting_institution	Universiti Malaysia Perlis
granting_department	School of Computer & Communication Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/12180/1/p.1-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/12180/2/Full%20Text.pdf
_version_	1747836758737813504

Overhead vision system for mobile robot orientation detection

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