Modified stereo vision method for an unmanned ground vehicle

In recent years, automated robots are widely used in different fields of science and engineering such as industrial, rescue, surveillance and military applications. Among these automated machines, there are some robots which need to move around and navigate autonomously to perform their tasks. One o...

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Main Author: Samadi, Masoud
Format: Thesis
Language:English
Published: 2014
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Online Access:http://eprints.utm.my/id/eprint/50710/25/MasoudSamadiMFKE2014.pdf
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spelling my-utm-ep.507102020-07-09T01:07:48Z Modified stereo vision method for an unmanned ground vehicle 2014-03 Samadi, Masoud TK Electrical engineering. Electronics Nuclear engineering In recent years, automated robots are widely used in different fields of science and engineering such as industrial, rescue, surveillance and military applications. Among these automated machines, there are some robots which need to move around and navigate autonomously to perform their tasks. One of the crucial parts in these kinds of mobile robots which helps them to navigate autonomously is the environmental perception part. In order to retrieve information from the surroundings, a robot could use different types of sensor. Lately, stereo vision system has found its place in the environmental perception methods. This method has a great ability to provide 3D information of all the objects in the robots’ path. The main goal of this thesis is to build a stereo vision-based mobile robot which navigates autonomously and explores an unknown environment while avoiding collision with obstacles in its path. Within the scope of this thesis, a modified version of standard Census stereo vision algorithm is proposed to reduce the processing time of the existing method. A stereo Vision-Based robot is designed and prototyped to implement and test the proposed stereo vision method. In addition, dynamic path planning algorithm is employed to provide a collision free path for the robot. The proposed strategy is able to navigate the robot from its current position to the defined destination while avoiding the obstacles throughout an estimated path. The details of design and prototype of the autonomous mobile robot such as hardware and software developments are extensively described. The results obtained are compared with standard benchmark dataset and the evaluation shows 3.36% improvement in terms of accuracy, while the speed is about two times faster than standard Census method. Therefore, based on the empirical observation, the proposed modified Census algorithm makes the robot able to reach the destination point without colliding with any obstacle throughout a planned path. 2014-03 Thesis http://eprints.utm.my/id/eprint/50710/ http://eprints.utm.my/id/eprint/50710/25/MasoudSamadiMFKE2014.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:85884 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic TK Electrical engineering
Electronics Nuclear engineering
spellingShingle TK Electrical engineering
Electronics Nuclear engineering
Samadi, Masoud
Modified stereo vision method for an unmanned ground vehicle
description In recent years, automated robots are widely used in different fields of science and engineering such as industrial, rescue, surveillance and military applications. Among these automated machines, there are some robots which need to move around and navigate autonomously to perform their tasks. One of the crucial parts in these kinds of mobile robots which helps them to navigate autonomously is the environmental perception part. In order to retrieve information from the surroundings, a robot could use different types of sensor. Lately, stereo vision system has found its place in the environmental perception methods. This method has a great ability to provide 3D information of all the objects in the robots’ path. The main goal of this thesis is to build a stereo vision-based mobile robot which navigates autonomously and explores an unknown environment while avoiding collision with obstacles in its path. Within the scope of this thesis, a modified version of standard Census stereo vision algorithm is proposed to reduce the processing time of the existing method. A stereo Vision-Based robot is designed and prototyped to implement and test the proposed stereo vision method. In addition, dynamic path planning algorithm is employed to provide a collision free path for the robot. The proposed strategy is able to navigate the robot from its current position to the defined destination while avoiding the obstacles throughout an estimated path. The details of design and prototype of the autonomous mobile robot such as hardware and software developments are extensively described. The results obtained are compared with standard benchmark dataset and the evaluation shows 3.36% improvement in terms of accuracy, while the speed is about two times faster than standard Census method. Therefore, based on the empirical observation, the proposed modified Census algorithm makes the robot able to reach the destination point without colliding with any obstacle throughout a planned path.
format Thesis
qualification_level Master's degree
author Samadi, Masoud
author_facet Samadi, Masoud
author_sort Samadi, Masoud
title Modified stereo vision method for an unmanned ground vehicle
title_short Modified stereo vision method for an unmanned ground vehicle
title_full Modified stereo vision method for an unmanned ground vehicle
title_fullStr Modified stereo vision method for an unmanned ground vehicle
title_full_unstemmed Modified stereo vision method for an unmanned ground vehicle
title_sort modified stereo vision method for an unmanned ground vehicle
granting_institution Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department Faculty of Electrical Engineering
publishDate 2014
url http://eprints.utm.my/id/eprint/50710/25/MasoudSamadiMFKE2014.pdf
_version_ 1747817517564297216