Development of binocular vision guided mobility for autonomous vehicle

Unmanned Surface Vessels (USVs) or Autonomous Surface Vehicles (ASVs) are revolutionizing maritime activities. These self-operating boats use sensors like GPS, LiDAR, and cameras to move and make decisions on water without needing people. They're useful for a range of tasks, from military...

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Main Author: Lai, Tingfeng
Other Authors: Xie Ming
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2024
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Online Access:https://hdl.handle.net/10356/173435
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1734352024-02-10T16:51:44Z Development of binocular vision guided mobility for autonomous vehicle Lai, Tingfeng Xie Ming School of Mechanical and Aerospace Engineering mmxie@ntu.edu.sg Engineering Unmanned Surface Vessels (USVs) or Autonomous Surface Vehicles (ASVs) are revolutionizing maritime activities. These self-operating boats use sensors like GPS, LiDAR, and cameras to move and make decisions on water without needing people. They're useful for a range of tasks, from military patrols to oceanographic explorations. The Maritime RobotX Challenge is an important international competition held every two years at the university level. It's designed to promote the development of autonomous maritime robots. Students from around the world participate, creating new technologies and building global partnerships between universities and the industry. In this competition, a key goal is to create innovative USVs that can perform various tasks. Our research focuses on the development of a binocular vision system tailored for RobotX tasks - obstacle avoidance, path following, and autonomous docking. The project began with a new principle toward achieving a robust matching solution which leverages on the use and integration of top down image sampling strategy, hybrid feature extraction, and Restricted Coulomb Energy (RCE) neural network for cognition as well as recognition, finally utilizing stereo matching to derive three-dimensional coordinates. A preliminary version of the proposed solution has been implemented and tested with data from Maritime RobotX Challenge. Also, a Graphical User Interface (GUI) was designed to present and direct visualization platform for researchers and operators. Master's degree 2024-02-05T02:59:26Z 2024-02-05T02:59:26Z 2023 Thesis-Master by Coursework Lai, T. (2023). Development of binocular vision guided mobility for autonomous vehicle. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/173435 https://hdl.handle.net/10356/173435 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
spellingShingle Engineering
Lai, Tingfeng
Development of binocular vision guided mobility for autonomous vehicle
description Unmanned Surface Vessels (USVs) or Autonomous Surface Vehicles (ASVs) are revolutionizing maritime activities. These self-operating boats use sensors like GPS, LiDAR, and cameras to move and make decisions on water without needing people. They're useful for a range of tasks, from military patrols to oceanographic explorations. The Maritime RobotX Challenge is an important international competition held every two years at the university level. It's designed to promote the development of autonomous maritime robots. Students from around the world participate, creating new technologies and building global partnerships between universities and the industry. In this competition, a key goal is to create innovative USVs that can perform various tasks. Our research focuses on the development of a binocular vision system tailored for RobotX tasks - obstacle avoidance, path following, and autonomous docking. The project began with a new principle toward achieving a robust matching solution which leverages on the use and integration of top down image sampling strategy, hybrid feature extraction, and Restricted Coulomb Energy (RCE) neural network for cognition as well as recognition, finally utilizing stereo matching to derive three-dimensional coordinates. A preliminary version of the proposed solution has been implemented and tested with data from Maritime RobotX Challenge. Also, a Graphical User Interface (GUI) was designed to present and direct visualization platform for researchers and operators.
author2 Xie Ming
author_facet Xie Ming
Lai, Tingfeng
format Thesis-Master by Coursework
author Lai, Tingfeng
author_sort Lai, Tingfeng
title Development of binocular vision guided mobility for autonomous vehicle
title_short Development of binocular vision guided mobility for autonomous vehicle
title_full Development of binocular vision guided mobility for autonomous vehicle
title_fullStr Development of binocular vision guided mobility for autonomous vehicle
title_full_unstemmed Development of binocular vision guided mobility for autonomous vehicle
title_sort development of binocular vision guided mobility for autonomous vehicle
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/173435
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