Joint underwater mapping with acoustic and optical Iimages

This thesis is developed within the context of the IURBI project [1], which seeks to develop an intelligent AUV capable of real-time seafloor analysis and adaptive mission planning (Figure 1.1). A fundamental prerequisite for such autonomous capabilities is the ability to robustly align and fuse sen...

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Detalles Bibliográficos
Autor: Philip-Ifabiyi, Precious
Tipo de recurso: tesis de maestría
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/28379
Acceso en línea:http://hdl.handle.net/10256/28379
https://hdl.handle.net/10256/28379
Access Level:acceso abierto
Palabra clave:Autonomous Underwater Vehicles
Autonomous Underwater Vehicles -- Navigation systems
Vehicles submergibles autònoms -- Sistemes de navigació
Digital mapping
Cartografia digital
SLAM
Sonar
Sonar (Navegació)
Algorismes
Algorithms
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spelling Joint underwater mapping with acoustic and optical IimagesPhilip-Ifabiyi, PreciousAutonomous Underwater VehiclesAutonomous Underwater Vehicles -- Navigation systemsVehicles submergibles autònoms -- Sistemes de navigacióDigital mappingCartografia digitalSLAMSonarSonar (Navegació)AlgorismesAlgorithmsThis thesis is developed within the context of the IURBI project [1], which seeks to develop an intelligent AUV capable of real-time seafloor analysis and adaptive mission planning (Figure 1.1). A fundamental prerequisite for such autonomous capabilities is the ability to robustly align and fuse sensor data from multiple sources and surveys into a single, coherent model. This thesis addresses that foundational challenge by developing a comprehensive offline framework for multi-session, multimodal map alignment. The primary objectives of this thesis are to: – Develop a robust and flexible framework for the alignment and integration of side-scan sonar and optical imagery acquired in single or multiple sessions by AUVs, towfish, or ROVs. – Formulate and implement a factor graph optimization approach to jointly re fine vehicle trajectories and sensor alignments across multiple sessions and modalities, accommodating the inherent uncertainties in underwater navigation. – Evaluate the performance of the proposed methodology using real-world under water datasets, assessing its accuracy, robustness, and practical applicability. The scope of this work encompasses the offline processing and alignment of pre viously collected side-scan sonar and optical image datasets. While initial navigation data from the AUV/ROV is assumed to be available, this work specifically focuses on refining these initial pose estimates to achieve precise multimodal and multi-session co-registration.9Universitat de Girona. Institut de Recerca en Visió per Computador i Robòtica2025info:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10256/28379https://hdl.handle.net/10256/28379Erasmus Mundus Joint Master in Intelligent Field Robotic Systems (IFROS)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10256/283792026-05-29T05:05:01Z
dc.title.none.fl_str_mv Joint underwater mapping with acoustic and optical Iimages
title Joint underwater mapping with acoustic and optical Iimages
spellingShingle Joint underwater mapping with acoustic and optical Iimages
Philip-Ifabiyi, Precious
Autonomous Underwater Vehicles
Autonomous Underwater Vehicles -- Navigation systems
Vehicles submergibles autònoms -- Sistemes de navigació
Digital mapping
Cartografia digital
SLAM
Sonar
Sonar (Navegació)
Algorismes
Algorithms
title_short Joint underwater mapping with acoustic and optical Iimages
title_full Joint underwater mapping with acoustic and optical Iimages
title_fullStr Joint underwater mapping with acoustic and optical Iimages
title_full_unstemmed Joint underwater mapping with acoustic and optical Iimages
title_sort Joint underwater mapping with acoustic and optical Iimages
dc.creator.none.fl_str_mv Philip-Ifabiyi, Precious
author Philip-Ifabiyi, Precious
author_facet Philip-Ifabiyi, Precious
author_role author
dc.subject.none.fl_str_mv Autonomous Underwater Vehicles
Autonomous Underwater Vehicles -- Navigation systems
Vehicles submergibles autònoms -- Sistemes de navigació
Digital mapping
Cartografia digital
SLAM
Sonar
Sonar (Navegació)
Algorismes
Algorithms
topic Autonomous Underwater Vehicles
Autonomous Underwater Vehicles -- Navigation systems
Vehicles submergibles autònoms -- Sistemes de navigació
Digital mapping
Cartografia digital
SLAM
Sonar
Sonar (Navegació)
Algorismes
Algorithms
description This thesis is developed within the context of the IURBI project [1], which seeks to develop an intelligent AUV capable of real-time seafloor analysis and adaptive mission planning (Figure 1.1). A fundamental prerequisite for such autonomous capabilities is the ability to robustly align and fuse sensor data from multiple sources and surveys into a single, coherent model. This thesis addresses that foundational challenge by developing a comprehensive offline framework for multi-session, multimodal map alignment. The primary objectives of this thesis are to: – Develop a robust and flexible framework for the alignment and integration of side-scan sonar and optical imagery acquired in single or multiple sessions by AUVs, towfish, or ROVs. – Formulate and implement a factor graph optimization approach to jointly re fine vehicle trajectories and sensor alignments across multiple sessions and modalities, accommodating the inherent uncertainties in underwater navigation. – Evaluate the performance of the proposed methodology using real-world under water datasets, assessing its accuracy, robustness, and practical applicability. The scope of this work encompasses the offline processing and alignment of pre viously collected side-scan sonar and optical image datasets. While initial navigation data from the AUV/ROV is assumed to be available, this work specifically focuses on refining these initial pose estimates to achieve precise multimodal and multi-session co-registration.
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/28379
https://hdl.handle.net/10256/28379
url http://hdl.handle.net/10256/28379
https://hdl.handle.net/10256/28379
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat de Girona. Institut de Recerca en Visió per Computador i Robòtica
publisher.none.fl_str_mv Universitat de Girona. Institut de Recerca en Visió per Computador i Robòtica
dc.source.none.fl_str_mv Erasmus Mundus Joint Master in Intelligent Field Robotic Systems (IFROS)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.81155

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