MARINE VEHICLE CHARACTERIZATION AND IMPLEMENTING VARIOUS LEVELS OF AUTONOMY

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dc.contributor.advisorKrieg, Michael
dc.contributor.authorNg, Patrick Julian
dc.contributor.departmentMechanical Engineering
dc.date.accessioned2025-02-20T22:36:48Z
dc.date.available2025-02-20T22:36:48Z
dc.date.issued2024
dc.description.degreeM.S.
dc.identifier.urihttps://hdl.handle.net/10125/110205
dc.subjectRobotics
dc.subjectOcean engineering
dc.subjectMechanical engineering
dc.subjectControl
dc.subjectMarine Robotics
dc.subjectRemotely Operated Vehicle (ROV)
dc.subjectRobot Operating System (ROS)
dc.subjectSystem Identification
dc.subjectUnmanned Underwater Vehicle (UUV)
dc.titleMARINE VEHICLE CHARACTERIZATION AND IMPLEMENTING VARIOUS LEVELS OF AUTONOMY
dc.typeThesis
dcterms.abstractRemotely operated vehicles (ROVs) are marine submersible robots that serve a variety of purposes in industry and research. These unmanned vessels harness human judgment and precision to perform tasks within extreme environments like the deep sea, polar, and volcanic regions of the ocean. Some examples of their usages are to survey the ocean floor, maintain pipelines and collect scientific data in the form of sediment and hydrothermal vent plume samples and optical observations of marine wildlife. Training of ROV pilots is typically very expensive and time-consuming because of the highly specialized skill requirements. A novel system was proposed by collaborators from the University of Florida (UF) and the University of Hawai‘i at M ̄anoa (UHM) for piloting ROVs with an intuitive augmented/virtual reality (AR/VR) interface that uses a hybrid autopilot. To demonstrate the feasibility of this system the group at UHM altered the ArduSub firmware of the commercially available BlueROV2 (BROV2) Heavy to enable model-based quantitative control. Error feedback control for the hybrid autopilot was implemented using Robot Operating System (ROS) in a modular manner that enabled various levels of autonomy to assist ROV pilots. Alongside the development of the custom firmware and hybrid autopilot, the software-in-the-loop (SITL) simulation environment was also updated with an experimentally determined hydrodynamic model using onboard sensor- based system identification techniques As much as sixty percent improvement of relative error when predicting vehicle behavior compared to the original SITL model. The calibration process of the hybrid autopilot involved iteratively cycling between SITL and water tank testing. It was demonstrated that this procedure was an effective method for achieving precision control of the BROV2.
dcterms.extent91 pages
dcterms.languageen
dcterms.publisherUniversity of Hawai'i at Manoa
dcterms.rightsAll UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.
dcterms.typeText
local.identifier.alturihttp://dissertations.umi.com/hawii:12384

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