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    Human Autonomy Teaming for ROV Shared Control

    Source: Journal of Computing in Civil Engineering:;2024:;Volume ( 038 ):;issue: 004::page 04024015-1
    Author:
    Pengxiang Xia
    ,
    Tianyu Zhou
    ,
    Yang Ye
    ,
    Jing Du
    DOI: 10.1061/JCCEE5.CPENG-5756
    Publisher: ASCE
    Abstract: Remotely operated vehicle (ROV) is a widely used subsea vehicle in offshore oil and gas industries to assist in the development and inspection of offshore oil fields, given its agility, safety, and endurance. As the offshore industry and subsea engineering fields advance, the demands on ROV technology, particularly in terms of control accuracy and safety, have been greatly increasing. Traditional methods require ROV operators to be stationed on vessels in challenging conditions, relying on video streams that offer limited spatial information about the ROV working environment. All these factors make conventional joystick controls even harder for novices. This research aims to propose a novel approach to human-autonomy collaboration aiming to diminish the learning and operational burdens on operators. A virtual reality (VR)-based sensory augmentation and body motion teleoperation method was applied, which allows operators to teleoperate the ROV in a much more comfortable environment. An interactive user interface was developed to enable seamless engagement with the autonomous system and facilitate dynamic switching between human and autonomous controls. To assess the system, a human subject experiment was conducted to compare the performance of an inspection task between human control, full autonomy, and human autonomy teaming methods. The result indicated that our solution could enhance human understanding of the ROV work status as well as reduce human workload during operation.
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      Human Autonomy Teaming for ROV Shared Control

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4297347
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    contributor authorPengxiang Xia
    contributor authorTianyu Zhou
    contributor authorYang Ye
    contributor authorJing Du
    date accessioned2024-04-27T22:43:33Z
    date available2024-04-27T22:43:33Z
    date issued2024/07/01
    identifier other10.1061-JCCEE5.CPENG-5756.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4297347
    description abstractRemotely operated vehicle (ROV) is a widely used subsea vehicle in offshore oil and gas industries to assist in the development and inspection of offshore oil fields, given its agility, safety, and endurance. As the offshore industry and subsea engineering fields advance, the demands on ROV technology, particularly in terms of control accuracy and safety, have been greatly increasing. Traditional methods require ROV operators to be stationed on vessels in challenging conditions, relying on video streams that offer limited spatial information about the ROV working environment. All these factors make conventional joystick controls even harder for novices. This research aims to propose a novel approach to human-autonomy collaboration aiming to diminish the learning and operational burdens on operators. A virtual reality (VR)-based sensory augmentation and body motion teleoperation method was applied, which allows operators to teleoperate the ROV in a much more comfortable environment. An interactive user interface was developed to enable seamless engagement with the autonomous system and facilitate dynamic switching between human and autonomous controls. To assess the system, a human subject experiment was conducted to compare the performance of an inspection task between human control, full autonomy, and human autonomy teaming methods. The result indicated that our solution could enhance human understanding of the ROV work status as well as reduce human workload during operation.
    publisherASCE
    titleHuman Autonomy Teaming for ROV Shared Control
    typeJournal Article
    journal volume38
    journal issue4
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-5756
    journal fristpage04024015-1
    journal lastpage04024015-14
    page14
    treeJournal of Computing in Civil Engineering:;2024:;Volume ( 038 ):;issue: 004
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian