FW-HTF-R/Collaborative Research: Human-Robot Sensory Transfer for Worker Productivity, Training, and Quality of Life in Remote Undersea Inspection and Construction Tasks

FW-HTF-R/合作研究:人机感官传递可提高远程海底检查和施工任务中工人的生产力、培训和生活质量

基本信息

  • 批准号:
    2128924
  • 负责人:
  • 金额:
    $ 40.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-12-01 至 2025-11-30
  • 项目状态:
    未结题

项目摘要

This Future of Work at the Human-Technology Frontier: Core Research project will create a novel interface for remote operation of undersea robots and customize it to the needs of offshore industries and workers. The novel interface integrates robot sensor readings and high-speed predictive simulations of hydrodynamic forces to create an immersive mixed reality (MR) display. In addition to augmented video images of the robot's surroundings, the interface converts measurements of water flow rates, hydrostatic pressure, ambient temperature, and other variables into tactile sensations for the operator. Likewise, the interface will render natural movements of the operator's body into control commands to the robot. The goal is human-robot "sensory transfer," that is, seamless translation of perceptions and actions between the operator and the robot. The goal of this project is to develop and match the capabilities of the interface to industry and worker needs. One anticipated benefit is to reduce the extensive training currently required for operators, thereby increasing access to these jobs while reducing industry training expenses and downtime due to personnel shortages. The project will study the most effective way to improve worker performance, safety, and quality of life, and by requiring a diverse set of subjects, will show how such human-robot interfaces can expand economic opportunity to broad sections of society. The interface can also be used in a purely virtual mode as a training tool. The project will examine the use of this capability to recruit workers from adjacent fields, such as construction. Offshore applications that would directly benefit from this project include subsea infrastructure inspection, geological surveys, marine habitat monitoring, pollution assessments, ship-hull inspections, unexploded ordnance surveys, contraband detection, aquaculture monitoring, search and rescue, and archaeological exploration and surveys. An increase in extreme weather and rising sea levels will place increasing demands on offshore operations to protect and repair coastal damage. Similarly offshore sustainable energy infrastructure such as wind, wave, or tidal generators will increase the demand for undersea inspection, construction, and maintenance.This project will reconceptualize future subsea industry by advancing knowledge of underwater Human-Robot Interaction (HRI) in under-explored subsea workplaces, illuminating socioeconomic features and adult-learning needs of workforce transformation to subsea industry, and establishing academia-industry-government partnerships for improving performance, safety, and societal outcomes of subsea works. Novel human-robot sensory transfer methods are suggested for reliability against conditions unique to subsea. These methods will support fast and accurate reconstruction of subsea workplaces. MR will be used to generate human-perceivable simulation of remote subsea workplaces in real time based on feedback from a novel robotic sensing and data transmission system. Motion capture will be created for easier navigation of remotely operated vehicles (ROVs). This research will establish new knowledge on motivational and educational determinants of introducing easy-to-use collaborative ROVs as part of a transformative workforce for future subsea robot operations, through extensive participation from industrial partners. The assessment will integrate techniques from psychometric and behavioral sciences as well as engineering and human factors. The work will also pioneer the development of a future subsea job framework for integration of ROVs into a participatory delivery of core subsea services. The economic benefits of robotic adoption will be estimated based on demand projection and elasticity estimation. This research will transform the frontiers of human-technology partnership in the context of the future subsea industry, reposition workforce threatened by automation in other domains, enhance future workers’ safety and well-being, and improve subsea operation performance, thus enhancing the long-term sustainable ocean exploration.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
人类技术前沿的工作未来:核心研究项目将为海底机器人的远程操作创建一个新颖的界面,并根据海上工业和工人的需求进行定制。该新颖的界面集成了机器人传感器读数和流体动力的高速预测模拟,以创建身临其境的混合现实(MR)显示。除了机器人周围环境的增强视频图像之外,该界面还将水流速率、静水压力、环境温度和其他变量的测量结果转换为操作员的触觉。同样,该界面会将操作员身体的自然运动转化为机器人的控制命令。目标是人机“感官传递”,即操作员和机器人之间感知和动作的无缝转换。该项目的目标是开发接口功能并将其与行业和工人的需求相匹配。预期的好处之一是减少操作员目前所需的大量培训,从而增加获得这些工作的机会,同时减少行业培训费用和因人员短缺而导致的停机时间。该项目将研究提高工人绩效、安全和生活质量的最有效方法,并通过要求不同的主题,将展示这种人机界面如何将经济机会扩大到社会各阶层。该界面还可以在纯虚拟模式下用作培训工具。该项目将研究如何利用这种能力从建筑等邻近领域招聘工人。将直接受益于该项目的海上应用包括海底基础设施检查、地质调查、海洋栖息地监测、污染评估、船体检查、未爆炸弹药调查、违禁品检测、水产养殖监测、搜索和救援以及考古勘探和调查。极端天气的增加和海平面上升将对海上作业保护和修复沿海破坏提出越来越高的要求。同样,风力、波浪或潮汐发电机等海上可持续能源基础设施将增加对海底检查、建设和维护的需求。该项目将通过在未开发的海底工作场所中推进水下人机交互(HRI)知识,阐明社会经济特征和劳动力向海底行业转型的成人学习需求,并建立未来海底工业的概念。 学术界、工业界和政府之间的伙伴关系,以提高海底工程的性能、安全性和社会成果。建议采用新颖的人机感觉传递方法,以确保在海底特有条件下的可靠性。这些方法将支持快速、准确地重建海底工作场所。 MR 将用于根据新型机器人传感和数据传输系统的反馈,实时生成远程海底工作场所的人类可感知模拟。创建动作捕捉是为了更轻松地遥控潜水器 (ROV) 导航。这项研究将通过工业合作伙伴的广泛参与,建立关于引入易于使用的协作式 ROV 作为未来海底机器人操作变革劳动力的一部分的激励和教育决定因素的新知识。该评估将整合心理测量和行为科学以及工程和人为因素的技术。这项工作还将开创未来海底作业框架的开发,将 ROV 整合到参与式提供核心海底服务中。机器人采用的经济效益将根据需求预测和弹性估计进行估计。这项研究将改变未来海底行业背景下的人与技术伙伴关系的前沿,重新定位其他领域受自动化威胁的劳动力,提高未来工人的安全和福祉,并提高海底作业绩效,从而增强长期可持续的海洋勘探。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
VR-Based Haptic Simulator for Subsea Robot Teleoperations
  • DOI:
    10.1061/9780784483893.126
  • 发表时间:
    2022-05
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Fang Xu;Qi Zhu;Shuai Li;Zhuoyuan Song;Jing Du
  • 通讯作者:
    Fang Xu;Qi Zhu;Shuai Li;Zhuoyuan Song;Jing Du
Virtual Telepresence for the Future of ROV Teleoperations: Opportunities and Challenges
ROV 远程操作未来的虚拟远程呈现:机遇与挑战
  • DOI:
    10.5957/tos-2022-015
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Xia, Pengxiang;McSweeney, Kevin;Wen, Feng;Song, Zhuoyuan;Krieg, Michael;Li, Shuai;Yu, Xiao;Crippen, Kent;Adams, Jonathan;Du, Eric Jing
  • 通讯作者:
    Du, Eric Jing
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Michael Krieg其他文献

Pharmacokinetic and pharmacodynamic evaluation of fluticasone propionate after inhaled administration
丙酸氟替卡松吸入后的药动学和药效学评价
  • DOI:
    10.1007/s002280050407
  • 发表时间:
    1998
  • 期刊:
  • 影响因子:
    2.9
  • 作者:
    H. Möllmann;M. Wagner;B. Meibohm;Günther Hochhaus;J. Barth;Ricarda Stöckmann;Michael Krieg;Heike Weisser;C. Falcoz;Hartmut Derendorf
  • 通讯作者:
    Hartmut Derendorf
Pharmacokinetics and Rectal Bioavailability of Hydrocortisone Acetate
  • DOI:
    10.1002/jps.2600800906
  • 发表时间:
    1991-09-01
  • 期刊:
  • 影响因子:
  • 作者:
    Helmut Möllmann;Jürgen Barth;Carsten Möllmann;Sabine Tunn;Michael Krieg;Hartmut Derendorf
  • 通讯作者:
    Hartmut Derendorf
No Climate-Resilient Society Without a Resilient Transport System
没有具有复原力的交通系统就没有具有气候复原力的社会
Atomic force microscopy-based mechanobiology
基于原子力显微镜的力学生物学
  • DOI:
    10.1038/s42254-018-0001-7
  • 发表时间:
    2018-11-01
  • 期刊:
  • 影响因子:
    39.500
  • 作者:
    Michael Krieg;Gotthold Fläschner;David Alsteens;Benjamin M. Gaub;Wouter H. Roos;Gijs J. L. Wuite;Hermann E. Gaub;Christoph Gerber;Yves F. Dufrêne;Daniel J. Müller
  • 通讯作者:
    Daniel J. Müller
Deep learning enhanced bioluminescence microscopy
深度学习增强生物发光显微镜
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    L. Morales;G. Castro;A. Gonzalez;Lynn Lin;Montserrat Porta;D. Ramallo;P. Loza;Michael Krieg
  • 通讯作者:
    Michael Krieg

Michael Krieg的其他文献

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{{ truncateString('Michael Krieg', 18)}}的其他基金

NRI/Collaborative Research: Robotic Iceberg Sentinels (RISE)
NRI/合作研究:冰山哨兵机器人 (RISE)
  • 批准号:
    2221677
  • 财政年份:
    2022
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant
MRI: Development of an Innovative Underwater Robot Testing Facility for the Kilo Nalu Natural Coastal Marine Observatory
MRI:为基洛纳鲁自然沿海海洋观测站开发创新型水下机器人测试设施
  • 批准号:
    2216518
  • 财政年份:
    2022
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant

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转HTFα对脊髓继发性损伤和微循环重建的影响
  • 批准号:
    39970755
  • 批准年份:
    1999
  • 资助金额:
    13.0 万元
  • 项目类别:
    面上项目

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