B2: Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders (LEARNER)

B2：为下一代应急响应人员提供增强和机器人技术的学习环境（学习者）

• 批准号: 2349138
• 负责人: Ranjana Mehta
• 金额: $ 499.83万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2349138&HistoricalAwards=false
• 关键词: B2; Learning; Environments; Augmentation; Robotics

The NSF Convergence Accelerator supports use-inspired, team-based, multidisciplinary efforts that address challenges of national importance and will produce deliverables of value to society in the near future.The broader impact and potential societal benefits of this Convergence Accelerator Phase II project will be to generate technology-based learning solutions that can support and augment the performance and safety of emergency response (ER) personnel. Academic researchers, core-technology developers, stakeholders, and an advisory board constituted of leaders from industry and government will come together to assess opportunities and challenges related to the use of human augmentation technologies (HATs) that can transform the process of foundational, use-inspired solution-finding for ER work, and in a way that is transferable to other work contexts as well. This will involve the development and evaluation of LEARNER (Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders), a mixed-reality learning environment with physical, augmented, and virtual reality components, for users to learn to work effectively with two HAT classes: powered exoskeletons (EXO) and head-worn AR interfaces (AR). Our effort will contribute to better conceptualize convergence work that can foster the understanding of reciprocal human-technology interactions; contribute to systems that are tailored, optimized, and continuously adapted for humans and their environments; and education and lifelong learning to create the requisite workforce. Our effort will also serve as a model for other research communities that can benefit from working across traditional disciplinary boundaries in engineering, computer science, learning sciences, and human resource development. We will share our methods, learnings and findings with the ER community and the wider world by leading a National Talent Ecosystem Council, a collaborative think-tank organization, to support scientific research activities on workforce learning with advanced technologies and organizing Learn-X symposiums on the topic of technology-driven advances in learning-sciences and educational/human resource development.We will develop and evaluate a functional prototype of LEARNER – an innovative accessible, modular, personalized, and scalable learning platform to accelerate skilling and reskilling of ER workers, particularly on nascent augmentation technologies that have significant potential to change the very nature of work and improve efficiency, health, and well-being. LEARNER will provide a unique training paradigm by incorporating physiological, neurological, and behavioral markers of learning into real-time scenario evolution. The proposed virtual and physical user interfaces and interaction techniques will advance the human-computer interaction field by providing a multisensory approach for ER simulation and synchronized virtual interactions with physical environments and work artifacts. Furthermore, our plan to field these HATs and develop an effective learning platform has significant transformative potential as EXOs and AR will enable users to formulate new work strategies at the individual and team levels enabled by their newly extended physical and perceptual capabilities. Finally, our work will advance learning by creating a scalable and replicable platform that will increase the speed of integration and adoption of innovative and emerging HATs that benefit the future workforce across diverse industrial sectors. Our transdisciplinary approach converges and enhances the existing knowledge from the disciplines of learning science, computer science, virtual and augmented realities, human factors, cognitive psychology, and systems engineering to create the LEARNER platform that integrates training course design, innovative and emerging technology implementation, and new techniques of work.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.

NSF融合加速器支持采用的，基于团队的多学科努力，这些努力应对国家重要性的挑战，并将在不久的将来为社会带来价值的可交付成果。这种融合加速器II阶段项目的更广泛的影响和潜在的社会益处将是为了产生基于技术的学习解决方案，以支持和增强绩效和安全响应的绩效和安全性（ER）人员（ER）人员（ER）。学术研究人员，核心技术开发人员，利益相关者和顾问委员会由工业和政府的领导人组成，将共同评估与使用人类增强技术（HATS）有关的机遇和挑战，这些技术（HATS）可以改变基础，使用启发性的解决方案的急诊工作，并以某种方式转移到其他工作环境中。这将涉及学习者的开发和评估（对于下一代应急人员的增强和机器人技术的学习环境），一种具有物理，增强和虚拟现实组件的混合真实学习环境，使用户能够学会与两个帽子类别的类别合作：有效的外exoskeletons（EXO）（EXO）和worn worn worn Ar Interfaces（AR）。我们的努力将有助于更好地概念化融合工作，从而促进对互惠人类技术相互作用的理解；为量身定制，优化和不断适应人类及其环境的系统做出贡献；以及教育和终身学习创造必要的劳动力。我们的努力还将成为其他研究社区的模型，这些研究社区可以从工程，计算机科学，学习科学和人力资源开发方面的传统学科界限中受益。我们将通过领导国家人才生态系统委员会（一个协作智障组织）来支持与先进技术的劳动力学习有关的科学研究活动，并组织学习型驱动力驱动的学习和人类资源开发方面的主题，我们将开发技术/人类资源的发展，我们将在Instripation Insportiational fromptigation frompticts of inteptys of Farmity offictation，我们将与ER社区和更广阔的世界分享我们的方法，学习和发现，以支持劳动力学习的科学研究活动。个性化且可扩展的学习平台，以加速ER工人的技能和重新运输，尤其是在新生的增强技术上，这些技术具有改变工作本质并提高效率，健康和福祉的巨大潜力。学习者将通过将学习的身体，神经和行为标志物纳入实时场景演变来提供独特的培训范式。所提出的虚拟和物理用户界面以及交互技术将通过为ER模拟和与物理环境和工作工件同步的多感觉方法来推动人类计算机的交互字段。此外，我们计划戴上这些帽子并开发有效的学习平台具有巨大的变革潜力，因为Exos和AR将使用户能够通过其新扩展的物理和感知能力来为个人和团队级别制定新的工作策略。最后，我们的工作将通过创建一个可扩展且可复制的平台来提高学习，我们将提高整合和采用创新和新兴帽子的速度，从而使潜水员工业部门的未来劳动力受益。我们的跨学科方法从学习科学，计算机科学，虚拟和增强现实，人为因素，人为因素，认知心理学和系统工程的学科中融合并增强了现有知识，以创建学习平台，从而使培训课程设计，创新和新兴的技术实施，以及工作的新技术集成了范围的新技术。影响审查标准。