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Convergence Accelerator Phase I (RAISE): Learning Environments with Advanced Robotics for Next-Generation Emergency Responders (LEARNER)

融合加速器第一阶段 (RAISE)：为下一代紧急响应人员提供先进机器人技术的学习环境 (LEARNER)

基本信息

批准号：
1937053
负责人：
Joseph Gabbard
金额：
$ 99.93万
依托单位：
Virginia Polytechnic Institute and State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2021-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937053&HistoricalAwards=false
关键词：
Convergence Accelerator Phase RAISE Learning

项目摘要

The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact/potential benefit of this Convergence Accelerator Phase I project is to generate technology-based 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 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 of technology prototypes including semi-autonomous ground robots, wearable robots (powered exoskeletons) and augmented reality interfaces tailored for ER work; and building and evaluating a mixed-reality learning environment with physical, augmented, and virtual reality components, for users to learn to work effectively with multiple augmentation technologies. Our effort will also contribute to better conceptualization of convergence research and serve as a model for other research communities that can benefit from working across traditional disciplinary boundaries in engineering and computer science. We will share our methods, learnings and findings with the ER community and the wider world through an open-source knowledge sharing platform and appropriate dissemination channels. This Convergence Accelerator Phase I project will significantly advance ER operations and training through the development and prototyping of an adaptive, personalized mixed-reality learning platform that enables integrating advanced technologies for human augmentation in ER work, and the creation of principled human-robot team strategies. Our work will substantially advance the knowledge and state-of-the-art in exoskeleton control, human-robot interaction, and human-computer interaction through use-inspired technology design and development of adaptive human-in-the-loop control to facilitate learning. Furthermore, an opportunity to field these technologies and develop effective learning platforms has significant transformative potential as semi-autonomous ground robots, exoskeletons and AR will enable users to formulate fundamentally new work strategies at the individual and team levels that are only afforded by their newly extended physical and perceptual capabilities. Finally, our work will advance learning by creating a replicable platform that increases the speed for the integration of innovative and emerging technologies for training future worker. Our transdisciplinary approach combines 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 a framework 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融合加速器支持以团队为基础的多学科努力，以应对国家重要性的挑战，并在不久的将来展示可交付成果的潜力。这个融合加速器第一阶段项目的更广泛的影响/潜在好处是生成基于技术的解决方案，可以支持和增强应急响应（ER）人员的性能和安全。学术研究人员，核心技术开发人员，利益相关者和由行业和政府领导人组成的咨询委员会将聚集在一起，评估与使用人类增强技术相关的机遇和挑战，这些技术可以改变ER工作的基础，使用启发的解决方案寻找过程，并以一种可转移到其他工作环境的方式。这将涉及技术原型的开发，包括半自主地面机器人，可穿戴机器人（动力外骨骼）和为ER工作量身定制的增强现实接口;以及构建和评估具有物理，增强和虚拟现实组件的混合现实学习环境，让用户学习有效地使用多种增强技术。我们的努力也将有助于更好地融合研究的概念化，并作为其他研究社区的典范，这些研究社区可以从工程和计算机科学的传统学科界限中受益。我们将通过开源知识共享平台和适当的传播渠道与ER社区和更广泛的世界分享我们的方法，学习和发现。这个融合加速器第一阶段项目将通过开发和原型设计一个自适应的，个性化的混合现实学习平台来显着推进ER运营和培训，该平台能够将先进的人类增强技术集成到ER工作中，并创建有原则的人类-机器人团队战略。我们的工作将通过使用启发的技术设计和自适应人在回路控制的开发来促进学习，从而大大推进外骨骼控制，人机交互和人机交互方面的知识和最新技术。此外，有机会将这些技术付诸实践并开发有效的学习平台具有巨大的变革潜力，因为半自主地面机器人，外骨骼和AR将使用户能够在个人和团队层面制定全新的工作策略，而这些策略只能由他们新扩展的物理和感知能力提供。最后，我们的工作将通过创建一个可复制的平台来促进学习，该平台将加快创新和新兴技术的整合速度，以培训未来的工人。我们的跨学科方法结合并增强了学习科学，计算机科学，虚拟和增强现实，人为因素，认知心理学和系统工程等学科的现有知识，以创建一个整合培训课程设计，创新和新兴技术实施，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.