EAGER: Documenting and Analyzing Use of Robots for COVID-19

EAGER：记录和分析机器人在 COVID-19 中的使用情况

• 批准号: 2032729
• 负责人: Robin Murphy
• 金额: $ 6.9万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2032729&HistoricalAwards=false
• 关键词: EAGER; Documenting; Analyzing; Use; Robots

The robotics community needs to learn and prepare for future infectious diseases and future disasters. Understanding the role of robotics in preventing, responding to, and mitigating the consequences of pandemics could have a profound impact on the future of robotics research and convergence research in general. This understanding could identify applications where robotics are impacting, or could impact, the response to the COVID-19 pandemic disaster. Roboticists could then concentrate on those applications and gaps while the relevant agencies could have confidence in the systems. This project will guide the rapid innovation of robots for the remainder of the COVID-19 pandemic and inform future convergence research on autonomous robots by creating and analyzing a database of press and social media reports on how ground and aerial robots are being used throughout the world for the response. The project has two novel components that distinguish it from simple data gathering and archiving and that will ensure its utility for research. One, by archiving, curating, and analyzing the comprehensive use of robots worldwide for COVID-19 response and creating a sustainable nexus permitting incorporation of new reports during the evolving pandemic and supporting additional analyses. Two, the novel cross-disciplinary framework will provide a standard set of schemas for capturing data on the use of robots for disasters. Not only will the framework and plan of work establish how robots are being used, it is expected to use the experts’ unique domain knowledge to identify missed opportunities for application.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.

机器人社区需要学习并为未来的感染和未来的灾难做准备。了解机器人技术在预防，应对和缓解大流行的后果方面的作用可能会对机器人研究和融合研究的未来产生深远的影响。这种理解可以确定机器人技术正在影响或可能影响对COVID-19大流行灾难的反应的应用。然后，机器人可以专注于这些应用和差距，而相关机构可以对系统充满信心。该项目将通过创建和分析有关如何在全球范围内使用地面和空中机器人的新闻和社交媒体报告数据库来指导机器人的快速创新，并通过创建和分析新闻和社交媒体报告的数据库来为自治机器人提供有关自主机器人的未来融合研究。该项目有两个新颖的组件，可以将其与简单的数据收集和存档区分开，这将确保其研究用途。首先，通过归档，策划和分析全球在Covid-19响应中的机器人的全面使用，并创建可持续的Nexus允许在不断发展的大流行期间制定新报告的政策并支持其他分析。第二，新颖的跨学科框架将提供一组标准的模式，用于捕获有关在灾难中使用机器人的数据。工作的框架和工作计划不仅会确定如何使用机器人，而且还可以利用专家的独特领域知识来确定缺失的应用程序。该奖项反映了NSF的法定任务，并通过使用基金会的智力优点和更广泛的影响来评估NSF的法定任务。

项目成果

Progress in robotics for combating infectious diseases

• DOI: 10.1126/scirobotics.abf1462
• 发表时间: 2021-03-17
• 期刊: SCIENCE ROBOTICS
• 影响因子: 25
• 作者: Gao, Anzhu;Murphy, Robin R.;Yang, Guang-Zhong
• 通讯作者: Yang, Guang-Zhong