EAGER: Documenting and Analyzing Use of Robots for COVID-19
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2032729
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$68,962Funder
National Science Foundation (NSF)Principal Investigator
Robin MurphyResearch Location
United States of AmericaLead Research Institution
Texas A&M Engineering Experiment StationResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Other secondary impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
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.
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.