Angela Clendenin - US grants

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.

Robotics innovations (unmanned ground, aerial, and marine systems) have been sporadically used for disaster response by emergency management agencies since 2001. Disasters pose a dilemma: on one hand, there is often an emotional urge to try anything in the hopes of coping with overwhelming potential loss of life and livelihoods; on the other hand, the poorly considered introduction of a robot into a disaster can lead to worse outcomes than doing nothing. This EArly Concept Grant for Exploratory Research (EAGER) study will bring together leaders in robotics, law, emergency management, and public health with expertise in emergency management and policy to investigate robotics innovations and instances of ethical concerns during the COVID-19 pandemic. The result will be the first theory of responsible robotics innovation for disasters. This will transform how responders select robot technology during a disaster, ultimately saving lives, mitigating long-term environmental and health impacts, and accelerating economic recovery. The project will provide evidence for anticipatory governance, such as new regulations and policies, to accelerate the adoption of safe, effective robots during a disaster while reducing negative consequences from either deploying unsound technology or deferring deployment of technology. The project will impact how engineering, law, and policy is taught, train graduate and undergraduate students in multidisciplinary approaches to science and society, and increase the diversity of students in the research pipeline.

The multidisciplinary team will conduct a rigorous analysis, featuring structured interviews with clinical healthcare providers, public health and public safety officials worldwide who deployed robots during the pandemic in order to understand the influences on adoption. The demand analysis will be complemented by prior work in quantitatively classifying the capabilities of the robot for a use case; together these orthogonal sets of user-centric and robot-centric influences will create a novel template for describing future innovation. The project will explore the legal systems and how they adapted to the exigencies of the pandemic, especially any correlations with national policies on robotics, and investigate emergent ethical concerns. The resulting quantitative model is expected to be both prescriptive for policy and predictive for future law and science research into robotics adoption. The model will revolutionize the methodology for constructing innovation theories. It will contribute to foundational responsible innovation research and comparative law, especially how groups interpret legal uses of robotics and how robotics impacts expectations of rights and responsibilities of agencies and developers.

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.