Robotics Engineers Take on COVID-19

Methods that were originally created to help robots to walk and autonomous cars to drive safely can also help epidemiologists predict the spread of the COVID-19 pandemic. Professor Aaron Ames and colleagues took these tools and applied them to the development of an epidemiological methodology that accounts for human interventions (like mask mandates and stay-at-home orders). By utilizing the U.S. COVID-19 data from March through May, they were able to predict the infection wave during the summer to high accuracy. "This is the greatest health challenge to face our society in a generation at least. We all need to pitch in and help in any way we can," Ames says. [Caltech story]

Tags: research highlights MCE CMS Aaron Ames Andrew Singletary