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. Aaron Ames, Bren Professor of Mechanical and Civil Engineering and Control and Dynamical Systems, 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]