Ensuring the safety of autonomous systems, such as driverless cars, unmanned aerial vehicles and surgical robots, is a critical challenge in the growing field of automation. A new award supports work at the McKelvey School of Engineering at Washington University in St. Louis to develop a framework that will allow these systems to maintain safety even in the face of sensor malfunctions, mechanical failures or deliberate cyberattacks.
Andrew Clark, an associate professor in the Preston M. Green Department of Electrical & Systems Engineering, received a $454,202 grant from the National Science Foundation to support his research on safe control of autonomous systems in adverse conditions. Whether malfunctions result from naturally occurring faults or deliberate attacks, Clark aims to combine techniques from control theory, machine learning and system security to guarantee system functionality across a wide range of autonomous systems and fault or attack scenarios.
One of the primary challenges Clark will address is the vulnerability of learning-enabled systems — those powered by machine-learning algorithms — which often struggle to adapt when confronted with novel situations not seen during training.
Read more on the McKelvey Engineering website.
