“Formal Methods for Safe and Interpretable Control”
Thursday, Nov 6 at 1:00pm
MALA 5050
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Abstract
In control theory, complicated dynamics such as systems of (nonlinear) differential equations are mostly controlled to achieve stability and to optimize a cost. In formal methods, simple systems such as finite state transition graphs modeling computer programs or digital circuits are analyzed or controlled from specifications such as safety, liveness, or richer requirements expressed as formulas of temporal logics. Many current applications, such as dexterous robotic manipulation, involve high-dimensional and partially known dynamical systems, which require machine learning techniques for motion planning and control. Ensuring safety and incorporating specifications given in rich, natural language within a learning-based system are challenging problems that received a lot of attention recently. In this talk, I will show how techniques based on control barrier and Lyapunov functions can be combined with temporal logics and reinforcement learning to address these challenges. I will use examples from robotic manipulation and autonomous driving.
Biography
Calin Belta, Ph.D., is the Brendan Iribe Endowed Professor of Electrical and Computer Engineering and Computer Science at the University of Maryland, College Park, where he is also affiliated with the Institute of Systems Research (ISR) and the Maryland Robotics Center (MRC). His research focuses on dynamics and control theory, with particular emphasis on cyber-physical systems, formal methods, and applications to robotics and systems biology. Notable awards include the 2008 AFOSR Young Investigator Award, the 2005 National Science Foundation CAREER Award, and the 2017 IEEE TCNS Outstanding Paper Award. He is a Fellow of the IEEE and a Distinguished Lecturer of the IEEE CSS.