We use theoretical insights to devise practical, computationally-efficient, and provably-correct algorithms for field deployment.
The goal of the Autonomous Systems Laboratory (ASL) is the development of methodologies for the analysis, design, and control of autonomous systems, with a particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. The lab combines expertise from control theory, robotics, optimization, and machine learning to develop the theoretical foundations for networked autonomous systems operating in uncertain, rapidly-changing, and potentially adversarial environments. Theoretical insights are then used to devise practical, computationally-efficient, and provably-correct algorithms for field deployment.