Today’s society is rapidly advancing towards cyber-physical systems (CPS) that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. The safety-critical nature of these systems requires us to provide provably correct guarantees about their performance in interaction with humans. The goal of my research is to enable such human-cyber-physical systems (h-CPS) to be safe and interactive. I aim to develop a formalism for design of algorithms and mathematical models that facilitate correct-by-construction control for safe and interactive autonomy.

In this talk, I will first discuss interactive autonomy, where we use algorithmic human-robot interaction to be mindful of the effects of autonomous systems on humans, and further leverage these effects for better safety, efficiency, coordination, and estimation. I will then talk about safe autonomy, where we provide correctness guarantees, while taking into account the uncertainty arising from the environment. Further, I will discuss a falsification algorithm to show robustness with respect to learned human models. While the algorithms and techniques introduced can be applied to many h-CPS applications, in this talk, I will focus on the implications of my work for semi-autonomous driving.