Practical Safety Assurances for Dynamic Human-Robot Interactions

An outstanding challenge with safety methods for human-robot interaction is reducing their conservatism while maintaining robustness to variations in human behavior. In this talk, I propose that robots leverage online data of human-robot interaction to modulate the conservatism of their safety monitors, automatically shifting between robust zero-sum models to general-sum game-theoretic models of human interaction.