I study safe human-robot interaction, particularly when robots learn from and about people. My goal is to develop robots that interact safely despite imperfect human models; for example, autonomous vehicles that automatically slow down around erratic pedestrians and assistive robots that only learn from human feedback they can understand. My research proposes novel control-theoretic frameworks for analyzing data-driven human models and develops theoretically rigorous and practical robot algorithms for safe interaction with people. A core aspect of my approach is consistently evaluating my methods through robotic hardware experiments with real human participants in domains like assistive robotic manipulators, quadrotor navigation, and autonomous vehicles.
Administrative Assistant: Hadley Pratt
Joining Fall 2023Mailing Address
Personal and Assistive Robotics Personal Agents Robots in the Home Transportation Self-Driving Cars & Vehicles