Human interaction with autonomous systems is becoming ubiquitous in consumer products, transportation systems, manufacturing, and many other domains. However, few tools exist for modeling, computation, and control that are responsive to human heterogeneity. We seek to ascertain when human heterogeneity is important for control, and to design and assure controllers that are responsive to the uncertainty inherent to human-in-the-loop systems. Our methods are based in both data-driven and model-based approaches that can accommodate arbitrary, non-Gaussian uncertainty. We have developed high-fidelity, data-driven characterizations of human-in-the-loop trajectories, based in conditional distribution embeddings, with application to psychomotor tasks. We have also begun to explore a game theoretic framework for controller synthesis under cautious, partial cooperation with the human. Lastly, we have developed stochastic controllers and probabilistic verification tools that can accommodate stochastic processes associated with human decision and action in a computationally efficient manner, without gridding, sampling, or recursion. These methods and tools help address the need for new paradigms and frameworks to enable responsivity to human variability in autonomous systems.
Meeko Oishi received the Ph.D. (2004) and M.S. (2000) in Mechanical Engineering from Stanford University (Ph.D. minor, Electrical Engineering), and a B.S.E. in Mechanical Engineering from Princeton University (1998). She is a Professor of Electrical and Computer Engineering at the University of New Mexico. Her research interests include human-in-the-loop control, stochastic optimal control, and autonomous systems. She previously held a faculty position at the University of British Columbia at Vancouver, and postdoctoral positions at Sandia National Laboratories and at the National Ecological Observatory Network. She was a Visiting Researcher at AFRL Space Vehicles Directorate, and a Science and Technology Policy Fellow at The National Academies. She is the recipient of the NSF CAREER Award, the NSF BRITE Fellowship, the Truman Postdoctoral Fellowship in National Security Science and Engineering, and a member of the 2022-2024 US Defense Science Study Group.