Toward Flexible and Effective Human-Robot Teaming

Toward Flexible and Effective Human-Robot Teaming

Abstract: Despite nearly seventy years of development, robots are not yet realizing their promise of handling the undesirable day-to-day tasks of skilled industrial workers. Recent studies indicate that today’s robots are still too inflexible and difficult to program, particularly for less structured and high-variability tasks. In this talk, I will present three recent approaches to human-robot teaming that aim to unlock new opportunities for robots. These approaches address key questions in human-robot teaming, such as how to optimize human input during teaming and how skilled workers can teach robots complex behaviors. I will conclude by discussing open problems in the area and outlining next steps toward more widespread
human-robot teaming.

Biography: Mike Hagenow is a postdoctoral fellow in the Department of Aeronautics and Astronautics and CSAIL at the Massachusetts Institute of Technology. He received the B.S. degree in Mechanical Engineering from Tufts University in 2014 and the M.S./Ph.D. degrees in Mechanical Engineering from the University of Wisconsin – Madison in 2019 and 2023, respectively. His work has previously been supported by funding from NSF, NASA, and the Grainger Wisconsin Distinguished Graduate Fellowship (WDGF). Currently, his work is supported by the Postdoctoral Fellowship Program for Engineering Excellence (PFPFEE) and the MIT Work of the Future Initiative. His research interests include human-robot interaction, shared control/autonomy, and robot learning.