How Do We Do It?
Resolving the Paradox of Human Performance
Friday, April 7, 3:00 pm
Sidney & Marian Green Classroom (3550 MEK)
Meet & Greet Reception to follow at 4:00 pm
Free and open to the public
Neville Hogan, Ph.D.
Professor, Mechanical Engineering & Brain & Cognitive Sciences
Massachusetts Institute of Technology
Cambridge, MA
Abstract: Human dexterity and agility significantly out-perform contemporary robots, yet humans have vastly slower ‘hardware’ (e.g. muscles) and ‘wetware’ (e.g. neurons). How can this paradox be resolved? Slow actuators and long communication delays require predictive control based on some form of internal model—but what form? A plausible answer is based on dynamic primitives; they enable highly dynamic behavior with minimal high-level supervision and intervention. Supporting this proposal, I will review a surprising limitation arising from control via dynamic primitives—moving slowly is hard for humans.
Controlling physical interaction requires mechanical impedance to be one class of dynamic primitives. Both motion and interaction primitives may be combined by a nonlinear generalization of the classical equivalent circuit. It reconciles contrasting constraints of information-processing (computation) and energy-processing (physical dynamics). I suggest that nonlinear equivalent networks provide a general basis for the internal models required for high-performance interactive control, and especially physical human-robot interaction.
Bio: Neville Hogan is professor of Mechanical Engineering and Brain and Cognitive Sciences at the Massachusetts Institute of Technology. He holds a Diploma in Engineering (with distinction) from Dublin Institute of Technology and M.S., Mechanical Engineer and Ph.D. degrees from MIT. Hogan joined MIT’s faculty in 1979 and presently directs the Newman Laboratory for Biomechanics and Human Rehabilitation. He co-founded Interactive Motion Technologies, recently acquired by Bionik Laboratories. His research includes robotics, motor neuroscience, and rehabilitation engineering, emphasizing the control of physical contact and dynamic interaction. Awards include: the Silver Medal of the Royal Academy of Medicine in Ireland; the Henry M. Paynter Outstanding Investigator Award; the Rufus T. Oldenburger Medal; and Honorary Doctorates from Dublin Institute of Technology and Delft University of Technology.