Abstract
In this talk, I will introduce the concept of generating complex robot motions by implementing sensorimotor learning capabilities of humans. The idea is to consider the target robotic platform as a tool that can be controlled by a human. Provided with an intuitive interface between the human and the robot, the human learns to perform a given task using the robot. After the learning, the skilled control of the robot by the human provides data that are used for construction of an autonomous controller that controls the robot without any guidance by the human. I will demonstrate the feasibility of this framework by presenting several examples of robotic motion including statically stable reaching skill and in-place stepping of a small size humanoid robot. I will also present some ideas on the neural correlates of human-in-the-loop robot control and show how the interfaces built for robot skill synthesis can also be used in the reverse direction, for probing motor control mechanisms employed by the central nervous system.
Short bio
Jan Babic is a Research Fellow at the Jozef Stefan Institute and a Senior Researcher in the Faculty of Electrical Engineering, University of Ljubljana, Slovenia. He received his Ph.D. from the Faculty of Electrical Engineering, University in Ljubljana, examining the role of biarticular muscles in human locomotion. During the years 2006-2007 he was a visiting researcher at the ATR Computational Neuroscience Laboratories in Japan. His current research is concerned with understanding how the human brain controls movement of the arms and legs, and with the design of biologically plausible robot controllers that achieve similar robustness and adaptation to the changing environment as found in humans.
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