What robotics may yet learn from the brain

By Jean-Jacques Slotine
Dept. of Mechanical Engineering and Dept. of Brain and Cognitive Sciences, MIT.

Although neurons as computational elements are 7 orders of magnitude slower than their artificial counterparts, the primate brain grossly outperforms robotic algorithms in all but the most structured tasks. Parallelism alone is a poor explanation, and much recent functional modelling of the central nervous system focuses on its modular, heavily feedback-based computational architecture, the result of accumulation of subsystems throughout evolution. We discuss this architecture from a global functionality point of view, and show why evolution is likely to favor certain types of aggregate stability. We then study synchronization as a model of computations at different scales in the brain, such as pattern matching, restoration, priming, temporal binding of sensory data, and mirror neuron response. We derive a simple condition for a general dynamical system to globally converge to a regime where diverse groups of fully synchronized elements coexist, and show accordingly how global "polyrhythmic" patterns can be transiently selected and controlled by a very small number of inputs or connections. We also quantify how synchronization mechanisms can protect from noise. Applications to classical questions in robot manipulation, locomotion, vision, imitation, and cooperation are discussed.

About the speaker


Jean-Jacques Slotine was born in Paris in 1959, and received his Ph.D. from the Massachusetts Institute of Technology in 1983. After working at Bell Labs in the computer research department, in 1984 he joined the faculty at MIT, where he is now Professor of Mechanical Engineering and Information Sciences, Professor of Brain and Cognitive Sciences, and Director of the Nonlinear Systems Laboratory. He is the co-author of the textbooks "Robot Analysis and Control" (Wiley, 1986) and "Applied Nonlinear Control" (Prentice-Hall, 1991). Prof. Slotine was a member of the French National Science Council from 1997 to 2002, and is a member of Singapore's A*STAR SigN Advisory Board.