Mechanisms as Minds: Unconventional Methods of Control in Tensegrity Robots

John Rieffel
Assistant Professor of Computer Science
Union College

Friday, October 18th, 2013

Abstract: Traditional engineering approaches strive to avoid, or actively suppress, nonlinear dynamic coupling among components. Biological systems at every scale of life, by contrast, are often rife with these same dynamics. Could there be, in some cases, a benefit to high degrees of dynamical coupling? The emerging field on "morphological computation" explores the paradoxical notion that increasing a robot's complexity can sometimes simplify the task of control. In this talk I'll demonstrate morphological computation in physical tensegrity robots driven by simple oscillators. These results lend further credence to notions of embodied anatomical computation in biological systems, and are of particular interest when studying the biomechanics of completely soft animals such as caterpillars, and in the nascent field of soft robotics.

John Rieffel is an Assistant Professor of Computer Science at Union College. He received degrees in Computer Science (BA) and Engineering (BS) from Swarthmore College, and a Ph.D in Computer Science from Brandeis University. He has held postdoctoral positions in Cornell's Mechanical Engineering Department and Tufts University's Biology Department.  His research interests include tensegrities, soft and amorphous robotics, 3D printing, and the evolution of physical systems. 

October 18, 2013

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