Data driven models of multilegged locomotion : an ongoing challenge

June 08, 2018, Webb 1100

Shai Revzen

University of Michigan, Biorobotics and Biomechanics

Abstract

As soon as the terrain is no longer flat, legs out perform wheels as a means for terrestrial locomotion. Yet we know very little about how multilegged animals move as effectively at they do. This talk will review some of the mechanical fundamentals of locomotion, and discuss over a decade of work attempting to produce good data-driven models of multilegged locomotion. Initial work explored multilegged motion from an oscillator theory perspective, leading to the development of methods for Data Driven Floquet Analysis. More recent approaches delve into geometric mechanics to offer classes of reduced order models. The talk combines ideas from biology, robotics, mechanics, dynamical systems theory, and geometric mechanics.

Speaker's Bio

Shai Revzen is an Assistant Professor in the departments of Electrical Engineering and Computer Science and of Ecology and Evolutionary Biology in the University of Michigan, Ann Arbor. He holds a PhD from the University of California, Berkeley in biomechanics, an MSc in computer science from the Hebrew University in Jerusalem, and did his post-doctoral work in robotics in the GRASP lab of the University of Pennsylvania. His BIRDS (Biologically Inspired Robotics and Dynamical Systems) Lab in Michigan focuses on the crucial role of mechanics in robot motion and on the rapid manufacturing of robots and robotic mechanisms, primarily to study questions of legged locomotion. The aim of BIRDS Lab is to extract core principles of biological robustness and control in mathematical form and recast them into robots. Shai's work has been published in engineering, biology and applied mathematics journals. Shai is also a co-founder of a company developing novel electro-cardiac diagnostics, is the author of several patents, and has extensive experience from over a decade in the tech industry in both Tel-Aviv and Silicon Valley.