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Revision as of 16:42, 8 October 2012
Aaron Ames will be visiting Caltech on 11-12 October (Thu-Fri). If you would like to meet with him, sign up below.
Thursday (11 Oct)
Friday (12 Oct)
Simplicity on the Far Side of Complexity in the Control of Bipedal Robots
Speaker: Aaron Ames
Affiliation: ME, Texas A&M
Date and time: 11 October 2012 - 12:00pm
Location: 114 Steele Lab
Humans have the ability to walk with deceptive ease, navigating everything from daily environments to uneven and uncertain terrain with efficiency and robustness. Despite the simplicity with which humans appear to ambulate, locomotion is inherently complex due to highly nonlinear dynamics and forcing. Yet there is evidence to suggest that humans utilize a hierarchical subdivision between cortical control and central pattern generators in the spinal column, indicating that when humans perform motion primitives potentially simple and characterizable control strategies are implemented, i.e., humans display simplicity on the far side of complexity. If these fundamental mechanisms underlying human walking can be discovered and formally understood, human-like abilities can be imbued into robotic devices with far-reaching applications ranging from legged robots for space exploration to disaster response.
This talk presents the process of formally achieving bipedal robotic walking through controller synthesis inspired by human locomotion, and demonstrates these methods through experimental realization on multiple bipedal robots. Motivated by the hierarchical control present in humans, we claim that the essential information needed to understand walking is encoded by a simple class of functions canonical to human walking. In other words, we view the human as a complex system, or "black box," and outputs of this system (as computed from human locomotion data) are presented that appear to characterize its behavior—thus yielding low dimensional characterization of human walking. By considering the equivalent outputs for the bipedal robot, a nonlinear controller can be constructed that drives the outputs of the robot to the output of the human; moreover, the parameters of this controller can be optimized so that stable robotic walking is provably achieved while simultaneously producing outputs of the robot that are as close as possible to those of a human. The end result is the automatic generation of bipedal robotic walking that is remarkably human-like and is experimentally realizable, as will be evidenced by the demonstration of the resulting controllers on multiple robotic platforms.
Biography: Dr. Aaron D. Ames is an Assistant Professor in Mechanical Engineering at Texas A&M University, with a joint appointment in Electrical and Computer Engineering. His research interests center on robotics, nonlinear control, and hybrid and cyber-physical systems, with special emphasis on bipedal robots, behavior unique to hybrid systems such as Zeno behavior, and the mathematical foundations of hybrid systems. Dr. Ames received a BS in Mechanical Engineering and a BA in Mathematics from the University of St. Thomas in 2001, and he received a MA in Mathematics and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley in 2006. At UC Berkeley, he was the recipient of the 2005 Leon O. Chua Award for achievement in nonlinear science and the 2006 Bernard Friedman Memorial Prize in Applied Mathematics. Dr. Ames served as a Postdoctoral Scholar in the Control and Dynamical System Department at the California Institute of Technology from 2006 to 2008. In 2010 he received the NSF CAREER award for his research on hybrid systems and bipedal robotic walking.