Aaron D. Ames on Human-Inspired Control of Bipedal Robots

Tuesday June 5th 2012, 13:15 (1:15pm), Wigforssalen, Halmstad University

Click here for a video recording of the lecture.

Bipedal robots provide an important example of a cyber-physical system (CPS). As a result, understanding the process of realizing formal results experimentally, and the software structures needed to do so, can yield important insights into software synthesis for complex CPS. This talk presents the process of formally achieving human-like bipedal robotic walking by synthesizing controllers inspired by human locomotion data, discusses the software structures used in realizing these controllers and demonstrates these methods through experimental realization on two bipedal robots: AMBER and NAO.

Motivated by the hierarchical control present in humans, the fundamental principle behind this process is 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 of this process is the automatic generation of bipedal robotic walking that is surprisingly human-like. Extensions of these ideas to different walking behaviors, e.g., stair climbing, will be discussed, along with their application to simulating and designing controllers for prosthetic devices. Finally, the experimental realization of these formal results on two robotic platforms—an underactuated 2D biped, AMBER, and a fully actuated 3D robot, NAO—will be demonstrated.

About Dr. Aaron D. Ames

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 bipedal robotic walking and its applications to prosthetic devices.