This Faculty Early Career Development (CAREER) grant provides funding for contributions to the foundations of hybrid systems through the anthropomorphically motivated study of dynamic walking of bipedal robots, with a special focus on behavior unique to hybrid systems and applications to prosthesis design.

Bipedal walking is a quintessential example of complex dynamically stable behavior. Hybrid systems---systems with both continuous and discrete behavior---provide a modeling paradigm in which to capture the behavior of highly complex systems, resulting in new phenomena not found in continuous and discrete systems. Bipedal walking robots are naturally modeled as hybrid systems, and it is the confluence of these two areas---bipedal walking and hybrid systems---that affords a unique opportunity to further the understanding of each of these areas.

This project uses studies of human walking to obtain accurate and anthropomorphic hybrid models of bipedal robots, designs control laws that yield human-like walking through the use of geometric reduction, formally studies the stability and robustness of the resulting hybrid systems, and uses this cumulative understanding of bipedal walking to design prosthesis devices.

The applications of the ideas underlying this project are far reaching, providing new research directions in hybrid systems and a new understanding of the fundamental mechanisms underlying walking. Applying this understanding to the design of prosthesis devices could have a dramatic impact on the quality of life of the millions of lower body extremity amputees. Furthermore, the anthropomorphic nature of bipedal locomotion has wide appeal to people of all ages and demographics, greatly facilitating outreach and education.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Application #
0953823
Program Officer
M. Mimi McClure
Project Start
Project End
Budget Start
2010-06-01
Budget End
2016-05-31
Support Year
Fiscal Year
2009
Total Cost
$333,810
Indirect Cost
Name
Texas Engineering Experiment Station
Department
Type
DUNS #
City
College Station
State
TX
Country
United States
Zip Code
77845