NSF Award Abstract - #0427260| NSF Award Abstract - #0427260 |
| NSF Org | IIS |
| Latest Amendment Date | September 22, 2004 |
| Award Number | 0427260 |
| Award Instrument | Standard Grant |
| Program Manager |
Edwina L. Rissland IIS Division of Information & Intelligent Systems CSE Directorate for Computer & Information Science & Engineering |
| Start Date | October 1, 2004 |
| Expires | September 30, 2008 (Estimated) |
| Awarded Amount to Date | $900000 |
| Investigator(s) |
C.S. George Lee csglee@purdue.edu (Principal Investigator)
Howard Zelaznik (Co-Principal Investigator) |
| Sponsor |
Purdue University Young Hall West Lafayette, IN 47907 765/494-4600 |
| NSF Program(s) | ITR FOR NATIONAL PRIORITIES |
| Field Application(s) |
0104000 Information Systems, 0104000 Information Systems |
| Program Reference Code(s) |
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| Program Element Code(s) |
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Currently humanoid robots do not move like human beings. They are not skillful enough to perform tasks that require interactions with humans and the environment. Humans can learn new skills very easily with deliberate practice. If humanoid robots could acquire skills like humans, they would be able to help with many needs of society. Humans exhibit remarkable flexibility in motor skill. We believe that human flexibility is derived from the fact that humans are inconsistent in performance. This inconsistency allows people the flexibility to learn new skills. Should humanoid robots have the ability to acquire skills like humans, we can expect a dramatic improvement in the performance of humanoid robots on various tasks. This proposal, a unique collaboration between a robotics researcher and a motor learning and control researcher from a kinesiology perspective, aims at capturing these characteristics of human motor learning and control and then instantiating these characteristics in the coordination and control algorithms of a humanoid robot. In addition, an international collaboration with researchers at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan will allow us to examine the goodness of our research experimentally on an HRP-2 humanoid robot. In this project, we will be studying the motion of human subjects as they learn a few complicated tasks. These subjects will either practice the skill as a whole or practice the individual parts of the skill. We then will observe how well subjects transfer to a novel motor skill. We will model the learning human with network models and then attempt to put these models in a humanoid robot. Will the humanoid robot show the same transfer of learning as the human? Can the humanoid robot show the same types of errors as the human? These are some of the questions that we seek to answer from this research. The broader impacts of this research include: (i) a systematic investigation of motor skill learning and transfer, their limitations, and their integration to produce intelligent humanoid robots; (ii) research collaboration between researchers from engineering and liberal arts to engage in information technology research and education from different perspectives, and international research collaboration with the AIST in Japan; (iii) development of a web site for students to simulate humanoid robots using OpenHRP software; and (iv) research results will be disseminated in professional conference and archival journal publications. In addition, the project will have an impact on undergraduate and graduate education, especially experimental research and senior design projects. Finally, for the outreach impact, humanoid robots and simulation tools will be an excellent vehicle to educate high-school students in team work and encourage them to select engineering for their higher education and career.