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Chris Atkeson
Professor, RI/HCII Associated center: CFR Email address: cga@cs.cmu.edu
Mailing address: Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
For more information, see my personal homepage.
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Biography |
Research interests |
Keywords |
Labs & groups |
Projects |
Publications
I
received my PhD from MIT in Brain and Cognitive Sciences in 1986. I was on the faculty in MIT's Brain and Cognitive Science Department and Artificial Intelligence Laboratory and Georgia Tech's College of Computing before coming to CMU in 2000. I received an NSF Presidential Young Investigator Award, a Sloan Research Fellowship, and a Teaching Award from the MIT Graduate Student Council.
This section last updated - January 1999.
I
am an experimentalist in the field of robot learning, specializing in the learning of challenging dynamic tasks such as juggling. I am also working on applying ideas and techniques from robotics to intelligent environments. I combine designing learning algorithms with exploring their behavior in implementations on actual robots and in intelligent environments. My research interests include nonparametric learning, reinforcement learning, learning from demonstration, and modeling human behavior. For more detail please see my personal
home page.
This section last updated - January 1999.
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artificial intelligence, control, entertainment robotics, human-computer interaction, humanoid robotics, intelligent environments, legged locomotion, machine learning, manipulation, motion planning, planning, and quality-of-life technology
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Robotics Education Lab - The Robotics Education Lab is a central resource to support courses and
individual projects in robotics.
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Dynamic Biped - We are developing a new series of bipedal walking robots that use passive-dynamic principles.
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Informedia Digital Video Library - Informedia Digital Video Library - Informedia is pioneering new approaches
for automated video and audio indexing, navigation, visualization,
summarization search, and retrieval and embedding them in systems for use in
education, health care, defense intelligence and understanding of human
activity.
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Learning Locomotion - Robust planning and control of the quadruped robot
"Little Dog" to traverse rough terrain (DARPA sponsored).
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Quality of Life Technology Center - QoLT is a unique partnership between Carnegie Mellon and the University of Pittsburgh that brings together a cross-disciplinary team of technologists, clinicians, industry partners, end users, and other stakeholders to create revolutionary technologies that will improve and sustain the quality of life for all people.
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- Knowledge transfer using local features
M. Stolle and C. Atkeson
Proceedings of the IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning, 2007.
[Abstract]
Download: pdf [1123 KB] copyrighted
- Transfer of policies based on trajectory libraries
M. Stolle, H. Tappeiner, J. Chestnutt, and C. Atkeson
Proceedings of the International Conference on Intelligent Robots and Systems, 2007.
[Abstract]
Download: pdf [1613 KB] copyrighted
- Coordinating Feet in Bipedal Balance
S. Anderson, J.K. Hodgins, and C. Atkeson
IEEE Humanoids 2006, November, 2006, pp. 624-628.
[Abstract]
Download: pdf [364 KB] copyrighted
- Policies based on trajectory libraries
M. Stolle and C. Atkeson
Proceedings of the International Conference on Robotics and Automation, 2006.
[Abstract]
Download: pdf [1057 KB] copyrighted
- Powered bipeds based on passive dynamic principles
S. Anderson, M. Wisse, C. Atkeson, J.K. Hodgins, G. Zeglin, and B. Moyer
5th IEEE-RAS International Conference on Humanoid Robots, December, 2005, pp. 110 - 116.
[Abstract]
Download: pdf [505 KB] copyrighted
- Swing leg retraction helps biped walking stability
M. Wisse, C. Atkeson, and D.K. Kloimwieder
5th IEEE-RAS International Conference on Humanoid Robots, December, 2005, pp. 295 - 300.
[Abstract]
Download: pdf [315 KB] copyrighted
- Dynamic Programming in Reduced Dimensional Spaces:
Dynamic Planning For Robust Biped Locomotion
M. Stilman, C. Atkeson, J. Kuffner, and G. Zeglin
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'05), April, 2005, pp. 2399 - 2404.
[Abstract]
Download: pdf [854 KB] copyrighted
- Poincare-Map-Based Reinforcement Learning for Biped Walking
J. Morimoto, J. Nakanishi, G. Endo, G. Cheng, C. Atkeson, and G. Zeglin
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'05), April, 2005.
[Abstract]
Download: pdf [452 KB] copyrighted
- Acquisition of a Biped Walking Pattern Using an Approximate Poincare Map
J. Morimoto, J. Nakanishi, G. Endo, G. Cheng, C. Atkeson, and G. Zeglin
Proceedings of the IEEE-RAS/RSJ Int. Conf. on Humanoid Robots (Humanoids 2004), November, 2004, pp. 912 - 924.
[Abstract]
Download: pdf [1034 KB] copyrighted
- A Simple Reinforcement Learning Algorithm For Biped Walking
J. Morimoto, G. Cheng, C. Atkeson, and G. Zeglin
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'04), April, 2004, pp. 3030 - 3035.
[Abstract]
Download: pdf [838 KB] copyrighted
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