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Summary
Russ Tedrake is an Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, and a member of the Computer Science and Artificial Intelligence Lab. He received his B.S.E. in Computer Engineering from the University of Michigan, Ann Arbor, in 1999, and his Ph.D. in Electrical Engineering and Computer Science from MIT in 2004, working with Sebastian Seung. After graduation, he spent a year with the MIT Brain and Cognitive Sciences Department as a Postdoctoral Associate. During his education, he has spent time at Microsoft, Microsoft Research, and the Santa Fe Institute. Professor Tedrake's research group is interested in underactuated motor control systems in animals and machines that are capable of executing dynamically dexterous tasks and interacting with uncertain environments. They believe that the design of these control systems is intimately related to the mechanical designs of their machines, and that tools from machine learning and optimal control can be used to exploit this coupling when classical control techniques fail. Current projects include robust and efficient bipedal locomotion on flat terrain, multi-legged locomotion over extreme terrain, flapping-winged flight, and feedback control for fluid dynamics.
Russ Tedrake is an Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, and a member of the Computer Science and Artificial Intelligence Lab. He received his B.S.E. in Computer Engineering from the University of Michigan, Ann Arbor, in 1999, and his Ph.D. in Electrical Engineering and Computer Science from MIT in 2004, working with Sebastian Seung. After graduation, he spent a year with the MIT Brain and Cognitive Sciences Department as a Postdoctoral Associate. During his education, he has spent time at Microsoft, Microsoft Research, and the Santa Fe Institute. Professor Tedrake's research group is interested in underactuated motor control systems in animals and machines that are capable of executing dynamically dexterous tasks and interacting with uncertain environments. They believe that the design of these control systems is intimately related to the mechanical designs of their machines, and that tools from machine learning and optimal control can be used to exploit this coupling when classical control techniques fail. Current projects include robust and efficient bipedal locomotion on flat terrain, multi-legged locomotion over extreme terrain, flapping-winged flight, and feedback control for fluid dynamics.
| Current Institution | Massachusetts Institute of Technology |
| Department | Electrical Engineering and Computer Science |
| Disciplines | |
| Address | MIT 32-380, 32 Vassar Street Cambridge Massachusetts 02139 United States Phone: (617) 253-1778 |
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Education
Massachusetts Institute of Technology Cambridge
Ph.D.,
Electrical Engineering and Computer Science
(Aug 2004)
University of Michigan
B.S.E,
Computer Engineering
(May 1999)
Work Experience
Associate Professor
Massachusetts Institute of Technology
(2009 - Present)
Courtesy Joint Appointment
Massachusetts Institute of Technology
(2011 - Present)
Achievements
General
Publication Summary
- Ian R. Manchester, Uwe Mettin, Fumiya Iida, and Russ Tedrake. Stable dynamic walking over uneven terrain. The International Journal of Robotics Research (IJRR), 3(3), March 2011.
- Alexander Shkolnik, Michael Levashov, Ian R. Manchester, and Russ Tedrake. Bounding on rough terrain with the littledog robot. The International Journal of Robotics Research (IJRR), 30(2):192215, Feb 2011.
- Jan Peters, Russ Tedrake, Nicholas Roy, and Jun Morimoto. Robot learning. In Claude Sammut and Geoffrey I. Webb, editors, Encyclopedia of Machine Learning, pages 865–9. Springer, 2011.
- Mark Tobenkin, Ian R. Manchester, Jennifer Wang, Alex Megretski, and Russ Tedrake. Convex optimization in identification of stable non-linear state space models. In Proceedings of the 49th IEEE Conference on Decision and Control (CDC 2010), extended version available online: arXiv:1009.1670 [math.OC], Dec 2010.
- R. Platt, R. Tedrake, L.P. Kaelbling, and T. Lozano-Perez. Belief space planning assuming maximum likelihood observations. In Proceedings of Robotics: Science and Systems, 2010.
- Russ Tedrake, Ian R. Manchester, Mark M. Tobenkin, and JohnW. Roberts. LQR-Trees: Feedback motion planning via sums of squares verification. International Journal of Robotics Research, 29:1038– 1052, July 2010.
- Philipp Reist and Russ Tedrake. Simulation-based LQR-trees with input and state constraints. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2010.
- Elena Glassman and Russ Tedrake. A quadratic regulator-based heuristic for rapidly exploring state space. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2010.
- Fumiya Iida and Russ Tedrake. Minimalistic control of biped walking in rough terrain. Autonomous Robots, OnlineFirst:355–368, January 7 2010.
- Jan Peters, Jun Morimoto, Russ Tedrake, and Nicholas Roy. Robot learning [TC Spotlight]. Robotics and Automation Magazine, IEEE, 16(3):19–20, September 2009.
- JohnW. Roberts, Lionel Moret, Jun Zhang, and Russ Tedrake. Motor learning at intermediate Reynolds number: Experiments with policy gradient on the flapping flight of a rigid wing. In From Motor toInteraction Learning in Robots. Springer, 2009.
- Russ Tedrake. LQR-Trees: Feedback motion planning on sparse randomized trees. In Proceedings of Robotics: Science and Systems (RSS), page 8, 2009.
- Ian R. Manchester, Uwe Mettin, Fumiya Iida, and Russ Tedrake. Stable dynamic walking over rough terrain: Theory and experiment. In Proceedings of the International Symposium on Robotics Research(ISRR), 2009.
- Katie Byl and Russ Tedrake. Metastable walking machines. International Journal of Robotics Research, 28(8):1040–1064, August 1 2009. Russell Tedrake 2 of 12
- Khashayar Rohanimanesh, Nicholas Roy, and Russ Tedrake. Towards feature selection in actor-criticalgorithms. In Proceedings of the Workshop on Abstraction in Reinforcement Learning (ICML, UAI,COLT 2009), Montreal, Canada, June 18 2009.
- Warren Hoburg and Russ Tedrake. System identification of post stall aerodynamics for UAV perching. In Proceedings of the AIAA Infotech@Aerospace Conference, Seattle, WA, April 2009. AIAA.
- Joseph Moore and Russ Tedrake. Powerline perching with a fixed-wing UAV. In Proceedings of the AIAA Infotech@Aerospace Conference, Seattle, WA, April 2009. AIAA.
- John W. Roberts, Rick Cory, and Russ Tedrake. On the controllability of fixed-wing perching. In Proceedings of the American Controls Conference (ACC), 2009.
- Alexander Shkolnik and Russ Tedrake. Path planning in 1000+ dimensions using a task-space Voronoi bias. In Proceedings of the IEEE/RAS International Conference on Robotics and Automation (ICRA). IEEE/RAS, 2009.
- Alexander Shkolnik, Matthew Walter, and Russ Tedrake. Reachability-guided sampling for planning under differential constraints. In Proceedings of the International Conference on Robotics and Automation(ICRA), pages 2859–2865. IEEE/RAS, 2009.
- Fumiya Iida and Russ Tedrake. Minimalistic control of a compass gait robot in rough terrain. In Proceedings of the IEEE/RAS International Conference on Robotics and Automation (ICRA). IEEE/RAS, 2009.
- John W. Roberts and Russ Tedrake. Signal-to-noise ratio analysis of policy gradient algorithms. In Advances of Neural Information Processing Systems (NIPS) 21, page 8, 2009.
- Abderrahmane Bennis, Miriam Leeser, Gilead Tadmor, and Russ Tedrake. Implementation of a highly parameterized digital PIV system on reconfigurable hardware. In Proceedings of the Twelfth AnnualWorkshop on High Performance Embedded Computing (HPEC), Lexington, MA, September 2008.
- Katie Byl, Alexander Shkolnik, Sam Prentice, Nicholas Roy, and Russ Tedrake. Reliable dynamic motions for a stiff quadruped. In Proceedings of the 11th International Symposium on ExperimentalRobotics (ISER), 2008.
- Alexander Shkolnik and Russ Tedrake. High-dimensional underactuated motion planning via task space control. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots andSystems (IROS). IEEE/RSJ, 2008.
- Rick Cory and Russ Tedrake. Experiments in fixed-wing UAV perching. In Proceedings of the AIAA Guidance, Navigation, and Control Conference. AIAA, 2008.
- Katie Byl and Russ Tedrake. Metastable walking on stochastically rough terrain. In Proceedings of Robotics: Science and Systems IV, 2008.
- Katie Byl and Russ Tedrake. Approximate optimal control of the compass gait on rough terrain. In Proc. IEEE International Conference on Robotics and Automation (ICRA), 2008.
- Rick Cory and Russ Tedrake. On the controllability of agile fixed-wing flight. In Proceedings of the 2007 Symposium on Flying Insects and Robots (FIR), August 2007.Russell Tedrake 3 of 12
- Khashayar Rohanimanesh, Nicholas Roy, and Russ Tedrake. Towards feature selection in actor-critic algorithms. Technical report, Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory, 2007.
- Fumiya Iida and Russ Tedrake. Motor control optimization of compliant one-legged locomotion in rough terrain. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007.
- Finale Doshi, Emma Brunskill, Alexander Shkolnik, Thomas Kollar, Khash Rohanimanesh, Russ Tedrake, and Nicholas Roy. A supervised learning approach for collision detection in legged locomotion. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007.
- Alexander Shkolnik and Russ Tedrake. Inverse kinematics for a point-foot quadruped robot with dynamic redundancy resolution. In Proceedings of the 2007 IEEE International Conference on Roboticsand Automation, April 2007.
- Katie Byl and Russ Tedrake. Stability of passive dynamic walking on uneven terrain. In Art Kuo, editor, Proceedings of Dynamic Walking 2006, May 2006.
- Jerry E. Pratt and Russ Tedrake. Velocity based stability margins for fast bipedal walking. In Proceedings of the First Ruperto Carola Symposium on Fast Motions in Biomechanics and Robotics: Optimization and Feedback Control, volume 340, pages 299–324, Sep 2005.
- Russ Tedrake, Teresa Weirui Zhang, and H. Sebastian Seung. Learning to walk in 20 minutes. In Proceedings of the Fourteenth Yale Workshop on Adaptive and Learning Systems, Yale University, New Haven, CT, 2005.
- Steven H. Collins, Andy Ruina, Russ Tedrake, and Martijn Wisse. Efficient bipedal robots based on passive-dynamic walkers. Science, 307:1082–1085, February 18 2005.
- Russell L Tedrake. Applied Optimal Control for Dynamically Stable Legged Locomotion. PhD thesis, Massachusetts Institute of Technology, 2004.
- Russ Tedrake, TeresaWeirui Zhang, and H. Sebastian Seung. Stochastic policy gradient reinforcement learning on a simple 3D biped. In Proceedings of the IEEE International Conference on IntelligentRobots and Systems (IROS), volume 3, pages 2849–2854, Sendai, Japan, September 2004.
- Russ Tedrake, Teresa Weirui Zhang, Ming-fai Fong, and H. Sebastian Seung. Actuating a simple 3D passive dynamic walker. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), volume 5, pages 4656–4661, New Orleans, LA, April 2004.
- Russ Tedrake and H. Sebastian Seung. Improved dynamic stability using reinforcement learning. In 5th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR), pages 341–348, Paris, France, September 2002. Professional Engineering Publishing Limited.
- Russ Tedrake. Soaring with descent 3. Proceedings of the 19th American Soar Workshop, 1999. Russell Tedrake 4 of 12
- Mike van Lent, John Laird, Josh Buckman, Joe Hartford, Steve Houchard, Kurt Steinkraus, and Russ Tedrake. Intelligent agents in computer games. In Proceedings of the American Association for ArtificialIntelligence, pages 929–930, Orlando, FL, July 1999.
Books
Other Publications
