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.
32 Vassar Street
Cambridge, MA 02139
B.S.E., 1999, University of Michigan; Ph.D., MIT, 2004.
International Conference on Robotics and Automation, Best Paper (2013); Hybrid Systems Computation and Control, Best Paper (2013); Robotics, Science and Systems, Best Student Paper Award Finalist (2011); Robotics, Science and Systems, Best Paper Award (2009); DARPA, Young Faculty Award (2009); Microsoft Research, New Faculty Fellowship Award (2008); MIT, Jerome Saltzer Award (2008); National Science Foundation, Career Award (2008)