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Optimization techniques for vehicle control

The first part of the talk is on the use of hybrid systems tools for multi-vehicle cooperative control. I discuss mixed integer linear programming (MILP) techniques for single vehicle trajectory generation and obstacle avoidance. Then, building on the single vehicle techniques, I discuss MILP techniques for modeling and controlling multi-vehicle systems using Cornell's multi-vehicle testbed (RoboFlag) as a motivating example. The second part of the talk is on decomposition methods using trajectory primitives. I discuss the decomposition of a RoboFlag multi-vehicle control problem and an algorithm to solve the resulting combinatorial optimization problem.

Type of Seminar:
Public Seminar
Matthew Earl, Ph.D. Student
Cornell University Ithaca NY, USA
Jun 21, 2004   13:30

ETH Zentrum, ETZ E 81
Contact Person:

Prof. M. Morari
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Biographical Sketch:
Matthew Earl received the B.S. degree in mechanical engineering from the University of Rochester, Rochester, New York. He is currently a Ph.D. candidate in dynamics and control at Cornell University, Ithaca, New York. His research interests include optimization techniques for multi-vehicle cooperative control, hybrid systems, and the application of controls tools to applied problems