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Nader Sadegh has been on the faculty of the Woodruff School of Mechanical Engineering at the Georgia Institute of Technology since January of 1988. He received his Ph.D. and M.S. degrees from the University of California at Berkeley in 1987 and 1984, respectively.
His early research work in the field of robotics and automation resulted in the development of a class of adaptive and learning controllers for nonlinear mechanical systems including robotic manipulators. These controllers enable a robot to learn a repetitive task through practice, much like a human being, and without requiring a precise model. Parallel to his efforts in the repetitive learning control area, Sadegh has made significant contributions to the theory and applications of artificial neural networks (ANN). In particular, he developed a new class of networks that enable a machine to learn the “concept” of executing a series of similar tasks rather than a specific one as is done in repetitive control through practice.
In addition to motion control, Sadegh is also interested in robotics perception and motion planning. He has developed a new algorithm based on dynamic programming that allows optimal motion planning through an arbitrary obstacle field while incorporating dynamic constraints such as velocity and acceleration limits. Successful implementation of this approach has the potential of significantly reducing the cycle time of many automated manufacturing processes without sacrificing quality.
Sadegh has authored and co-authored more than 120 archival publications and holds a joint patent for the application of his learning controller to a robotic system. He has also served an associate editor of the ASME journal of Dynamic Systems, Measurement, and Control, and has organized several technical symposia for the IEEE and ASME conferences.
Institute for Robotics & Intelligent Machines
801 Atlantic Drive
Atlanta, GA 30332-3000
Phone: (404) 385-8746