Convex Optimization-based Trajectory Planning and Control

Discipline: Flight Mechanics

Abstract:
This talk provides an overview of convex optimization-based trajectory generation methods: lossless convexification and sequential convex programming algorithms. These new trajectory generation methods are fast, reliable, efficient, and suitable for real-time embedded applications – representing a key enabling technology for the autonomous systems of the future.

About the Presenter:
Behcet Acikmese is a professor in the William E. Boeing Department of Aeronautics and Astronautics and an adjunct faculty member in Department of Electrical Engineering at University of Washington, Seattle. He received his Ph.D. in Aerospace Engineering from Purdue University. He was a senior technologist at JPL and a lecturer at Caltech. At JPL, He developed control algorithms for planetary landing, spacecraft formation flying, and asteroid and comet sample return missions. He developed the “flyaway” control algorithms in the Mars Science Laboratory (MSL) mission, and the reaction control system algorithms for the NASA SMAP mission. Dr. Acikmese invented a novel planetary landing guidance algorithm (G-FOLD) that was flight tested by JPL, which is a first demonstration of a real-time optimization algorithm forrocket guidance.

He is a recipient of NSF CAREER Award, IEEE Technical Excellence in Aerospace Controls Award, and numerous NASA Achievement awards for his contributions to NASA missions and new technology development. He is a Fellow of AIAA and IEEE, and an associate editor of IEEE Control System Magazine and AIAA JGCD.