Control and planning for autonomous systems under uncertainty - fusing predictive control and learning with guarantees

18.11.2019 von 16:00 bis 17:00


Many autonomous systems tasks, especially in uncertain environments, require a tight integration of planning and control. Examples are the writing of a robot with a pen on a flexible object, the cooperative movement off an object via multiple robots in a dynamic environment, or the operation of a drone in an highly dynamic and uncertain enviroment.  In the frame of this talk we outline that a combination of optimisation based decisions for planning and control with learning approaches allows to tackle uncertain and dynamic problems. In the first part of the talk we outline a predictive control approach for force feedback control under uncertainty. The second part focuses on how to fuse predictive control with learning approaches, while guaranteeing constraint satisfaction and stability for all considered situations. The presented results are underlined with experimental and simulation results from robotics, unmanned aerial vehicles and autonomous driving.


Rolf Findeisen obtained a M.S. degree from the University of Wisconsin, Madison, a Diploma in Engineering Cybernetics and Doctorate from the University of Stuttgart. Since 2007 he is heading the Laboratory for Systems Theory and Automatic Control at the Otto-von-Guericke Universität Magdeburg.  He had several longer stays at ETH Zürich and Imperial College and was visiting professor at MIT Cambridge and EPF Lausanne. Rolf is editor/associated editor of several journals and he is the international program co-chair of the IFAC World Congress 2020 in Berlin. The research of his group focuses on the fusion of learning and optimal and predictive control, control for autonomous systems, decision-making under uncertainty, cyberphysical systems.  The considered fields of applications span from automotive applications and robotics to process automation and biotechnology.



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