Studies of electrical engineering and information technology at Karlsruhe Institute of Technology (KIT). Bachelor’s thesis at the Light Technology Institute (LTI) on thermal characterization of LED systems (2011). Internship at Daimler AG in the Truck Powertrain E/E Development Department. Master’s thesis at the Institute of Control Systems (IRS) on the prediction of steering behavior using a model based on driver-specific movement primitives (2014). Member of the scientific staff of IRS since February 2015; PhD thesis: “Methods for inverse dynamic games with application to cooperative systems identification”.
Head of the research group “Cooperative Systems” since May 2020.
Modeling, Identification and Adaption in Cooperative Control Systems
Automation trends are increasingly including a close interaction and cooperation between automated systems and people in order to exploit their respective strengths. This yields a great potential for broad application in, for example, innovative driver assistance systems, the development of intelligent machine tools and robot-assisted rehabilitation in medicine.
Successful human-machine interaction demands a suitable model for describing the behavior of the cooperating human. This model can be used to identify the model parameters that explain the behavior of an individual person. On this basis, the machine can be optimally adapted for safe and effective cooperation. Dynamic game theory provides a powerful mathematical framework with great potential for an application in this field.
My research focuses on the following:
- Modeling cooperative systems using dynamic game theory
- Investigation of reinforcement learning approaches to describe adaptation processes
- Online identification in cooperative systems through the efficient solution of inverse dynamic games
- Development of game-theoretical methods for intention detection based on measurement data
- The application of these methods for identifying human behavior during a cooperation with machines
