Studies of electrical engineering and information technology at the Karlsruhe Institute of Technology (KIT).
Bachelor's thesis at the Institute of Control Systems (IRS) on power flow calculation algorithms (2016).
Internship with Siemens Healthineers in Princeton, NJ on a pulse sequence optimization for magnetic resonance fingerprinting (2017).
Master's thesis at the IRS on the development and analysis of Reinforcement-Learning-based controlers for differential games with an unknown cooperation partner (2018).
Shared control of heterogenous robot swarms
Heterogenous swarms of robots are able to manage tasks that exceed the abilities of the individual robot systems by far.
This makes these robot swarms especially suited for challenging tasks like the exploration of potentially dangerous environments, medical applications and industrial production.
During regular operation, the swarm works fully automated; however, situations might occur that require the operator's intervention either because the automation lacks the ability to deal with the situation or because the operator wants to deviate from the automated procedure for other reasons. Since the manual operation of multiple robots would overwhelm the operator, the automation has to stay active during the intervention and support the operator. This leads to a shared control with both the automation and the operator partly in control of the system.
Ideally, solely the parts of the control that are required to perform the intervention should be handed over to the operator. All other parts should remain automated to assist the operator optimally.