  The goal of this thesis is to propose the combination of
Control-Barrier-Functions (CBF) with Model-Predictive-Control (MPC) resulting
in the novel Model-Predictive-Control-Barrier-Function (MPCBF). It can be
shown, that the performance of the MPCBF surpasses the performance of the CBF
due to the increased time horizon of the MPC. Moreover, the MPCBF was applied
to a quadrotor, a system strongly in need of fast and predictive control. Using
the MPCBF, the quadrotor was able to avoid obstacles, which the CBF failed to
avoid due to the relative speed of the obstacle. The results of this work are
experimentally validated.

Robotics;Systems and Control;Systems and Control;Optimization and Control