The video shows the online control of a scale car with nonlinear model-predictive control (NMPC) and obstacle avoidance. The position is obtained by an indoor GPS system. The online optimization within the NMPC is done by the software OCPID-DAE1.

This video shows our quadrocopter flying indoor by manual control.

This video shows an KUKA Youbot detecting a red ball with a stereo camera module XTION PRO LIVE.

The video shows an application with the KUKA youBot robot. The task is to mark predefined positions automatically with a high precision. The high accuracy is achieved with an external laser based positioning system.

For a predefined setting, an optimal obstacle avoidance maneuver was computed. The derived solution is then applied at the model car.

The video presents a control experiment for interacting vehicles in a road network. The approach combines a high-level controller for the generation of collision-free trajectories and a low-level dynamic inversion controller for path tracking. The high-level controller uses model-predictive control for generalized Nash equilibrium problems, which are used to coordinate the vehicles. The control concept was implemented and validated on scale robots.

The video shows results from a flight test. Model-predictive control is used to generate collision-free flight paths in realtime. The desired flight paths are visualized to the pilot using a tunnel in the sky, which the pilot aims to follow. The method is capable to avoid obstacles, which can be created from a ground station using a data link.