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.

The video shows the drive of an autonomous car on the testtrack of the University of the Bundeswehr Munich. The path following and path planning tools with collision avoidance capability have been developed within the dtec.bw project MORE by the Engineering Mathematics Group (LRT 1.1) of the Department of Aerospace Engineering.