The rapid development in the field of Unmanned Aerial Vehicles (UAVs) is driven by new challenging applications in agriculture, logistics, inspection and smart manufacturing. The future keys in this domains are the abilities to autonomously interact with the environment and with other robotic systems. One possibility to manipulate the environment is to attach a robotic arm to a UAV. Such aerial manipulation scenarios are extended to cooperative aerial manipulation when other robots are cooperating with the manipulating UAV to achieve a global objective. In order to approach these key capabilities, this thesis is contributing control solutions for UAVs, aerial manipulation and cooperative aerial manipulation scenarios. From a control engineering perspective, the challenges for such scenarios are the complex fast nonlinear dynamics of UAVs and dynamically changing control objectives and system topology. This complexity and speed conflicts with their limited computational power onboard. In this thesis, these challenges are addressed with real-time nonlinear model predictive control.
Members of the defence committee:
- Chairman: Prof. Dr.-Ing. Jean-Régis Hadji-Minaglou, University of Luxembourg
- Vice-chairman: Prof. Dr. Gianluca Antonelli, University of Cassino and Southern Lazio, Italy
- Supervisor: Prof. Dr.-Ing. Holger Voos, University of Luxembourg
- Member: Dr. Somasundar Kannan, Luxembourg
- Member: Prof. Dr. Erdal Kayacan, Aarhus University, Denmark