Docking a UAV using a robotic arm and computer vision

The aim of this Thesis is to research the possibility of docking an airborne UAV using a robotic armand computer vision. In the scope of the SHERPA project on robot collaboration in Alpine rescue scenario‘s a robust and autonomous way of retrieving small scale UAV‘s is required. In a scenario where landing the UAV on a mobile ground station is not possible and landing on the ground could be harmful to the drone, docking the UAV while it is airborne using a robotic arm would be the best solution. In this work a system is presented to accurately follow and dock an UAV near a ground vehicle using an external monocular camera mounted on a robotic armand internal UAV sensors. The system combines the strengths of visual pose estimation and IMU motion tracking while minimizing the effect of their weaknesses. The result is a system with an accurate pose estimate and which is also robust through temporary occlusion or motion blur. A functional proof of principle system was implemented using Robotic Operating System and a KUKA LWR4+ robot armto show the advantages provided by the system.