Development and implementation of a customized flight control system for an Unmanned Aerial Vehicle operating in a connected Industry environment

The forthcoming industrial environments will require a high level of automation to be flexible and adaptive enough to comply with the increasingly faster and low-cost market demands. Autonomous and collaborative robots will have an ever-greater role in this context. In this view, the FIXIT project aims at providing an interactive support for the human operator, within an industrial or logistic environment compliant with the Industry 4.0 requirements. The objective of this thesis is to develop and implement a customized flight control system for a commercial UAV (Unmanned Aerial Vehicle). The system is going to be implemented on the aerial node of the robotic FIXIT platform (a multi-element robotics platform consisting of a mobile robot and an aerial robotic system). The system interacts with a path planning and obstacle detection algorithm running on a separate companion computer located on board. The positioning system for the robot is an UWB (Ultra Wide Band) localization system mounted on the CIM4.0 digital pilot line. Many papers and projects implement the UWB as a localization system but just a few of them actually use it on UAVs. The initial analysis of the state of art was followed by two phases. In the first one, some simulations have been made in which the UAV was able to perform missions and to navigate in the simulated environment through way-points computed by means of an obstacle avoidance algorithm. In the second one, the real tests showed that the drone behaves like in the simulation tests, but with some uncertainties and errors that have to be taken into account. Some tests were made outdoor. With a correct calibration and a correct configuration of the Pixhawk board, the UAV was able to takeoff, follow a static defined path and land. Some other tests were made indoor. The UWB positioning system and the chosen sensors has been widely tested and they revealed to be the best ones for the environment in which the UAV was tested.