In this thesis I will introduce how to determinant the orientation and position of an Unmanned Aerial Vehiche (UAV). I'm going to introduce the state description methods and how to measure it with sensors. I will show, how to construct a Kalman-filter based state prediction algorithm, which good for predict the state of a non-linear system, like an aeroplane.
The development started in the AMORES Robotics project. The goal of the project was to research and develop autonomous mobile robotics technologies.
The described algorithm going to be an important part of a microcontroller based auto pilot system. In my thesis I'm going to introduce the components of an auto-pilot system and how to connect with the state prediction algorithm. I'm going to detail the implementation questions, the used numerical methods and their realizations. During my work I'm going to create simulation of the state predictor, and implement it in the microcontroller. I will introduce the used and previously created hardware components and the required software enviroment. To proof the implementation, I will develop a test branch, and compare the solution with the simulation.