GPS-based autonomous navigation of unmanned ground vehicles in precision agriculture applications

The global population is growing exponentially and the actual agricultural techniques and resources will not be able to feed every person on the Earth in a few years. To account for this serious problem, groups of research are focusing their attention on precision agriculture, because it looks for the improvement of the productivity and efficiency of both agricultural and farming production processes, while reducing the environmental impact, exploiting automation and robotics. The thesis aims to design and develop a solution, based on GPS, for the autonomous navigation problem in precision agriculture, using only few sensors: an Inertial Measurement Unit, a GPS receiver and a depth camera, in order to be cost effective. The proposed goal has been achieved through a system of inter-operating sub-components, that have to share information and collaborate each other in order to provide a complete autonomous navigation. In particular, the main involved entities are: a localization filter, a global and a local path planning algorithms and an obstacle avoidance approach, that have been developed and can cooperate each other by means of the Robot Operating System. Eventually, the proposed solution has been tested in a simulation environment, through different possible scenarios providing good results in each of them. However, it may be considered as a starting point for future improvement in the field of autonomous navigation for precision agriculture.