Adaptation of a path planning algorithm for UGV in precision agriculture

A great interest in self-driven vehicles has developed in the field of robotics and more generally in the industrial sector in the last few decades, and the number of applications where these vehicles are used is growing strongly. A clear example of this phenomenon are the efforts made by several automotive in terms of research and development, to manufacture increasingly competitive, safe and precise Autopilots. This is also due to cutting-edge on-board computers, the development of highly precise and performing sensors, and the advent of the 5G network, which is also aimed to ensure an unprecedented V2X communication, especially thanks to a new architecture called "network slicing". The robotics sector is now focused on providing solutions that may promote and improve the man-machine collaboration in agriculture as well as in other areas closely related to the civil sphere, therefore not only for military uses and space exploration, as it used to be. This process has seen an acceleration this year for the emergence of Covid-19, which has become a global pandemic. This situation has highlighted, now more than ever, the need to rely on autonomous instruments that, for example, transport medical equipment or essential commodities, without running the risk to get in contact with other people or the need for anyone to leave home. In this context, the aim of this thesis work is the creation of a UGV that can run independently, safely and efficiently through rough and uneven terrain, as for agricultural fields or unpaved roads, by using the RRT* (rapidly exploring random tree) path planner. The latter manages to accomplish its task also thanks to the collaboration with a UAV that, by means of the aerial photogrammetric survey method, can generate high-precision georeferenced orthophotos that are later processed by a GIS (geographic information system) software to generate two static maps, a DTM (Digital Terrain Model) and a binary mask. In detail, the project is designed to cover different project phases. Starting from the design phase, when the criticality of the problem is evaluated and possible solutions are identified, to the programming phase, in which a code has been developed that allows the planning of the route adapting to the problems that may arise in this type of terrain, up to the simulation and real test phase in the field.