Several human operators control a single Unmanned Aerial Vehicle. This is not scalable. Recently, the trend is to have a single human operator to handle a group of Unmanned Aerial Vehicles in order to have a system able to work with thousands of Unmanned Aerial Vehicles flying over a country. Swarm Intelligence (the emergent, collective of social insect colonies) provides the guidelines to design such a decentralized system. In particular, social insects are capable of achieving several things, such as building and defending a nest, foraging for food, taking care of the brood, allocating labor, forming bridges.This thesis presents a framework for decentralized control of a swarm of Unmanned Aerial Vehicles based on the artificial potential functions characterized by attractive and repulsive properties, which are used respectively to achieve the goal and to avoid collisions. Each vehicle of the swarm makes use of limited information from others, and furthermore it is assumed to have a simple dynamic and to be identified as an agent. In this scheme, multiple agents in a swam are able to reach a configuration and to maintain it, while migrating as a group and avoiding collisions among each other. Therefore, the behaviors of the swarm system proposed in this thesis are group migration and configuration, and include collision avoidance.In particular, this thesis evaluates different potential expressions in order to determine how quickly the swarm converges to a desired direction and velocity, and how robust the swarm is against collisions among the agents. Furthermore, two metrics estimate which potential is the best one in a certain scenario. One quantifies how quickly the swarm converges to the given velocity, and the second evaluates how robust the potential is against collisions. The simulation results show that the proposed scheme can construct a swarm system with the capability of group migration and configuration in the presence of obstacles, by using a Non Equipaggiato -rendendo il sistema di controllo non scalabile. Attualmente, nell'ambito del controllo di questo tipo di veicoli, la tendenzaé quella di gestire un gruppo di Unmanned Aerial Vehicle tramite un solo operatore in modo da avere un sistema in grado di operare con migliaia di Unmanned Aerial Vehicle che volano sopra una nazione. Swarm Intelligence, basata sui cosiddetti insetti sociali, fornisce le linee guida per progettare sistemi decentralizzati. In particolare, gli insetti sociali sono in grado di perseguire diversi obiettivi, dalla costruzione e difesa del nido, alla ricerca del cibo, al prendersi cura del nido, all'assegnazione di squadre di operai, alla costruzione di ponti.Questa tesi presenta un framework per il controllo decentralizzato di uno sciame di Unmanned Aerial Vehicle basato su funzioni di potentiale artificiale caratterizzate da proprietá attrattive e repulsive, che sono usate rispettivamente per raggiungere l'obiettivo e per evitare le eventuali collisioni. Ciascun veicolo dello sciame utilizza un numero limitato di inf...