From simulated to real scenarios: a framework for multi-UAVs A. Cesetti 1 , A. Mancini 1 , E. Frontoni 1 , P. Zingaretti 1 , and S. Longhi 1 Universit´a Politecnica delle Marche, DIIGA, Ancona, Italy {cesetti,mancini,frontoni,zinga}@diiga.univpm.it sauro.longhi@univpm.it Abstract. In this paper a framework for simulation of Unmanned Aerial Vehicles (UAVs), oriented to rotary wings aerial vehicles, is presented. It allows UAVs simulation for stand-alone agent or multi-agent exchang- ing data in cooperative scenarios. The framework, based on modularity and stratification in different specialized layers, allows an easy switching from simulated to real environments, thus reducing testing and debug- ging times. CAD modelling supports the framework mainly with respect to extraction of geometrical parameters and virtualization. Useful appli- cations of the framework include pilot training, testing and validation of UAVs control strategies, especially in an educational context, and simu- lation of complex missions. Key words: modeling framework for robots and environments, testing and validation of robot control software, simulated sensors and actuators, UAV. 1 Introduction Nowadays mobile robotics is going through a period of constant growth, pro- ducing tangible results in both scientific and commercial areas. However there is a significant difference between the results achieved with ground vehicles and aircrafts respectively. Unmanned Aerial Vehicles (UAVs) represent a challenging research field due on one hand to the complexity of systems and operating en- vironment and on the other hand to the variety of tasks they can perform. The range of aerial vehicles is ample (blimps, gliders, kites, planes, helicopters, etc.) and each one has a particularity that makes the difference in a mathematical description of physical phenomena. Mathematical models are really complex because an aerodynamic description has to be taken into account and dynamics is also influenced by turbulence from rotors and wind. Small-scale helicopters probably represent the most difficult systems to model because of the complex nature of their dynamics. At the same time their unique manoeuvrability capabilities (including hovering, vertical take- off and landing) and multiple flight modes make them able to perform various tasks, such as surveillance, search and rescue, photogrammetry and mapping. In many cases, complex missions can be carried out by fleets of cooperating autonomous and heterogeneous vehicles, hence interaction, cooperation and su- pervision become the main problems. UAVs applications development is closely