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This paper describes the design and development of a virtual environment conceived to support flight operations of an Unmanned Air Vehicle (UAV) used for wind mapping in the proximity of existing or planned wind farms. The virtual environment can be used in pre-flight briefings aiming to define a trajectory from a list of waypoints, to change and eventually re-plan the mission in case of intersection with no fly zones, to simulate the mission, and to preview images/videos taken from the UAV on-board cameras. During flight, the tool can be used to compute the wind speed along the trajectory by analyzing the data streaming from the UAV. The integration of Augmented Reality (AR) techniques in the flight environment provides assistance in remotely piloted landings, and allows visualizing flight and environmental information that are critical to the mission.

The high number of hull losses is a main concern in the UAV field, mostly due to the high cost of on-board equipment. A crashworthiness design can be helpful to control the extent and position of crash impact damage, minimizing equipment losses. However, the wide use of composite materials has recently put the accent on the lack of data about the behavior of these structures under operative loads, such as the crash conditions. This paper presents the outcome of a set of tests carried out to achieve a controlled crush of UAV structures, and to maximize the Specific Energy Absorption. In this work, a small-scale experimental test able to characterize the energy absorption of a Carbon-fiber-reinforced polymer under compression was developed introducing self-supporting sinusoidal shape specimens, which avoid the need for complex anti-buckling devices.

The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations “Sense and Avoid” or “Detect and Avoid” capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles.