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A unified approach to cooperative and non-cooperative Detect-and-Avoid (DAA) is a key enabler for Remotely Piloted Aircraft System (RPAS) to safely and routinely access all classes of airspace. In this paper state-of-the-art cooperative and non-cooperative DAA sensor/system technologies for manned aircraft and RPAS are reviewed and the associated multi-sensor data fusion techniques are discussed. A DAA system architecture is presented based on Boolean Decision Logics (BDL) for selecting non-cooperative and cooperative sensors/systems including both passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance - Broadcast (ADS-B). After elaborating the DAA system processes, the key mathematical models associated with both non-cooperative and cooperative DAA functions are presented.

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.

Having connectivity among ground vehicles brings about benefits in fuel economy improvement, traffic mobility enhancement and undesired emission reductions. On the other hand, Unmanned Aerial Vehicles (UAV) have proven to help in getting aerial data to end users in an affordable manner. When UAVs are equipped with cameras, they can get information about the terrain they are flying over. Moreover, using Vehicle-to-Everything (V2X) communication technologies, it is possible to form a communication link between UAVs and the connected ground vehicle networks comprising of Connected and Autonomous vehicles (CAVs). To investigate and exploit the potential benefits and use cases of a broad vehicle network, a microscopic traffic simulator modified previously by our group with the addition of nearby UAVs is used to integrate simulated Connected UAVs flying above a realistic simulation of heterogeneous traffic flow containing both CAVs and non-CAVs.

This paper relates to the design and development of a multi-modal UAV capable of aerial flight and underwater propulsion. A novel hybrid propulsion system has been manufactured and tested. Consisting of folding blades, the propeller has been optimized for propulsion both in air and water. The critical water to air transition phase is achieved by an additional impulsive thruster powered by a C02 cartridge. To decrease the drag in underwater cruise and reduce the potential damage when the vehicle impacts the water, a morphing wing has been developed. This consists of foam-carbon fiber lay-up constructed wings in a variable sweep configuration. The actuation of the sweep is achieved by linear servos mounted on the sleeve shaped spar. An integrated prototype is constructed, using an unconventional, anhedral horizontal stabilizers to allow clearance for the morphing wing.

Unmanned Aerial Vehicles (UAVs) provide the ability to perform a variety of experimental tests of systems and unproven research technologies, including new autopilot systems and obstacle avoidance capabilities, without risking the lives of human pilots. This paper describes the activities of design, optimization, and flight operations of a UAV conceived at Clarkson University (USA) and equipped to perform wind speed measurements to support wind farmsite planning. The UAV design has been assisted and validated by the use of an automatic virtual environment for the assisted design of civil UAVs. This tool can be used as a “computing machine” for civil UAVs. The operator inputs the mission profile and other generic parameters and data about performance, aerodynamics, and weight breakdown are extracted. A mathematical model of the UAV for flight simulation and its dynamic computations, along with automatic drawing is also produced.

One of the primary hazards associated with the operation of Unmanned Aircraft (UA) is the controlled or uncontrolled impact of the UA with terrain or objects on the terrain (e.g., people or structures). National Aviation Authorities (NAAs) have the responsibility of ensuring that the risks associated with this hazard are managed to an acceptable level. The NAA can mandate a range of technical (e.g., design standards) and operational (e.g., restrictions on flight) regulatory requirements. However, work to develop these regulations for UA is ongoing. Underpinning this rule-making process is a safety case showing how the regulatory requirements put in place ensure that the UA operation is acceptably safe for the given application and environment.

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.

Global Navigation Satellite Systems (GNSS) can support the development of low-cost and high performance navigation and guidance architectures for Unmanned Aircraft Systems (UAS) and, in conjunction with suitable data link technologies, the provision of Automated Dependent Surveillance (ADS) functionalities for cooperative Sense-and-Avoid (SAA). In non-cooperative SAA, the adoption of GNSS can also provide the key positioning and, in some cases, attitude data (using multiple antennas) required for automated collision avoidance. A key limitation of GNSS for both cooperative (ADS) and non-cooperative applications is represented by the achievable levels of integrity. Therefore, an Avionics Based Integrity Augmentation (ABIA) solution is proposed to support the development of an Integrity-Augmented SAA (IAS) architecture suitable for both cooperative and non-cooperative scenarios.

Multi-Sensor Data Fusion (MSDF) techniques involving satellite and inertial-based sensors are widely adopted to improve the navigation solution of a number of mission- and safety-critical tasks. Such integrated Navigation and Guidance Systems (NGS) currently do not meet the required level of performance in all flight phases of small Remotely Piloted Aircraft Systems (RPAS). In this paper an innovative Square Root-Unscented Kalman Filter (SR-UKF) based NGS is presented and compared with a conventional UKF governed design. The presented system architectures adopt state-of-the-art information fusion approach based on a number of low-cost sensors including; Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Navigation (VBN) sensors.

Accurate and robust tracking of objects is of growing interest amongst the computer vision scientific community. The ability of a multi-sensor system to detect and track objects, and accurately predict their future trajectory is critical in the context of mission- and safety-critical applications. Remotely Piloted Aircraft System (RPAS) are currently not equipped to routinely access all classes of airspace since certified Detect-and-Avoid (DAA) systems are yet to be developed. Such capabilities can be achieved by incorporating both cooperative and non-cooperative DAA functions, as well as providing enhanced communications, navigation and surveillance (CNS) services. DAA is highly dependent on the performance of CNS systems for Detection, Tacking and avoiding (DTA) tasks and maneuvers.

The implementation of Synthetic Jet Actuators (SJAs) on Unmanned Aerial Vehicles (UAVs) provides a safe test-bed for analysis of improved performance, in the hope of certification of this technology on commercial aircraft in the future. The use of high resolution numerical methods (i.e. CFD) to capture the details of the effects of SJAs on flows and on the hosting lifting surface are computationally expensive and time-consuming, which renders them ineffective for use in real-time flow control implementations. Suitable alternatives include the use of Reduced Order Models (ROMs) to capture the lower resolution overall effects of the jets on the flow and the hosting structure. This research paper analyses the effects of SJAs on aircraft wings using a ROM for the purpose of determining the unsteady aerodynamic forces modified by the presence of the SJAs. The model developed is a 3D unsteady panel code where the jets are represented by source panels.

In this paper the finite element model of an Unmanned Aerial Vehicle is updated by using experimental data coming from a standard ground vibration test in order to improve the numerical-experimental correlation. A sensitivity-based updating methodology that iteratively minimizes a residual vector, defined on the modal parameters (e.g. natural frequencies and mode shapes), is considered to identify the unknown values of the updating parameters. The structure under investigation is the Clarkson University Golden Eagle UAV. An initial numerical model of the structure is obtained by assembling the individual components previously updated which included wings, fuselage, horizontal tail, vertical tails and tail booms. As a result the identification procedure shifts its focus on the joints between UAV elements which could not be modeled accurately in earlier investigations.