Design and testing methodologies for UAVs under extreme environmental conditions

L'abstract è presente nell'allegato / the abstract is in the attachmen

Numerical modelling of sinusoidal brushless motor for aerospace actuator systems

The interest in electromechanical actuators (EMA) has been growing because of the development of next generation aircraft, based on the More Electric design. Electromechanical actuators have been gaining increased acceptance as they are becoming more and more safety-critical actuation devices: for prognostics and health management purposes of EMA, reliable and representative simulation models are needed in order to identify failures. This paper presents a multi domain model of EMA and it focuses on the numerical modelling of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice of the multi domain simulation is necessary to improve the simplifying hypotheses that are typically considered in numerical models and that are mostly used for prognostic analyses of electromechanical actuators

Modelling and simulation of a tethered UAS

Battery lifetime is one of the most challenging problems for Unmanned Aircraft System (UAS) applications. Multi-rotor platforms usually suffer limited payload capabilities and flight time. To overcome this problem, tethered vehicle solutions have been developed. In this paper, we propose a mathematical model able to describe the dynamic behaviour of a tethered UAS. The approach is based on the Finite Element Method and Lagrange’s Equation of motion. The cable is divided into segments linked to each other by spherical joints. An additional virtual element is used to represent the vehicle dynamics. Compared to other works, a variable cable length is implemented as well as wind effects on overall system are included. Simulation results corroborate that the proposed approach is able to simulate how the cable and UAS work in different operating conditions, such as take-off and hovering in both still air and wind scenario

A Risk-based Path Planning Strategy to Compute Optimum Risk Path for Unmanned Aircraft Systems over Populated Areas

The large diffusion of Unmanned Aircraft Systems (UAS) requires a suitable strategy to design safe flight missions. In this paper, we propose a novel path planning strategy to compute optimum risk path for UAS over populated areas. The proposed strategy is based on a variant of the RRT* (Rapidly-exploring Random Tree "Star") algorithm, performing a risk assessment during the path planning phase. Like other RRT-based algorithms, the proposed path planning explores the state space by constructing a graph. Each time a new node is added to the graph, the algorithm estimates the risk level involved by the new node, evaluating the flight direction and velocity of the UAS placed in the analyzed node. The risk level quantifies the risk of flying over a specific location and it is defined using a probabilistic risk assessment approach taking into account the drone parameters and environmental characteristics. Then, the proposed algorithm computes an asymptotically optimal path by minimizing the overall risk and flight time. Simulation results in realistic environments corroborate the proposed approach proving how the proposed risk-based path planning is able to compute an effective and safe path in urban areas

Unmanned Aircraft Systems Performance in a Climate-Controlled Laboratory

AbstractDespite many research studies focus on strategies to improve autopilot capabilities and bring artificial intelligence onboard Unmanned Aircraft Systems (UAS), there are still few experimental activities related to these vehicle performance under unconventional weather conditions. Air temperature and altitudes directly affect thrust and power coefficients of small scale propeller for UAS applications. Reynolds numbers are usually within the range 10,000 to 100,000 and important aerodynamic effects, such as the laminar separation bubbles, occur with a negative impact on propulsion performance. The development of autonomous UAS platforms to reduce pilot work-load and allow Beyond Visual Line of Sight (BVLOS) operations requires experimental data to validate capabilities of these innovative vehicles. High quality data are needed for a deep understanding of limitations and opportunities of UAS under unconventional flight conditions. The primary objective of this article is to present the characterization of a propeller and a quadrotor capabilities in a pressure-climate-controlled chamber. Mechanical and electrical data are measured with a dedicated test setup over a wide range of temperatures and altitudes. Test results are presented in terms of thrust and power coefficient trends. The experimental data shows low Reynolds numbers are responsible for degraded thrust performance. Moreover, details on brushless motor capabilities are also discussed considering different temperature and pressure conditions. The experimental data collected in the test campaign will be leveraged to improve UAS design, propulsion system modelling as well as to provide guidelines for safe UAS operations in extreme environments

UAS testing in low pressure and temperature conditions

The increasing demand of UAS has generated interest in the scientific community to understand how the environmental parameters affect performance of these emerging vehicles. A bias in the existing tests has been the nonreproducibility of the same climatic conditions. Therefore, UAS have not been fully exploited by the marker so far. Standard protocols for UAS testing in unconventional weather conditions have not been investigated from both industry and academic research. Temperature and pressure are environmental parameters that affect the aerodynamics of Unmanned Aircraft Systems (UAS). Low Reynolds numbers are common for small scale UAS and have a strongly influence on propeller and vehicle capabilities. In the past years, experimental studies on the effects of low Reynolds numbers have been carried out in wind tunnel facilities in conventional atmospheres (ambient temperature and pressure). Moreover, the complexity of the aerodynamic field results in propeller and full vehicle performance prediction methods with limited accuracy. In this paper an experimental setup inside a climatic and hypobaric laboratory is used to highlight temperature and pressure influence on single propeller and full vehicle performance in static conditions (hover). Test results are discussed and provided to the reader, highlighting the complexities of the measurements when extreme temperature and low pressure are set. The main contribution of this study is a set of experimental data to pave the way for a deep investigation on harsh environmental conditions on UAS propulsion system

Model-In-the-Loop Testing of Control Systems and Path Planner Algorithms for QuadRotor UAVs

Real systems, as Unmanned Aerial Vehicles (UAVs), are usually subject to disturbances and parametric uncertainties, which could compromise the mission accomplishment, considering particularly harsh environments or challenging applications. For this reason, the main idea proposed in this research is the design of the on-board software, as autopilot software candidate, for a multirotor UAV. In detail, the inner loop of the autopilot system is designed with a variable structure control system, based on sliding mode theory, able to handle external disturbances and uncertainties. This controller is compared with a simple Proportional-Integral-Derivative controller. The key aspects of the proposed methodology are the robustness to bounded disturbances and parametric uncertainties of the proposed combination of guidance and control algorithms. A path-following algorithm is designated for the guidance task, which provides the desired waypoints to the control algorithm. Model-in-the-loop simulations have been performed to validate the proposed approaches. Computationally efficient algorithms are proposed, as combination of a robust control system and path planner. Extensive simulations are performed to show the effectiveness of the proposed methodologies, considering both disturbances and uncertainties

A novel distributed architecture for UAV indoor navigation

Abstract In the last decade, different indoor flight navigation systems for small Unmanned Aerial Vehicles (UAVs) have been investigated, with a special focus on different configurations and on sensor technologies. The main idea of this paper is to propose a distributed Guidance Navigation and Control (GNC) system architecture, based on Robotic Operation System (ROS) for light weight UAV autonomous indoor flight. The proposed framework is shown to be more robust and flexible than common configurations. A flight controller and companion computer running ROS for control and navigation are also included in the section. Both hardware and software diagrams are given to show the complete architecture. Further works will be based on the experimental validation of the proposed configuration by indoor flight tests

A Mission Coordinator Approach for a Fleet of UAVs in Urban Scenarios

Abstract The use of Unmanned Aerial Vehicles (UAVs) is now common, but although they have been for various applications, there are still a lot of challenges that need to be overcome. One key issue is related to standardizing the use of these vehicles in urban environments and guaranteeing a minimum risk level for the population. To rise to these challenges, autonomous strategies that optimize and coordinate vehicles in cooperative missions and avoid human operators should be developed. The novelty of this paper is the development of an autonomous urban mission coordinator, which is responsible for the high-level logistics of a fleet of heterogeneous vehicles. A multi-variable weighted algorithm based on a tree optimization method is also proposed