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Thanks to recent technological advances, a new generation of low-cost, small, unmanned aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling unprecedented applications but, at the same time, new threats are arising linked to their possible misuse (e.g., drug smuggling, terrorist attacks, espionage). In this paper, the main challenges related to the problem of drone identification are discussed, which include detection, possible verification, and classification. An overview of the most relevant technologies is provided, which in modern surveillance systems are composed into a network of spatially-distributed sensors to ensure full coverage of the monitored area. More specifically, the main focus is on the frequency modulated continuous wave (FMCW) radar sensor, which is a key technology also due to its low cost and capability to work at relatively long distances, as well as strong robustness to illumination and weather conditions. This paper provides a review of the existing literature on the most promising approaches adopted in the different phases of the identification process, i.e., detection of the possible presence of drones, target verification, and classification.

The exploitation of offshore wind energy by means of floating wind turbines is gaining traction as a suitable option to produce sustainable energy. Multi‐rotor floating wind turbines have been proposed as an appealing option to reduce the costs associated with manufacturing, logistics, offshore installations, and operation and maintenance of large wind turbine components. The development of such systems is forestalled by the lack of a dedicated tool for dynamics and load analysis. Standard codes, such as FAST by NREL, offer the desired fidelity level but are not able to accommodate multi‐rotor configurations. A few experimental codes have been also proposed, which may accommodate multi‐rotor systems, but low flexibility makes them impractical to study a vast range of innovative multi‐rotor FWTs concepts. To close the gap, this work presents the development and comprehensive benchmark of a fully coupled aero‐hydro‐servo‐elastic tool able to easily accommodate arbitrary platform and tower geometries and the number of wind turbines employed. Development is carried out in Modelica, which allows for the employment of the same code functionality in a virtually unlimited number of physical configurations. Full blade‐element momentum capabilities are achieved by integrating into Modelica the well‐established NREL aerodynamic module AeroDyn v15 within FAST v8. Structural dynamics of tower and blades are implemented through a lumped‐element approach. Hydrodynamic loads are computed by employing the DNV software SESAM WADAM. Thorough benchmark is performed against FAST, and positive results are obtained. The dynamic performance of a two‐rotor floating wind turbine is finally assessed considering different turbulence spectrums.

This paper describes a Mission Definition System and the automated flight process it enables to implement measurement plans for discrete infrastructure inspections using aerial platforms, and specifically multi-rotor drones. The mission definition aims at improving planning efficiency with respect to state-of-the-art waypoint-based techniques, using high-level mission definition primitives and linking them with realistic flight models to simulate the inspection in advance. It also provides flight scripts and measurement plans which can be executed by commercial drones. Its user interfaces facilitate mission definition, pre-flight 3D synthetic mission visualisation and flight evaluation. Results are delivered for a set of representative infrastructure inspection flights, showing the accuracy of the flight prediction tools in actual operations using automated flight control.

A multi‐rotor wind turbine (MRWT) is a concept that can reduce the size of the rotor blades compared to a single‐rotor wind turbine (SRWT). Making a cost‐optimized MRWT requires a detailed understanding of its stability properties. This paper aims to establish a physical and intuitive representation of whirling modes for three‐bladed isotropic SRWT and MRWT. An aeroelastic simulation of a nonlinear SRWT model is presented to empathize the importance of whirling. The whirling concept is introduced by simplifying the complexity of the wind turbine rotor into two models. From the models, edgewise and flapwise whirling modes are analyzed. An analytical model of a two‐rotor wind turbine is examined to present the edgewise whirling modes of MRWT. The flapwise whirling modes for MRWT are introduced by using results from edgewise whirling and findings from previous research. The MRWT whirling analysis shows whirling from multiple rotors creates reaction forces to the supporting structure when the rotors have the same speed. This results in whirling coupling modes at the same natural frequency. One is a rotor symmetric whirling mode where the rotors whirling are in phase and a rotor asymmetric mode where whirling of the rotors are out of phase. The whirling coupling effects are minimized in the case that the rotors have different speeds.

Multi‐rotor floating wind turbines are among the innovative technologies proposed in the last decade in the effort to reduce the cost of wind energy. These systems are able to offer advantages in terms of smaller blades deployed offshore, cheaper operations, fewer installations, and sharing of the floating platform. As the blade‐pitch actuation system is prone to failures, the assessment of the associated load scenarios is commonly required. Load assessment of blade‐pitch fault scenarios has only been performed for single‐rotor solutions. In this work, we address the effect of blade‐pitch system faults and emergency shutdown on the dynamics and loads of a two‐rotor floating wind turbine. The concept considered employs two NREL 5‐MW baseline wind turbines and the OO‐Star semi‐submersible platform. The blade‐pitch faults investigated are blade blockage and runaway, that is, the seizure at a given pitch angle and the uncontrolled actuation of one of the blades, respectively. Blade‐pitch faults lead to a significant increase in the structural loads of the system, especially for runaway fault conditions. Emergency shutdown significantly excites the platform pitch motion, the tower‐bottom bending moment, and tower torsional loads, while suppressing the faulty blade flapwise bending moment after a short peak. Shutdown delay between rotors increases significantly the maxima of the torsional loads acting on the tower. Comparison of blade loads with data from single‐rotor spar‐type study show great similarity, highlighting that the faulty blade loads are not affected by (1) the type of platform used and (2) the multi‐rotor deployment.

An aeroelastic analysis is carried out to assess the loads on a selected quad‐rotor wind turbine vis‐à‐vis those on an equivalent rated single‐rotor turbine, with a specific focus on a comparison of support structure loads (e.g., tower root, yaw‐bearing, and boom loads). A quad‐rotor wind turbine with combined rated power of 6 MW and a single‐rotor with equivalent machine rating are modeled in SIMAPCK coupled with AerodynV15 (including turbulent wind input from TurbSim) to calculate the aerodynamic loads. A correction for tower/boom shadow is implemented in Matlab to account for reduction in (axial) incoming wind due to the presence of support structures that carry the rotors. The performance of the quad‐rotor wind turbine, with the single‐rotor as baseline, is carried out for load cases selected from wind turbine certification standard (IEC‐61400‐1) covering the following: nominal loads under normal wind speed profile, fatigue loads under normal turbulence, and ultimate loads under extreme turbulence. Results show that, comparing the quad‐rotor tower root loads to those of the single‐rotor turbine under extreme turbulence, the side‐side force is up to 31% higher, the force‐aft bending moment is up to 15% higher, and the normal force is up to 46% higher due to additional boom/nacelle inertial loads.

Multi-rotor system (MRS) wind turbines can be a competitive alternative to large-scale wind turbines. In order to address the structural behavior of the turbine tower, an in-house aeroelastic tool has been developed to study the dynamic responses of a 2xNREL 5MW twin-rotor configuration wind turbine. The developed tool has been verified by comparing the results of a single-rotor configuration to a FAST analysis for the same simulation conditions. Steady flow and turbulent load cases were investigated for the twin-rotor configuration. Results of the simulations have shown that elasticity of the tower should be considered for studying tower dynamic responses. The tower loads, and deformations are not straightforward with the number of rotors added. For an equivalent tower, an additional rotor will increase the tower-top deflection, and the tower-base bending moment both in the fore-aft direction will be more than doubled. The tower torsional stiffness becomes a crucial factor in the case of a twin-rotor tower to avoid a severe torsional deflection. Tower natural frequencies are dominant over the flow conditions in regards to the loads and deflections.

We present a model-based approach to estimate the vertical profile of horizontal wind velocity components using motion perturbations of a multirotor unmanned aircraft system (UAS) in both hovering and steady ascending flight. The state estimation framework employed for wind estimation was adapted to a set of closed-loop rigid body models identified for an off-the-shelf quadrotor. The quadrotor models used for wind estimation were characterized for hovering and steady ascending flight conditions ranging between 0 and 2 m/s. The closed-loop models were obtained using system identification algorithms to determine model structures and estimate model parameters. The wind measurement method was validated experimentally above the Virginia Tech Kentland Experimental Aircraft Systems Laboratory by comparing quadrotor and independent sensor measurements from a sonic anemometer and two SoDAR instruments. Comparison results demonstrated quadrotor wind estimation in close agreement with the independent wind velocity measurements. However, horizontal wind velocity profiles were difficult to validate using time-synchronized SoDAR measurements. Analysis of the noise intensity and signal-to-noise ratio of the SoDARs proved that close-proximity quadrotor operations can corrupt wind measurement from SoDARs, which has not previously been reported.

Multi-rotor Unmanned Aerial Vehicles (UAVs), although originally designed and developed for defence and military purposes, in the last ten years have gained momentum, especially for civilian applications, such as search and rescue, surveying and mapping, and agricultural crops and monitoring. Thanks to their hovering and Vertical Take-Off and Landing (VTOL) capabilities and the capacity to carry out tasks with complete autonomy, they are now a standard platform for both research and industrial uses. However, while the flight control architecture is well established in the literature, there are still many challenges in designing autonomous guidance and navigation systems to make the UAV able to work in constrained and cluttered environments or also indoors. Therefore, the main motivation of this work is to provide a comprehensive and exhaustive literature review on the numerous methods and approaches to address path-planning problems for multi-rotor UAVs. In particular, the inclusion of a review of the related research in the context of Precision Agriculture (PA) provides a unified and accessible presentation for researchers who are initiating their endeavours in this subject.

Multi-rotor drones, a kind of unmanned equipment which is widely used in the military, commercial consumption and other fields, have been developed very rapidly in recent years. However, their short flight time has hindered the expansion of their application range. This can be addressed by utilizing hydrogen fuel cells, which exhibit high energy density, strong adaptability to ambient temperature, and no pollution emissions, as the power source. Accordingly, the application of hydrogen fuel cells as the power source in multi-rotor drones is a promising technology that has attracted significant research attention. This paper summarizes the development process of hydrogen fuel cell multi-rotor drones and analyzes the key obstacles that need to be addressed for the further development of hydrogen fuel cell multi-rotor drones, including structural light weight, hydrogen storage methods, energy management strategies, thermal management, etc. Additionally, prospects for the future development of hydrogen fuel cell multi-rotor drones are presented.