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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.

New locations for onshore technology, which have not been considered so far, must be developed to increase the total installed capacity of renewable energies, especially wind energy. For this purpose, cost-effective wind turbines, even in difficult-to-access locations, such as mountainous and high-mountainous areas, must be designed. This paper presents a novel wind turbine with a related control system that meets these requirements. The proposed turbine uses a multi-rotor configuration with five rotors arranged in a star shape configuration. Each rotor drive train combines up to 12 generators in a maintenance-friendly multi-generator concept. A suitable observer-based control for load mitigation in the full-load region is proposed for the multi-rotor and multi-generator design. Simulations are used to demonstrate the applicability and practical benefits of this concept.

The development of multi-rotor helicopter concepts, driven by the active introduction of brushless electric motors, leads to the necessity of assessing the multi-rotor scheme main advantages implementing possibility and determining the rational areas of its application. The article analyzes the concept of a multi-rotor platform with a distributed power plant. Parametric study of characteristics depending on the number of rotors for a line of multi-propeller aircraft with take-off weight from 0.5 to 120 tons was carried out. Evaluation of weight and dimensional characteristics of blades, main rotor heads, gear boxes, as well as power wires of electric motors and structure beams connecting the elements of the distributed power plant is obtained. Evaluation of drag and thrust losses on blowing, as well as power requirements for typical flight modes was carried out. Estimation of the required number of rotors for the implementation of the gearless condition and flight safety with one engine failed are obtained. Rational areas of multi-rotor scheme application are defined.

This letter proposes a novel NMPC for multi-rotor aerial vehicles which is designed without stabilizing terminal costs or constraints in its cost function for stabilization. A growth bound sequence is derived from a tailored running cost to ensure the closed-loop stability and provide a measure of the performance of the proposed NMPC scheme. Furthermore, it facilitates the computation of a stabilizing prediction horizon that guarantees the asymptotic stability of the system. The performance of the proposed scheme is investigated through two sets of numerical simulations and compared against the traditional NMPC scheme for the application as proposed in (Kamel et al. , 2017). The results show superior performance of the proposed NMPC scheme in terms of tracking accuracy, convergence rate, and computation time.

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural networks. Thus, the system performance can be improved by replacing the classic allocation matrix, without using the aerodynamic inflow equations directly. The network training is performed offline, which requires low computational power. The target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation algorithm. Such a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work, because of its small size. We compared the mechanical torques commanded by the flight controller, i.e., the control input, to those actually generated by the actuators and established at the aircraft. It was observed that the proposed neural network was able to closely match them, while the classic allocation matrix could not achieve that. The allocation error was also determined in both cases. Furthermore, the closed-loop performance also improved with the use of the proposed neural network control allocation, as well as the quality of the thrust and torque signals, in which we perceived a much less noisy behavior.

Flight safety and reliability improvement is an important research issue in aerial applications. Multi-rotor drones are vulnerable to motor failures leading to potentially unsafe operations or collisions. Therefore, researchers are working on autonomous landing systems to safely recover and land the faulty drone in on a desired landing area. In such a case, a suitable landing zone should be detected rapidly in for emergency landing. Majority of the works related with autonomous landing utilize a marker and GPS signals to detect landing site. In this work, we propose a landing system framework that involves only the processing of images taken from the onboard camera of the vehicle. First, the objects in the image are determined by filtering and edge detection algorithm, then the most suitable landing zone is searched. The area that is free from obstacles and closest to the center of the image is defined as the most immediate and suitable landing zone. The method has been tested on 25 images taken from different heights and its performance has been evaluated in terms runtime on a single board computer and detection precision and recall values. The average measured runtime is 2.4923 seconds and 100% of precision and recall values are achieved for the images taken from 1m and 2m. The smallest precision and recall values are 79.1% and 81.2%, respectively.

Fully-actuated multi-rotor aerial platforms are receiving increasing research interests for the capability of six degree-of-freedom (DOF) motions such as hovering at non-horizontal attitude angles. Existing real world hardware and experiments have demonstrated such capability for a limited range of angles. This letter presents an aerial platform that achieves maneuvering at arbitrary attitudes with uniformly high thrust efficiencies. We propose a novel vectoring thrust force actuator by mounting a regular quadcopter on a passive mechanical gimbal mechanism. The UAV platform achieves full six-DOF motion with redundancies from four of these vectoring thrust actuators. We present the hierarchical controller, which generates high-level virtual wrench commands, allocations to actuators, and low-level actuator controls. We demonstrate the first real-world experiments of any pose maneuver over 360 degrees without requiring unwrapping rotations.

In the development of tidal energy, in order to extract more energy in the limited tidal farm, large-scale deployment of tidal current turbine is needed. In this paper, based on the PimpleDyMFoam solver in Open Source Fluid Dynamics Software (OpenFOAM), an effective numerical method is proposed for the two-dimensional VATCT (Vertical Axis Tidal Current Turbine). Secondly, the symmetrical simplified model is introduced to simulate the multi-rotor VATCT array. The interaction and wake characteristics of each turbine in different array layout schemes are studied in order to enhance the understanding of the interaction between multiple turbines. It is well known that the interaction between multiple turbines improves the overall power conversion efficiency, so it is of great significance to conduct in-depth research. The CFD numerical simulation results of the multi-rotor turbine array are compared in three aspects: blade force, wake flow field and power conversion efficiency. The results show that the power conversion efficiency of multi-rotor turbine array is higher than that of the stand-alone turbine. The smaller the spacing of each turbine in the multi-rotor turbine, the larger the overall output power. The single-row multi-rotor array in the form of opposite-rotation is more advantageous for energy acquisition. The analysis of the multi-rotor array from the aspect of the wake flow field can provide some insights into the reasons for the increased power conversion in the array. In this paper, force characteristics, wake characteristics and the energy efficiency of multi-rotor VATCT under different array layouts are considered comprehensively. The array optimization scheme proposed from the point of view of hydrodynamics will provide technical insights for the industrialization of large-scale VATCT array farm.

This work presents a method for estimating the model parameters of multi-rotor unmanned aerial vehicles by means of an extended Kalman filter. Different from test-bed based identification methods, the proposed approach estimates all the model parameters of a multi-rotor aerial vehicle, using a single online estimation process that integrates measurements that can be obtained directly from onboard sensors commonly available in this kind of UAV. In order to develop the proposed method, the observability property of the system is investigated by means of a nonlinear observability analysis. First, the dynamic models of three classes of multi-rotor aerial vehicles are presented. Then, in order to carry out the observability analysis, the state vector is augmented by considering the parameters to be identified as state variables with zero dynamics. From the analysis, the sets of measurements from which the model parameters can be estimated are derived. Furthermore, the necessary conditions that must be satisfied in order to obtain the observability results are given. An extensive set of computer simulations is carried out in order to validate the proposed method. According to the simulation results, it is feasible to estimate all the model parameters of a multi-rotor aerial vehicle in a single estimation process by means of an extended Kalman filter that is updated with measurements obtained directly from the onboard sensors. Furthermore, in order to better validate the proposed method, the model parameters of a custom-built quadrotor were estimated from actual flight log data. The experimental results show that the proposed method is suitable to be practically applied.

The operation of the rapidly growing unmanned aerial vehicles (UAV) and the promising urban aerial mobility (UAM) could have a significant noise impact on the environment. In this work, we developed a cloud-based noise simulator to efficiently assess the environmental impact of UAM and UAV. The noise sources and long-distance propagation are computed by the propeller noise prediction models and an advanced Gaussian beam tracing method, respectively, in local high-performance computers. Users can define the working conditions and vehicle layer through a platform with a user-friendly graphical interface. In addition, the noise level distribution at the observers of interest such as the buildings can be visualized. By employing advanced interpolation methods or autonomous learning algorithms, the computations are efficiently accelerated such that the noise distributions are simultaneously displayed during flights of the vehicles. To better measure the noise impact on human perception, various noise metrics will be output for further analysis. By conducting the virtual flights using the simulator, the noise impact in each flight state and atmospheric condition of different vehicles can be predicted, which will then facilitate the low-noise flights for both UAV and UAM.

This survey paper presents a holistic perspective on the state-of-the-art in the design of guidance, navigation, and control systems for autonomous multi-rotor small unmanned aerial systems (sUAS). By citing more than 300 publications, this work recalls fundamental results that enabled the design of these systems, describes some of the latest advances, and compares the performance of several techniques. This paper also lists some techniques that, although already employed by different classes of mobile robots, have not been employed yet on sUAS, but may lead to satisfactory results. Furthermore, this publication highlights some limitations in the theoretical and technological solutions underlying existing guidance, navigation, and control systems for sUAS and places special emphasis on some of the most relevant gaps that hinder the integration of these three systems. In light of the surveyed results, this paper provides recommendations for macro-research areas that would improve the overall quality of autopilots for autonomous sUAS and would facilitate the transition of existing results from sUAS to larger autonomous aircraft for payload delivery and commercial transportation.

In this paper, a method for controlling the swing of loads is proposed by applying forces to a suspended load directly, instead of controlling a suspending machine itself, such as a helicopter and a crane. A special multi-rotor capable of moving in the level surface is developed to control the swing of loads. First, to create a model for controlling the swing of loads, a drone model is used to model a multi-rotor that can generate forces in (x, y)-directions and also produce a torque for yaw-rotation, and has four special coaxial rotors, while a double spherical pendulum is used as a rope model which hangs the multi-rotor. Moreover, in what is called a control allocation problem that determines the number of revolutions of each rotor, assume that the number of revolutions for each rotor consists of one for generating two forces in translational motion, and of one for generating one torque in rotational motion. Then, the number of revolutions for plane movement is first decided at the 1st step, and the number of revolutions for a torque required for yaw motion is next decided from the difference between the torque generated by the translational forces decided at the 1st step and the target torque. Finally, the validity of the proposed load-swing suppression control is verified with simulations.

This letter presents real-time optimization algorithms on trajectory generation and control for a multi-rotor with a suspended load. Since the load is suspended through a cable without any actuator, movement of the load must be controlled via maneuvers of the multi-rotor, which brings about difficulties in operating this system. Additionally, the highly nonlinear dynamics of the system exacerbates the difficulties. While trajectory generation and control are essential for safety, energy efficiency, and stability, the aforementioned characteristics of the system add challenges. With this in mind, the authors propose real-time path planning and optimal control algorithms for collision-free trajectory generation and trajectory tracking. For the dynamics, simplified dynamic models of the system are proposed by considering time delay in attitude control of the multi-rotor. For collision avoidance, the vehicle, cable, and load are considered as ellipsoids with different sizes and shapes, and collision-free constraints are expressed in an efficient and nonconservative way. The augmented Lagrangian method is applied to solve the nonlinear optimization problem with the nonlinear constraints in real-time. For control of the system, model predictive control with a sequential linear quadratic solver is used. Several simulations and experiments are conducted to validate the proposed algorithm.

This chapter presents the proportional integral derivative (PID) control of multi‐rotor unmanned aerial vehicles as case studies. It discusses the dynamics of a quadrotor and a hexacopter for the PID control system design. Because of nonlinearities and physical parameter uncertainties, the attitude control systems for an unmanned aerial vehicle are proposed to be PID control systems in a cascade structure and the PID controller parameters are found using the auto‐tuners. The auto‐tuners are implemented on laboratory test rigs specifically designed for multi‐rotor unmanned aerial vehicles and operated on the ground for the safety of the equipment. The purpose of using an auto‐tuner for the attitude control system is to avoid the time consuming tasks of finding the physical parameters for the secondary and primary plants as well as the actuators. In addition, the dynamics of the closed‐loop secondary system are taken into consideration in the primary control system through the application of the cascade auto‐tuner.

Wind disturbance presents a formidable challenge to the flight performance of multi-rotor small unmanned aerial vehicles (sUAVs). This paper presents a comprehensive review of techniques for measuring wind speed and airspeed for multi-rotor sUAVs. Three categories of sensing techniques are reviewed: flow sensors, anemometers, and tilt-angle based approaches. We also review techniques for generating wind disturbances in simulation. Wind simulation techniques that use power spectral density (PSD) functions, computational fluid dynamics (CFD), and probabilistic models are examined. Finally, we provide an open-source Python implementation of the Dryden wind turbulence model and embedded code to interface with an ultrasonic anemometer.

Multi-rotor wind turbines facilitate higher power production at a lower cost compared to their single-rotor counterparts. However, the larger induced loads due to yaw moments may lead to faster wear and tear on the tower structure and need be appropriately handled by means of pitch control. This paper investigates the feasibility of two different pitch control schemes based on extremum seeking principles for multi-rotor wind turbines in the full-load region. The proposed solutions are tested in simulation. Their performance is compared to that of a benchmark controller with respect to generator speed regulation, power optimisation and fatigue mitigation. The results show that the designed controllers match the performance of the conventional solution at the cost, however, of increased structural stress on the tower.

A multi-rotor wind turbine (MRWT) is accepted as a novel solution in reducing the rotor size without decreasing the energy harvesting capability compared to a single-rotor wind turbine (SRWT). However, there is no systematic methodology available for obtaining the modal properties of MRWTs. This paper presents a novel methodology and systematic modeling method of modal dynamics with comprehensive numerical simulations and analyses of MRWTs. In the methodology, Coleman transformation is employed to convert the nonlinear time-variant dynamics formulation of a MRWT into a set of linear time-invariant dynamic equations. Using HAWC2 and HAWCStab2 a method to establishing high-fidelity linear time-invariant dynamic models is presented. The structural modal dynamics of a tri-rotor wind turbine is systematically investigated by using modal analysis theory and interpreting the rotor speed-dependent dynamics visualized in a Campbell diagram. The investigation shows that rotor modes on a MRWT have similar behavior as for a SRWT and that low torsional stiffness of the rotor attachment point affects the first flapwise backward whirling modes by decreasing the corresponding natural frequencies. Moreover, the low torsional stiffness results in a delayed splitting of the asymmetric flapwise rotor modes. The simulations and analyses result verified the proposed dynamic modeling method. The major contributions in this paper provide the essential insights and guidance in the design of MRWTs but also for SRWT with slender towers.

In this paper, we present a new solution for the Autonomous navigation problem, using a Decomposition-Coordination Method (DCM) 1. The main purpose of this work is to compute an optimal and safe path for the multi-rotor Unmanned Aerial Vehicle (UAV) in a dynamic environment, moving from an initial location to the desired state. We assume that the flight environment is totally known to a supervisory unit, and the positions and trajectories of dynamic obstacles could be known in real-time, thus to perform in such environment a high reactivity is required as well as good connectivity with the supervisory unit that provides the safe path, each time one obstacle or more are detected on the road, so that the UAV could autonomously diverts from the unsafe path to the new safe one, and avoid the potential collisions. First and foremost, we choose a generalized nonlinear model for the multi-rotors in view of the rotational and translational dynamics of the UAV. We then associate that model with the objective functions. After that, we proceed to the resolution of the multi-objective optimization problem using our approach of decomposition-coordination. The principle of this method consists in decomposing the system into several smaller subsystems to simplify the treatment. Then we achieve the coordination afterward using Lagrange multipliers. To prove the convergence and stability of our method we make use of a Lyapunov function chosen particularly for this system. In the last section we present the simulation results, to confirm the reliability of our method.

Multi-rotor wind turbines (MRWTs) have been suggested in the literature as a solution to achieving wind turbine systems with capacities greater than 10 MW. MRWTs utilize a large number of small rotors connected to one support structure instead of one large rotor with the aim of circumventing the square cube law. Potential benefits of MRWTs include cost and material savings, standardization of parts, increased control possibilities, and improved logistics for assembly and maintenance. Almost all previous work has focused on mechanical and aerodynamic feasibility, with almost no attention being paid to the electrical systems. In this research eight different topologies of the electrical collection network for MRWTs are analysed to assess which are the most economically and practically viable options. AC and DC collection networks are presented in radial, star, cluster and DC series topologies. Mass, capital cost and losses are estimated based on scaling relationships from the academic literature and up-to-date commercial data. The focus of this study is the assessment of the type of electrical collector topology, so component type and voltage level are kept consistent between topology designs in order to facilitate a fair comparison. Topologies are compared in terms of four main criteria: capital cost, cost effectiveness, total mass and reliability. A comparison table is presented to summarize the findings of the research in a convenient way. It is found that the most cost-effective solutions are the AC radial and AC star topologies, with the least cost-effective being the DC series–parallel and DC cluster topologies. This is due to the high cost of DC–DC converters and DC switchgear along with the lower efficiency of DC converters. Radial designs perform best in terms of efficiency and annual energy capture. DC systems achieve a slightly lower nacelle mass compared to their equivalent AC systems. DC topologies are generally found to be more expensive when compared to their AC counterparts due to the high cost of DC–DC converters and DC switchgear. Star topologies are considered to have the best reliability due to having no shared equipment. The most suitable collection topology for MRWTs is shown to be of the star type, in which each turbine is connected to the step-up transformer via its own cable.

In this study different multi-rotor wind turbine systems (MRSs) are designed in such a way that the space frame, forming the connection between rotor nacelle assemblies (RNAs) and the tower, is modeled as an ideal truss work. To dimension the tube diameters and wall thicknesses, a simplified load case is used with an adjusted safety factor for loads. This simplified approach allows for fast computations of a large variety of different support structure designs. By variation of rotor number, space frame topology, space frame depth and positioning of yaw bearings, it is possible to gain an understanding of the optimal MRS design. As such, the simplified approach is a preliminary step helping to choose a good design parameter combination for a more detailed and comprehensive analysis.

Small multi-rotor unmanned aerial vehicles (UAVs) are poised to revolutionize commercial and logistics sectors through their versatility, maneuverability, and rapidly increasing sophistication and decreasing costs. However, these robotic systems also produce a substantial and overpowering level of acoustic noise that can potentially distract or harm humans who are working in close proximity to these UAVs. The aim of this study is to investigate the acoustic signature of quadcopter UAVs under various operating conditions, and its impact on human communication and psychological well-being. A unique design of experiments is developed allowing efficient usage of space and reducing the number of sessions required to complete the experiment. The human study has been conducted with popular UAV platforms in a workshop environment. Participants completed various listening tasks and their scores were compared with the noise signature of the UAV to identify operating factors with significant impact on human hearing and perceived annoyance.

The estimate of External Orientation (E.O.) parameters for a block of images is a crucial step in the photogrammetric pipeline and the most demanding in terms of required time and human effort, both during the fieldwork and post-processing phases. Different researchers developed strategies to minimize the impact of this phase. Despite the achievement of good results, it was not possible until now to completely cancel the effect of this step. However, the efforts of the researchers in these years have also been devoted to the implementation of direct photogrammetry strategies, in order to almost completely automate the E.O. of the photogrammetric block. These new approaches were made possible also thanks to the latest developments of commercial UAVs, especially in terms of the installed GPS/GNSS (Global Positioning System/Global Navigation Satellite System) hardware. The aim of this manuscript is to evaluate the different perspectives and issues connected with the deployment of a UAV (Unmanned Aerial Vehicle) equipped with a multi-frequency GPS/GNSS receiver. Starting from the considerations mentioned above and leveraging previous works based on a fixed-wing platform, the focus of this contribution is the assessment of the real performances of an RTK multi-rotor platform addressing several questions. Is it possible to generate added-value products with centimetre 3D accuracies without measuring any ground control point? Which are the operational requirements to be taken into account in the planning phase? Are consolidated UAV mapping operational workflows already available to enable a robust direct georeferencing approach?

Wind field and sound field characteristics are the key indexes for unmanned aerial vehicle. Therefore, in this study, the wind field and sound field characteristics of a quad-rotor unmanned aerial vehicle are investigated. First, the experimental platform was set up based on quad-rotor unmanned aerial vehicle. Second, the experiments were performed on the wind field and the sound field characteristics of the unmanned aerial vehicle at different working currents. Then, the experiment results were analysed. Meanwhile, the experimental results showed that the working current has a large impact on the wind field and the wind intensity increases as working current increases; as the working current increases, the sound field is enhanced and a linear relationship exists; within a certain distance range of the unmanned aerial vehicle, as distance increases, sound intensity dramatically decreases. The presented methods and results can not only be used to evaluate the performance of the electric multi-rotor unmanned aerial vehicle but also provide references for the further improvement of the performance of the unmanned aerial vehicle.

Acoustic sensing from a multi-rotor drone is heavily degraded by the strong ego-noise produced by the rotating motors and propellers. To address this problem, we propose a blind source separation (BSS) framework that extracts a target sound from noisy multi-channel signals captured by a microphone array mounted on a drone. The proposed method addresses the challenging problem of permutation alignment, in extremely low signal-to-noise-ratio scenarios (e.g. SNR $ −15 dB), by performing clustering on the time activities of the separated signals across frequencies. Since initialization plays an important role to the success of clustering, we propose a pre-processing algorithm which uses time-frequency spatial filtering (TFS) to generate a reference to pre-align the permutation. The pre-alignment not only improves the performance of clustering and permutation alignment, but also solves the target-channel selection problem for BSS. The proposed method integrates the advantages of both TFS and BSS. Experimental results with real-recorded data show that the proposed method is capable of processing the audio stream continuously in a blockwise manner and also remarkably outperforms the state-of-the-art.

This paper introduces an adaptable, human-computer interaction method to control multi-rotor aerial vehicles in unsupervised, multi-subject environments. A region-based convolutional neural network (R-CNN) first detects subjects in a frame and their faces’ regions of interest (RoIs), which are then fed to a facial recognition module to search for the main subject within the frame. The R-CNN model supplies the right-hand RoI of the main subject to a convolutional neural network (CNN) that classifies the right-hand gesture. A motion processing unit (MPU) and four flex sensors are embedded in the left hand’s smart glove to produce discrete and continuous signals. Those signals are generated based on the bending of left-hand fingers and the left hand’s roll angle and then fed to a support vector machine (SVM) to classify the left-hand gesture. Three validation layers have been implemented, including a human-based validation, classification validation, and the system validation. The comprehensive experimental results have validated the proposed method.

This paper proposes a cascade control strategy for multi-rotor unmanned aerial vehicle, where the inner-loop system is regulated by a sliding mode controller with disturbance observer and the outer-loop controller is a PID controller. Operational constraints are incorporated in the implementation for safety protection of the electronics. Experimental results are obtained to demonstrate the efficacy of the proposed design in comparison to a traditional cascade PID control system.

In recent years, many radioactive sources have been lost or stolen during use or transportation. When the radioactive source is lost or stolen, it is challenging but imperative to quickly locate the source before it causes damage. Nowadays, source search based on fixed-wing unmanned aerial vehicles (UAVs) can significantly improve search efficiency, but this approach has higher requirements for the activity of the uncontrolled radioactive source and the take-off sites. The aim of this study was to design and demonstrate a platform that uses low-cost multi-rotor UAVs to automatically and efficiently search for uncontrolled radioactive sources even with lower activity. The hardware of this platform consists of a multi-rotor UAV, radiation detection sensor, main control module, gimbal and camera, and ground control station. In the search process, the ground control station and UAV communicate wirelessly in real time. To accommodate different search scenarios, the study proposed three search algorithms with a theoretical comparison. Then, field experiments based on the traversal search algorithm showed that the search system based on multi-rotor UAVs could effectively and accurately conduct contour mapping of a region and locate the radioactive source with an error of 0.32 m. The platform and algorithms enable accurate and efficient searching of radioactive sources, providing an innovative demonstration of future environmental risk assessment and management.

We address a cooperative transport control problem involving three or more unmanned aerial vehicles (UAVs). We realize the transportation of an object that cannot be carried with a small number of UAVs. To improve scalability and real-time performance, we propose a controller that does not require optimization calculations. The attitude and position of the transported object are controlled by contact forces with the UAVs. The control system comprises two steps in which (1) a force is allocated to each UAV and (2) UAVs realize the force allocation using a decentralized disturbance observer-based controller. A friction cone constraint related to static friction is considered using the redundant degree of freedom in the force allocation. The effectiveness of the controller is verified in numerical simulations.

Suspending and transporting a load is met in many situations. However, it has been regarded as a problem because it leads to a decrease in work efficiency and an accident if the load is oscillated or rotated during transportation due to disturbances caused by winds or operational errors. As a countermeasure to this problem, a method for controlling sway and rotation with a suspending machine has been studied. However, such a method can only control swaying and not rotation, and are not applicable to all transport machines or aircrafts. Therefore, in this research, it is aimed at controlling the tip of the wire directly by using a horizontally movable multi-rotor, which is applicable to all types of suspending machines or aircrafts and can control the rotation as well as the swing. Then, a rotational control experiment and a sway control experiment are conducted using the developed horizontally movable multi-rotor to verify its usefulness for the sway and rotational motions.

International audience; The aim of this work is to present the necessary conditions for the design of an omnidirectional Multi-Rotor Aerial Vehicle (MRAV), while taking into consideration its geometry, weight, and actuation limits. The work formally defines these conditions and presents numerical metrics that reflect the satisfaction of the omnidirectional property. These metrics are then applied to assess the omnidirectional property of "Omni-plus-seven", i.e., an omnidirectional MRAV consisting of a hepta-rotor with uni-directional thrusters [1]. Finally the work shows the use of such metrics in the design of a new platform with similar geometry and modified weight and actuators.

In this work, a swarm behaviour for multi-rotor Unmanned Aerial Vehicles (UAVs) deployment will be presented. The main contribution of this behaviour is the use of a virtual device for quantitative sematectonic stigmergy providing more adaptable behaviours in complex environments. It is a fault tolerant highly robust behaviour that does not require prior information of the area to be covered, or to assume the existence of any kind of information signals (GPS, mobile communication networks …), taking into account the specific features of UAVs. This behaviour will be oriented towards emergency tasks. Their main goal will be to cover an area of the environment for later creating an ad-hoc communication network, that can be used to establish communications inside this zone. Although there are several papers on robotic deployment it is more difficult to find applications with UAV systems, mainly because of the existence of various problems that must be overcome including limitations in available sensory and on-board processing capabilities and low flight endurance. In addition, those behaviours designed for UAVs often have significant limitations on their ability to be used in real tasks, because they assume specific features, not easily applicable in a general way. Firstly, in this article the characteristics of the simulation environment will be presented. Secondly, a microscopic model for deployment and creation of ad-hoc networks, that implicitly includes stigmergy features, will be shown. Then, the overall swarm behaviour will be modeled, providing a macroscopic model of this behaviour. This model can accurately predict the number of agents needed to cover an area as well as the time required for the deployment process. An experimental analysis through simulation will be carried out in order to verify our models. In this analysis the influence of both the complexity of the environment and the stigmergy system will be discussed, given the data obtained in the simulation. In addition, the macroscopic and microscopic models will be compared verifying the number of predicted individuals for each state regarding the simulation. This work was supported by Ministerio de Economía y Competitividad (Spain) http://www.mineco.gob.es/portal/site/mineco/, project TIN2013-40982-R. Project co-financed with FEDER funds.

Purpose The purpose of this paper is to facilitate autonomous landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving/tilting platform using a robust vision-based approach. Design/methodology/approach Autonomous landing of a multi-rotor UAV on a moving or tilting platform of unknown orientation in a GPS-denied and vision-compromised environment presents a challenge to common autopilot systems. The paper proposes a robust visual data processing system based on targets’ Oriented FAST and Rotated BRIEF features to estimate the UAV’s three-dimensional pose in real time. Findings The system is able to visually locate and identify the unique landing platform based on a cooperative marker with an error rate of 1° or less for all roll, pitch and yaw angles. Practical implications The proposed vision-based system aims at on-board use and increased reliability without a significant change to the computational load of the UAV. Originality/value The simplicity of the training procedure gives the process the flexibility needed to use a marker of any unknown/irregular shape or dimension. The process can be easily tweaked to respond to different cooperative markers. The on-board computationally inexpensive process can be added to off-the-shelf autopilots.

With the rapid development of the economy, the scale of transmission networks has been expanding, bring higher demands and challenges on transmission line operation and maintenance. In this paper, the multi-rotor unmanned aerial vehicles (UAVs) safety inspection rules and automatic detailed inspection methods for transmission towers are studied. The theoretical model of multi-rotor UAVs of transmission lines inspection is established. The imaging calculation range of multi-rotor UAV-equipped cameras is determined. According to the inspection theory model, the flight safety judgment standard is designed, and the key parts of the transmission lines that need to be inspected are determined according to the accurate model of the transmission tower. Then the inspection waypoints are manually operated, and the photographing position and angle of each waypoint from the flight control are recorded through the waypoint planning function. Finally, the waypoints are connected in order, and the inspection route is automatically generated to achieve automatic detailed inspection. The inspection efficiency, error analysis and position accuracy comparing the proposed method with some state-of-the-art methods have been evaluated. The results show that the position error of UAVs automatic detailed inspection is less than 10 cm. The error of height is between 1.26 and 1.76 meter. Compared with the traditional manual inspection, the efficiency of multi-rotor UAVs automatic detailed inspection can be increased by 57.98%~62.88% and can be applied to large-scale inspection of transmission lines.

In this study, we aim at realizing the adaptive control system that enables the multi-rotor helicopter to fly autonomously without the tuning by human operator. This paper presents the design of the inner loop feedback control of multi-rotor helicopter based on adaptive PID control. The controller is designed by using the theory of simple adaptive control (SAC) method. Numerical simulation and flight experiment are carried out to verify the efficiency of proposed feedback control.

Motion control theory applied to multi-rotor aerial vehicles (MAVs) has gained attention with the recent increase in the processing power of computers, which are now able to perform the calculations needed for this technique, and with lower cost of sensors and actuators. Control algorithms of this kind are applied to the position and the attitude of MAVs. In this paper, we present a review of recent developments in position control and attitude control of multi-rotor aerial robots systems. We also point out the growth of related research, starting with the boom in multi-rotor unmanned aerial robotics that began after 2010, and we discuss reported field applications and future challenges of the control problem described here. The objective of this survey is to provide a unified and accessible presentation, placing the classical model of a multi-rotor aerial vehicle and the proposed control approaches into a proper context, and to form a starting point for researchers who are initiating their endeavors in linear/nonlinear position, altitude or attitude control applied to MAVs. Finally, the contribution of this work is an attempt to present a comprehensive review of recent breakthroughs in the field, providing links to the most interesting and most successful works from the state-of-the-art.

This paper presents a new formulation of controlling cooperative drones using relative Jacobian. This formulation affords relative movement of the end-effector drone with respect to the base drone, while the base drone moves with respect to the world frame. The relative movement releases unnecessary constraints in the movement of the drone with respect to each other, such that the relative movement between the drones now has increased degrees-of-freedom compared to absolute movement control. The implementation is shown in the Gazebo RotorS simulation platform using two firefly drones each with six propellers. The individual control of each firefly drone is using a new formulation that is also presented in this work using a Jacobian-based controller. This type of controller is versatile because it can lead towards Jacobian-based controllers of manipulators to be applied to controlling multi-rotor drones. This makes it possible to control more than one multi-rotor drone using a single controller. Frames of reference are assigned at the centre of gravity for each multi-rotor drone, and the derivation of individual drones Jacobian and the relative Jacobian are based on these reference frames. Simulation results are shown to demonstrate the effectiveness of this approach.

Gas-insulated switchgear (GIS), as an important high-voltage equipment in a substation, is extremely important to the normal operation of the substation. There are many SF 6 pointer meters in the GIS room to monitor the insulating medium, SF 6 gas, in the closed metal pipeline. However, since many meters are located at a height of 4-5 meters, it is not conducive to manual or robot inspection. Therefore, in order to solve the problem of inspection of SF 6 meters at high places, the article proposes to use a multi-rotor Unmanned Aerial Vehicle(UAV) with strong maneuverability and high flexibility for inspection. The inspection system designed in this paper is based on the secondary development of the DJI Mavic2 UAV platform, and uses Apriltag to achieve accurate indoor positioning of the UAV. At the same time, it combines the meter recognition algorithm based on key point detection to automatically read the meters. Finally, the autonomous inspection of SF 6 meters in the GIS room based on the multi-rotor UAV is realized. Through testing in the substation, the practicability of the inspection system is verified.

The transportation of long rod-like payload using multiple Multi-Rotor Aerial Vehicles (MRAVs) is analyzed to determine the ideal locations of the anchor points on the payload in order to improve the endurance of the system. The payload is modelled as a beam, with supports as the anchor points of the cable links between the payload and the MRAVs. The criterion for determining the ideal anchor point locations are laid. The proposed method is validated for different types of mass distributions and can be extended to any variation in payload mass distribution transported using multiple MRAVs. The proposed methodology is validated using Hector quadrotor in Gazebo environment.

This paper focuses on the energy costs of using a control system to follow a specific trajectory as opposed to directly choosing the inputs in an open-loop sense to achieve a specific trajectory. Results show that the PID controller will use 7–13% more energy than the open-loop system for the small-amplitude trajectories and 62–74% more energy for the high-amplitude trajectories while maintaining trajectory errors of approximately 5% and 19%, respectively. The PD controller will use 0.03–0.04% less energy than the open loop system for the small-amplitude trajectories and 0.35% less energy for the high-amplitude trajectories while maintaining similar trajectory errors to the PID controller. The two trajectories have different trajectory errors (5% vs. 19%). Therefore, the controller does not have to move the rotor speeds to the same level, thus causing more energy saved for the large-amplitude trajectory. Based on these simulations, it can be concluded that the PD controller will be significantly more energy efficient than the PID controller while maintaining similar trajectory errors throughout the entire flight. This is because the integral control term in the PID controller accumulates the error so any initial large errors in the position will result in large controller inputs later in the flight. The accumulation of error in the integral term then results in large variations in rotor speed which often leads to a higher energy usage. Thus, a PD controller may be a more energy efficient choice while maintaining effectiveness in trajectory-tracking. These results highlight the importance of considering and comparing the energy costs of various control systems when designing controllers for multi-rotor drones.

It is one of the significant tasks of power inspection by multi rotor Unmanned Aerial Vehicle (UAV) to recognize engineering vehicles in aerial images. If there are engineering vehicles working near or below the high-voltage power line, the UAV would give out the important early warning message to avoid the situation that the bucket or boom of the engineering vehicle enters the safe distance from the high-voltage power line, and reduce accidents such as short circuit breakdown. Aiming at the problem of recognition of engineering vehicles in aerial images of UAV inspection, this paper proposed an improved capsule network method. First, the structure of original capsule network is replaced with a multi-layer densely connected capsule network. Next, the dynamic routing algorithm of the capsule network is improved. As the results of experiments have shown, (1) the improved capsule network method gets a mAP of 93.74% for the recognition of engineering vehicles, and its parameter scale is smaller than other methods. (2) The number of network layers influences the recognition precision greatly. Their relationship is non-monotonic and nonlinear. In addition, whether or not to improve the dynamic routing algorithm does not affect the trends of recognition mAP. The overall performance of the improved capsule network method is obviously better than YOLOv5 and other artificial feature extraction methods.

A digital twin platform framework for multi-rotor UAV is proposed in this paper. The platform is composed of simulation system, physical UAV and service center, which is designed to solve the problem about UAV advanced capability training and algorithm verification. As we know, a good UAV system verification method is to make full use of virtual simulation before repeated physical tests. However, there is a gap between the virtual simulation and physical test results, because the simulation model is difficult to completely describe the actual physical object. So the hidden risks may exist in actual physical tests by only using the results of virtual simulations. Based on the feedback control idea, the actual state data of the physical UAV is fed back to virtual simulation platform, and the virtual simulation platform completes virtual and real joint training and verification based on this. That is, the technology of digital twin is introduced into the UAV system development process in this paper. In addition, the digital twin platform structure of two-way interaction between virtual space, physical space and service center is proposed. The 4G/5G communication interface is developed to improve the platform’s real-time interaction capabilities. Besides, the components of the platform and the construction process are introduced in detail. Finally, three platform test experiments are used to verify the interactive characteristics of the platform and introduce the operating process of the platform.

In this paper, we present control and parameter estimation strategies with theoretical guarantees to turn a hex-rotor unmanned aerial vehicle (UAV) into a microgravity enabling platform. We make the UAV to maintain a constant acceleration equal to free-fall acceleration for it and any payload on-board to experience microgravity. Towards this, we derive a feedback linearisation-based acceleration control law exploiting the differential flatness property of our system. The proposed control law requires the estimates of the system parameters. Therefore, ancillary to this control law, we propose a parameter estimation scheme and prove that the proposed control law along with the parameter estimation scheme ensures convergence of acceleration to the desired value under certain conditions. We also characterize these conditions that guarantee convergence. The flight tests that we have performed employing the proposed control and parameter estimation schemes gave microgravity levels of the order of $$10^{-3}g$$ for 1.6 s. To our knowledge, our hex-rotor UAV is the first multi-rotor UAV to achieve microgravity, and the first UAV—fixed-wing or rotary—to attain and maintain such levels of microgravity.

Accurate dynamic modeling lays foundation for design and control of UAV. The dynamic model for the multi-rotor fixed-wing UAV was looked into and it was divided into fuselage, air-body, multi-rotors, vertical fin, vertical tail and control surfaces, based on the multibody dynamics. The force and moment model for each body was established and derived into the Lagrange equation of the second king by virtual work. By electing quaternion as generalized coordinate and introducing Lagrangian multiplier, the dynamic modeling was deduced and established. Finally, the comparison between the simulation results and the experimental can be found that the present dynamic model accurately describes the process of dynamic change of this UAV and lay foundation for the control of UAV.

The propulsion system of a multi-rotor UAV plays a fundamental role in the aircraft flight characteristics. In fact, it generally represents the major contributor to the aerodynamic forces acting on the vehicle. While several approaches for modeling rotor thrust and drag forces exist, the problem of identifying the parameters for these models is still challenging. In this paper we propose a systematic method for identifying a limited number of parameters which guarantee accurate thrust and drag prediction according to Blade Element Theory (BET). Simple experimental tests employing a popular rotor system and a custom-made quadrotor are used both in the identification phase and for the final validation. The discussion of the results illustrates the accuracy of the method, while highlighting the modeling limit of BET. A refinement using Blade Element Momentum Theory is proposed and validated with the support of experimental data.

Multi-rotor drones have witnessed a drastic usage increase in several smart city applications due to their 3D mobility, flexibility, and low cost. Collectively, they can be used to accomplish different short- and long-term missions that require low-altitude motion in urban areas. Therefore, it is important to efficiently manage the operation of the fleet to leverage its use and maximize its application performances. In this paper, we propose to investigate the path routing problem for the multiple drones in urban areas, where obstacles with different heights exist. The objective is to find the best trajectories in this 3D environment while ensuring collision-free navigation. The collision is prevented by three possible alternatives: forcing the drone to statically hover, so its peer can pass first, making it fly at a different altitude, or completely changing its path. Multiple charging stations are made available to allow the drones to recharge their batteries when needed. A mixed integer linear program is first developed to model the problem and achieve optimal navigation of the fleet. Afterward, two heuristic algorithms with different conceptual constructions are designed to solve the trajectory planning problem with faster convergence speed. The selected simulation results illustrate the performance of our framework in realistic 3D maps and show that the designed heuristic approaches provide close performances to the optimal ones.

Unmanned aerial vehicles (UAVs) at low altitude flight may significantly degrade their performance and the safety under wind disturbances and incorrect operations. This paper presents a robust control strategy for UAVs to achieve good performance of low altitude flight and disturbance rejection. First, a novel second-order hexacopter dynamics is established and the position tracking is translated to the altitude and the rotational angle tracking problem. An integrated control scheme is created to deal with the challenges faced by hexacopter at low altitude flight, in which the influence of near-ground threshold distance and the desired roll, pitch, and yaw are analyzed. Moreover, an improved flying altitude planner and an attitude planner for low altitude conditions are designed respectively to avoid the overturning risk due to the big reaction torque and external disturbances. Second, a sliding-mode-based altitude tracking controller and an attitude tracking controller are designed to reduce the tracking errors and improve the robustness of the system. Finally, the proposed control scheme is tested on simulation and experiment platforms of multi-rotor UAV to show the feasibility and accurate trajectory tracking at low altitude flight.