Model Of Unmanned Aerial Vehicle Research Articles

Accuracy Analysis of Three-Dimensional Modeling of a Multi-Level UAV without Control Points

Unmanned Aerial Vehicle (UAV) oblique photography technology has been applied more and more widely for the 3D reconstruction of real-scene models due to its high efficiency and low cost. However, there are many kinds of UAVs with different positioning methods, camera models, and resolutions. To evaluate the performance levels of different types of UAVs in terms of their application to 3D reconstruction, this study took a primary school as the research area and obtained image information through oblique photography of four UAVs of different levels at different flight altitudes. We then conducted a comparative analysis of the accuracy of their 3D reconstruction models. The results show that the 3D reconstruction model of M300RTK has the highest dimensional accuracy, with an error of about 1.1–1.4 m per kilometer, followed by M600Pro (1.5–3.6 m), Inspire2 (1.8–4.2 m), and Phantom4Pro (2.4–5.6 m), but the accuracy of the 3D reconstruction model was found to have no relationship with the flight altitude. At the same time, the resolution of the 3D reconstruction model improved as the flight altitude decreased and the image resolution of the PTZ camera increased. The 3D reconstruction model resolution of the M300RTK + P1 camera was the highest. For every 10 m decrease in flight altitude, the clarity of the 3D reconstruction model improved by 16.81%. The UAV flight time decreased as the UAV flying altitude increased, and the time required for 3D reconstruction of the model increased obviously as the number and resolution of photos increased.

Disguised Tailing and Video Surveillance With Solar-Powered Fixed-Wing Unmanned Aerial Vehicle

Disguised tailing and visual monitoring of suspicious mobile targets is a promising application of security unmanned aerial vehicles (UAVs). But trajectory planning is non-trivial, especially for fixed-wing UAVs with more constrained maneuverability and dynamic models. This paper proposes a new framework to optimize collectively the propulsion power and the three-dimensional (3D) trajectory of a solar-powered, fixed-wing UAV on a disguised tailing and video surveillance mission. The multi-objective optimization strikes a balance between distance keeping, elevation variance, and power efficiency. A key aspect is that we develop a new propulsion power model of the fixed-wing UAV by analyzing the forces undergone while the UAV is ascending or descending. Another important aspect is a series of non-trivial reformulations, which convexify the multi-objective problem progressively with increasingly tightening linear approximation and solve the problem with a polynomial time-complexity. Our algorithm can control the trajectory of the UAV on-the-fly. Simulations confirm that the algorithm outperforms existing schemes in terms of visual disguise and power efficiency. The fixed-wing UAV also demonstrates its advantage of energy efficiency and sustainability to elongate the surveillance mission, over its rotary-wing counterpart.

The Application of Improved Harmony Search Algorithm to Multi-UAV Task Assignment

In this work, aiming at the problem of cooperative task assignment for multiple unmanned aerial vehicles (UAVs) in actual combat, battlefield tasks are divided into reconnaissance tasks, strike tasks and evaluation tasks, and a cooperative task-assignment model for multiple UAVs is built. Meanwhile, heterogeneous UAV-load constraints and mission-cost constraints are introduced, the UAVs and their constraints are analyzed and the mathematical model is established. The exploration performance and convergence performance of the harmony search algorithm are analyzed theoretically, and the more general formulas of exploration performance and convergence performance are proved. Based on theoretical analysis, an algorithm called opposition-based learning parameter-adjusting harmony search is proposed. Using the algorithm to test the functions of different properties, the value range of key control parameters of the algorithm is given. Finally, four algorithms are used to simulate and solve the assignment problem, which verifies the effectiveness of the task-assignment model and the excellence of the designed algorithm. Simulation results show that while ensuring proper assignment, the proposed algorithm is very effective for the multi-objective optimization of heterogeneous UAV-cooperation mission planning with multiple constraints.

The Dataset of UAV Based High-resolution Tidal Topography at the Nakdong Estuary: Focusing on Jin-u Island and Shin-ja Island

In the tidal flats of the Nakdong Estuary, eight weirs were installed as part of the Four Major River Restoration Project in 2011, and the environment changed from a flowing stream to a still water stream. As the Nakdong River’s weir was permanently opened in February 2022, the topography and ecological environment are expected to large change. In this study, Unmanned Aerial Vehicle (UAV) photogrammetry was conducted on the tidal flats of the Nakdong Estuary in November 2021, the environment before the Nakdong River floodgates were opened. The study area was surveyed using the Network-RTK (Real-Time Kinematic) method to obtain Ground Control Point (GCP), and using an UAV, orthographic image and digital elevation model were generated for an area of 3.47 ㎢ near Jin-u island and 2.75 ㎢ near Shin-ja island. A result of spatial resolution of 1.8 cm was obtained, the result was verified using checkpoints, and results with accuracy exceeding 1 cm were obtained in both Sin-u Island and Jin-woo Island. In the future, changes in the topography and sedimentation environment of this area are expected, so it will be useful data for various research and conservation management.

Risk Management Model for Unmanned Aerial Vehicles during Flight Operations.

Risk management and uncertainty models are practised in all branches of transport. Although unmanned aerial vehicles (UAVs) constitute a branch of the industry rather than transport as a whole, their development is oriented toward increasingly more serious applications involving the transport of goods and people. The constantly growing number of operations employing UAVs requires not only identification of hazard sources or risk assessment recommended by the applicable regulations, but also comprehensive risk management. In order to develop a systematic approach to risk management for air operations of UAVs, the classic risk management method can be used. This work proposes a novel multi-criteria risk model that may serve as the basis for further activities aimed at developing a risk management method for this domain. The model was based on six criteria and validated using a virtual route to risk assessment and valuation.

Finite Horizon Nonlinear Suboptimal Control for an Autonomous Soaring UAV

In this paper, a suboptimal nonlinear discrete control for nonlinear discrete affine systems is implemented in an autonomous soaring unmanned aerial vehicle (UAV) to improve energy consumption and performance. General expressions for this controller are obtained from the continuous nonlinear guidance model of a fixed-wing UAV and applied in a multiloop control structure. Simulation results in the task of trajectory tracking inside a thermal updraft and a comparative study with a proportional derivative (PD) controller validated the effectiveness of this method.

Implementation analysis of reliable unmanned aerial vehicles models for security against cyber-crimes: Attacks, tracebacks, forensics and solutions

This paper focuses on the major challenges that organizations and sectors face, such as cyber-attacks and crimes. With the advancement of technology for applications and services in businesses, homes, healthcare, and other areas, there has been an increase in cyber-crime. The quality and security of information have been compromised as a result of the attacks, and space optimization of these applications and services has become more challenging as a result of the migration to Unmanned Aerial Vehicles (UAVs). The UAVs are gaining popularity to provide civilian and military applications, but due to the current Internet environment, it is more vulnerable to malicious attacks. Forensics is the practice of gathering evidence to identify attacks. Cyber forensics collects evidence from cyber-attacks. Digital footprints are particularly significant in cyber forensics. UAVs contain real-time data, and users access it directly, exposing the solution to cyber-attacks. This study focuses on the function of UAVs in various applications and the issues faced in terms of cyber security and privacy. The current research also examines several security models for controlling quality and reliability in UAV applications, with the results discussed. The current research describes future challenges and research prospects in UAVs.

Coverage path planning of heterogeneous unmanned aerial vehicles based on ant colony system

Unmanned aerial vehicle (UAV) has been extensively studied and widely adopted in practical systems owing to its effectiveness and flexibility. Although heterogeneous UAVs have an enormous advantage in improving performance and conserving energy with respect to homogeneous ones, they give rise to a complex path planning problem. Especially in large-scale cooperative search systems with multiple separated regions, coverage path planning which seeks optimal paths for UAVs to completely visit and search all of regions of interest, has a NP-hard computation complexity and is difficult to settle. In this work, we focus on the coverage path planning problem of heterogeneous UAVs, and present an ant colony system (ACS)-based algorithm to obtain good enough paths for UAVs and fully cover all regions efficiently. First, models of UAVs and regions are built, and a linear programming-based formulation is presented to exactly provide the best point-to-point flight path for each UAV. Then, inspired by the foraging behaviour of ants that they can obtain the shortest path between their nest and food, an ACS-based heuristic is presented to seek approximately optimal solutions and minimize the time consumption of tasks in the cooperative search system. Experiments on randomly generated regions have been organized to evaluate the performance of the new heuristic in terms of execution time, task completion time and deviation ratio.

Unified Accurate Attitude Control for Dual-Tiltrotor UAV with Cyclic Pitch Using Actuator Dynamics Compensated LADRC.

This paper proposes a unified attitude controller based on the modified linear active disturbance rejection control (LADRC) for a dual-tiltrotor unmanned aerial vehicle (UAV) with cyclic pitch to achieve accurate attitude control despite its nonlinear and time-varying characteristics during flight mode transitions. The proposed control algorithm has higher robustness against model mismatch compared with the model-based control algorithms. The modified LADRC utilizes the state feedbacks from the onboard sensors like IMU and Pitot tube instead of the mathematical model of the plane. It has less dependency on the accurate dynamics model of the dual-tiltrotor UAV, which can hardly be built. In contrast to the original LADRC, an actuator model is integrated into the modified LADRC to compensate for the non-negligible slow rotor flapping dynamics and servo dynamics. This modification eliminates the oscillation of the original LADRC when applied on the plant with slow-response actuators, such as propeller and rotors of the helicopter. In this way, the stability and performance of the controller are improved. The controller replaces the gain-scheduling or the control logic switching by a unified controller structure, which simplifies the design approach of the controller for different flight modes. The effectiveness of the modified LADRC and the performance of the unified attitude controller are demonstrated in both simulation and flight tests using a dual-tiltrotor UAV. The attitude control error is less than ±4° during the conversion flight. The control rising time in different flight modes is all about 0.5 s, despite the variations in the airspeed and tilt angle. The flight results show that the controller guarantees high control accuracy and uniform control quality in different flight modes.

ПОРІВНЯЛЬНИЙ АНАЛІЗ ТА СТВОРЕННЯ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ ДЛЯ ФОРМУВАННЯ МАКЕТА РОЙОВОЇ ВЗАЄМОДІЇ

The subject of study is the process of creating an unmanned aerial vehicle of the helicopter type, which is able to perform autonomous flight and be used in the premises to test the algorithms of swarm interaction. The aim is to reduce the cost of forming and operating the UAV swarm intelligence model, ensuring compatibility with existing hardware positioning systems and simulation software platforms. Tasks: to analyze the existing prototypes of unmanned aerial vehicles of the helicopter type, used for modeling and testing of autonomous flight modes indoors; to review the systems of positioning and exchange of information between the participants of the swarm formation and to analyze the hardware systems necessary for the implementation of these systems; to develop the architecture of hardware subsystems for unmanned aerial vehicles capable of performing tasks at the level of the considered prototypes; design a case for a sound hardware platform, check its operational parameters, implement its collection and testing; install software that allows you to check the operability of the considered platform of the unmanned aerial vehicle. The methods used are: systems analysis used to compare models of unmanned aerial vehicles within the tasks, methods of analysis and synthesis of schemes for the implementation of the hardware platform, the method of graphic modeling for the design of the unmanned aerial vehicle, methods of system programming for flight program. The following results were obtained. The choice of the hardware platform of the unmanned aerial vehicle is substantiated; the hull for the helicopter was developed and implemented, two platforms of unmanned aerial vehicles were collected and tested during autonomous flight indoors. Conclusions. The study found that there are existing and widely used platforms for compatible indoor flight. These platforms are open and closed. The analysis of open hardware platforms and synthesis of architecture of own unmanned aerial vehicle is made. The designed and implemented unmanned aerial vehicle is capable of autonomous flight, has all the necessary components to perform a compatible flight program. As part of the layout of swarm interaction, it is necessary to further adjust the positioning system.

Robust Hierarchical Formation Control of Unmanned Aerial Vehicles via Neural-Based Observers

Herein, we investigate the robust formation control problem for a group of unmanned aerial vehicles (UAVs) with system uncertainty. A hierarchical formation control strategy is introduced to ensure the uniform ultimate boundedness of each UAV’s reference tracking error. First, a group of saturated high-level virtual agents are defined to act as the trajectory planners that offer feasible position references to the actual UAVs. A sliding mode neural-based observer is then constructed to estimate the nonlinear uncertainty in the UAV model. Furthermore, sliding mode controllers are designed for both the position loop and the attitude loop of the UAV. To attenuate the chattering phenomenon in the control input, a saturated and smoothed differentiator is proposed along with an observation introduction function. The effectiveness of the proposed control scheme is validated by both the Lyapunov stability theory and numerical simulations based on a multiple-UAV system.

Conceptual design and flight test of two wingtip-docked multi-body aircraft

To overcome the drawbacks such as large wing deformations, poor performance encountering gusts, limits in taking off and landing, inconvenience of transportation of High-Altitude Long-Endurance (HALE) Unmanned Aerial Vehicles (UAVs), a new conceptual aircraft called wingtip-docked Multi-Body Aircraft (MBA) has attracted lots of attentions. Aiming to investigate the feasibility of this concept, two UAV models were designed, manufactured and connected by a wingtip-docking mechanism, which only allows the relative roll motion between the two aircraft. The trim solution of the two connected aircraft is firstly obtained by solving the developed nonlinear flight dynamic equations, followed by the stability analysis based on the linearized model. The results show that the connected aircraft is inherently unstable and cannot fly without a reasonable flight control system. A set of Proportional-Integral-Derivative (PID) control laws was then developed and implemented in the two experimental aircraft. The success of the flight tests show that the flight control can effectively eliminate the unstable motion and the wingtip-docked MBA is controllable and feasible.

The dynamic model of a high-rise firefighting drone

The utilization of unmanned aerial vehicles (UAVs) in high-rise firefighting operations is the right solution for reaching the fire scene on high floors quickly and effectively. The article proposes a quadrotor-type firefighting UAV model carrying a launcher to launch a missile containing fire extinguishing powders into a fire. The kinematic model describing the flight kinematics of this UAV model is built based on the Newton – Euler method when the device is in normal motion and at the time of launching a firefighting missile. The results from the simulation testing the validity of the kinematic model and the simulation of the motion of the UAV show that the variation of Euler angles, flight angles, and aerodynamic angles during a flight are within an acceptable range and overload guarantee in flight. The UAV flew to the correct position to launch the required fire-extinguishing ammunition. The results of the research are the basis for building a control system of high-rise firefighting drones in Vietnam.

Use of drones in offshore wind farm inspections

Abstract: With the increase in global investments in offshore wind energy and the rapid implementation of wind technologies in hazardous deep water environments, operational inspection of wind turbines and related infrastructure plays an important role in the safe and efficient operation of offshore wind farms. In recent years, much attention has been paid to the use of unmanned aerial vehicles (UAVs) and remotely piloted unmanned aerial vehicles (RPAs) commonly referred to as "drones" for remote inspection of renewable energy infrastructure, i.e. photovoltaic farms and onshore wind farms. Drones have significant potential also in in offshore wind energy. Inspection with drones allows for to reduce not only the number of flight operations (involvement of aircraft and flight crews) and the transport of personnel carrying out the maintenance and repair of offshore wind turbines. With drones is possible carry the equipment transported for hazardous inspection work. The involvement of UAVs also reduces the plant downtime needed to detect faults and collect diagnostic information from the entire wind farm. The benefits of inspection technology in the offshore wind energy industry based on drones are confirmed by the previous tests, and the prospect of offshore energy development encourages further work with the use of UAVs. At the same time, it should be borne in mind that any unexpected failure of the drone system during its mission may interrupt control works (during inspections), and thus reduce the electricity generated by wind turbines. The article presents the potential of drones in the process of inspecting wind farms, including offshore wind farms, presents examples of UAV models used for inspections, indicates methods of conducting inspections with the use of drones and highlights a significant reduction in the costs of the operation of offshore wind farms as a result of limiting the use of manned aviation (helicopters and flight crews) and the elimination of the risk associated with the involvement of personnel to perform inspections of wind farms at sea. The potential of unmanned floating platforms as part of cooperation with UAV in the process of inspecting offshore wind farms was also indicated. Keywords: wind energy, offshore, drones, wind farms, drone inspections, maritime inspections, marine aviation, offshore, offshore wind energy, safety air operations, risk analysis

Fault‐tolerant attitude tracking control with practical finite time convergence for unmanned aerial vehicles under actuation faults

AbstractThis paper presents an adaptive attitude finite time tracking control algorithm for quadrotor unmanned aerial vehicle (UAV) in presence of actuator faults, input saturation and external disturbance. The dynamic model of the quadrotor UAV is characterized with quaternion representation. Subsequently, using nonsingular terminal sliding mode surface, an adaptive fault‐tolerant finite‐time attitude control scheme is proposed. Using Lyapunov stability analysis, it is shown that the proposed method is able to achieve practical finite time attitude tracking convergence in that the attitude tracking error converges to a small residual set within finite time and all signals of the closed‐loop system remain bounded. The effectiveness of the proposed method is confirmed via numerical simulation.

Safe Motion Planning and Learning for Unmanned Aerial Systems

To control unmanned aerial systems, we rarely have a perfect system model. Safe and aggressive planning is also challenging for nonlinear and under-actuated systems. Expert pilots, however, demonstrate maneuvers that are deemed at the edge of plane envelope. Inspired by biological systems, in this paper, we introduce a framework that leverages methods in the field of control theory and reinforcement learning to generate feasible, possibly aggressive, trajectories. For the control policies, Dynamic Movement Primitives (DMPs) imitate pilot-induced primitives, and DMPs are combined in parallel to generate trajectories to reach original or different goal points. The stability properties of DMPs and their overall systems are analyzed using contraction theory. For reinforcement learning, Policy Improvement with Path Integrals (PI2) was used for the maneuvers. The results in this paper show that PI2 updated policies are a feasible and parallel combination of different updated primitives transfer the learning in the contraction regions. Our proposed methodology can be used to imitate, reshape, and improve feasible, possibly aggressive, maneuvers. In addition, we can exploit trajectories generated by optimization methods, such as Model Predictive Control (MPC), and a library of maneuvers can be instantly generated. For application, 3-DOF (degrees of freedom) Helicopter and 2D-UAV (unmanned aerial vehicle) models are utilized to demonstrate the main results.

Prescribed performance–based tracking control for quadrotor UAV under input delays and input saturations

In this paper, a semi-global trajectory tracking control scheme is proposed for quadrotor unmanned aerial vehicle (UAV) under time-varying input delays, input saturations, and bounded disturbances. Initially, in order to ensure the desirable control performance that tracking error is limited in a prescribed bound, an error transformation function is presented to transform the constrained problem into a stabilization one. Then, under backstepping control scheme, a state prediction method combined with a dynamic surface control (DSC) is presented to compensate for the effects of input delays, and an auxiliary system is designed to tackle the input saturations, which are further to deal with input delays and input saturations in both position system and attitude system of quadrotor UAV. Particularly, the Euler angle is constrained to avoid the singular points of the attitude system. Besides, based on Lyapunov stability theory, it can be verified that all signals in the closed-loop system of the quadrotor UAV are semi-globally ultimately uniformly bounded (UUB) and the tracking errors are restrained in the prescribed bounds. Finally, by choosing some appropriate parameters, the simulation results based on quadrotor UAV model are given to verify the effectiveness of the proposed control scheme.

Study of Flow around a Trapezoidal Model of a Small-Sized UAV into Turbulent Wake

Investigations of the structure of the flow near the surface of a trapezoidal model of a small unmanned aerial vehicle were carried out when it enters a narrow turbulent wake. All experimental data were obtained in a wind tunnel at subsonic flow velocities. A feature of the work was that the study of the flow around the model was carried out at full-scale (flight) Reynolds numbers. Using the soot-oily visualization method, data on the features of the flow around the model were obtained, taking into account such factors as the angle of attack, the presence and absence of a source of external disturbances that generated a turbulent wake. The experiments were carried out in two flow regimes: at a zero angle of attack, when there are local separation bubbles on the wing, and at a large (supercritical) angle of attack of 18 degrees, when there is a global stall of the flow from the leading edge. It was shown that the turbulent wake has a significant effect on the nature of the flow near the model surface in both cases. Local separation bubbles gradually decrease in size with a decrease in the distance between the sources of disturbances and the wing. Large-scale vortices significantly decrease in geometrical dimensions and shift towards the side edges in the event of a global stall of the flow, thereby increasing the region of the attached flow on the model surface.

Characteristic Mode Analysis Prediction and Guidance of Electromagnetic Coupling Measurements to a UAV Model

In this work, we study the current coupled to a simplified Unmanned Aerial Vehicle (UAV) model using a dual computational and experimental approach. The simplified surrogate structure reduced the computational burden and facilitated the experimental measurement of the coupled currents. For a practical system, a wide range of simulations and measurements must be performed to analyze the induced current variations with respect to properties of the incident excitation waveform, such as the frequency, angle of incidence, and polarization. To simplify this analysis, Characteristic Mode Analysis (CMA) was used to compute the eigen-currents of the UAV model and predict where and under which RF excitation conditions the coupled current is maximized. We verified these predictions using direct experimental measurement of the coupled currents. The presented simulations and measurements show the usefulness of CMA for studying electromagnetic coupling to practical systems.

Hierarchical Learning Framework for UAV Detection and Identification

The ubiquity of unmanned aerial vehicles (UAVs) or drones is posing both security and safety risks to the public as UAVs are now used for cybercrimes. To mitigate these risks, it is important to have a system that can detect or identify the presence of an intruding UAV in a restricted environment. In this work, we propose a radio frequency (RF) based UAV detection and identification system by exploiting signals emanating from both the UAV and its flight controller, respectively. While several RF devices (i.e., Bluetooth and WiFi) operate in the same frequency band as UAVs, the proposed framework utilizes a semi-supervised learning approach for the detection of UAV or UAV’s control signals in the presence of other wireless signals such as Bluetooth and WiFi. The semi-supervised learning approach uses stacked denoising autoencoder and local outlier factor algorithms. After the detection of UAV or UAV’s control signals, the signal is decomposed by using Hilbert-Huang transform and wavelet packet transform to extract features from the time-frequency-energy domain of the signal. The extracted feature sets are used to train a three-level hierarchical classifier for identifying the type of signals (i.e., UAV or UAV control signal), UAV models, and flight mode of UAV.