Unmanned Aerial Vehicle Applications Research Articles

Compact inductive and capacitive combined wireless power transfer system for unmanned aerial vehicle applications

Compact inductive and capacitive combined wireless power transfer system for unmanned aerial vehicle applications

A review of perception sensors, techniques, and hardware architectures for autonomous low-altitude UAVs in non-cooperative local obstacle avoidance

Unmanned Aerial Vehicles (UAVs) can detect and communicate with cooperative obstacles through established protocols. However, non-cooperative obstacles pose a significant threat to UAVs during low-flight operations. These obstacles include static obstacles like buildings, trees, or communication towers and dynamic objects like other UAVs. The application of autonomous UAVs in low-altitude surveillance has motivated research into non-cooperative local obstacle avoidance. This paper provides an overview of such solutions that have been proposed within the last decade. Unlike most literature that limits obstacle avoidance to algorithms, this work provides an in-depth review of obstacle avoidance components, namely the perception sensor, techniques, and hardware architecture of the obstacle avoidance system. This review categorizes the non-cooperative obstacle avoidance techniques into four groups: gap-based methods, geometric methods, repulsive force-based methods, and Artificial Intelligence (AI) based methods. This paper provides a comprehensive resource for researchers working on collision-free surveillance by autonomous UAVs at low altitudes.

Mechanical and electromagnetic interference shielding properties of natural fiber reinforced polymer composite with carbon nanotubes addition

AbstractMechanical and electromagnetic interference (EMI) shielding properties are investigated for developed synthesized green composite. The varying content of kenaf fiber‐reinforced high‐density polyethylene (HDPE) composite has been fabricated using microwave‐assisted compression molding techniques with and without the addition of multi‐walled carbon nanotubes (MWCNTs). X band range has been used for EMI shielding characterization. Optimization for mechanical strength has been done using tensile test, impact test, and translaminar fracture toughness test. Fractography by scanning electron and optical microscopy concluded that interfacial adhesion between kenaf fiber and HDPE matrix and the degree of ductility of the matrix are primary governing factors for change in mechanical properties. The differential scanning calorimetry confirmed no change in the degree of crystallization of the matrix with the addition of MWCNTs. Composite with EMI shielding effect above 30 dB along with superior mechanical properties is obtained at 16% (v/v) kenaf fiber content with the addition of 5% (wt.) conductive MWCNTs for possible application in electronic equipment casing, overhead bin, or unmanned aerial vehicles.

Circuit simulation-based comparison of power electronics devices in a five-level converter for UAV applications

<p>In this paper, the performance of a 5-level cascaded H-bridge inverter in unmanned aerial vehicle (UAV) applications is analized to identify, at the converter design stage, the better device choice depending on different UAV operation scenarios. Considering that regardless of the specific application there are some typical operations, such as take-off, climb, land, cruise, and potential recurring climbs and descents, the results can support the choice by considering the typical working conditions of the specific application where the UAV would be used. The results have been obtained by simulating the H-bridge inverter considering the circuit models of insulated-gate bipolar transistors (IGBTs), GaN high-electron-mobility transistors (HEMTs), and Si and SiC metal-oxide-semiconductor field-effect transistors (MOSFETs) provided by manufacturers. The study has highlighted that the choice of the device depends on the UAV usage, switching frequency, and load conditions. More specifically, considering the typical devices and systems costs in the case of a selective harmonic elimination procedure operating at the fundamental switching frequency, the Si devices should be used. Moreover, the preference for using IGBTs or Si MOSFETs depends on the typical working conditions of the UAV application. In the case of phase-shift carrier modulation technique, at 4 kHz the MOSFET is the best device and the choice between Si and SiC devices depends on the UAV application's main operation scenarios. At 20 kHz the SiC MOSFET is the best device, while at higher frequencies the GaN HEMT cost should be faced to take advantage of its best performance.</p>

Разработка и производство гражданских беспилотных летательных аппаратов: опыт КНР для реализации стратегии развития беспилотной авиации РФ

The study aims to review the development and application of civil unmanned aerial vehicles (UAVs) based on the experience of China. An example of DJI, a leading global UAV developer, is provided. The interaction between China's higher education institutions and modern national businesses, which demonstrates positive outcomes, is examined. The potential for collaboration in the education of students inclined towards entrepreneurial activities in high tech business and business representatives is explored. The study proposes the establishment of strategic cooperation between representatives of Russia and China in the development and application of UAVs and systems based on UAV technology, serving the interests of both nations.

Application of Unmanned Aerial Vehicles in Construction Industry

Technological advances in the field of electronics, such as miniature electromechanical devices and small powerful electric motors, have made it possible to develop small and light devices, such as unmanned aerial vehicles (UAVs). Recently, civilian UAVs are rapidly gaining popularity. Undoubtedly, UAVs will be used for many services in the future. There is already a growing demand for such fields of application of unmanned aerial vehicles as agriculture, emergency services, energy, fuel, mining, construction, geodesy (cartography), transportation, etc. Thanks to modern technologies it possible to produce light and low-power but accurate sensors that can be used by controllers with high computing power and low energy consumption. This makes it possible to develop complex control systems for UAVs that can be implemented on board. Today’s quadcopters are used for design, surveillance, search, construction inspections, and a variety of other applications.

A Statistical Study of Arien Sequences for an H.264 Prediction Module Lower Complexity

Abstract Advanced video coding, or H.264/AVC has been proved to possess a highly complex encoder with a block motion estimation (ME) scheme, entropy coding and a prediction module. Typical applications of unmanned aerial vehicles (UAVs) require real-time video compression. As a result, the current study aims to develop an approach to decrease the computing complexity of the prediction module. The software algorithm that was developed helps basic functions to be achieved in the prediction module. In fact, the user can set up, manage, deploy, and monitor the UAVs in real time. Evaluations obtained in this paper have shown that the adopted approach can significantly improve the execution time of coding and, consequently, the network performance. When comparing the original method of the Laboratory of Electronics and Information’s software with the suggested approach, experimental results show that the proposed method had achieved an increase in execution time from 3.544–15.574 %.

Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning.

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MT-GS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency.

Sky-Farmers: Applications of Unmanned Aerial Vehicles (UAV) in Agriculture

Sky-Farmers: Applications of Unmanned Aerial Vehicles (UAV) in Agriculture

Resilient Neural Control Based on Event-Triggered Extended State Observers and the Application in Unmanned Aerial Vehicles

In the real world, many systems can be written as multiple-input multiple-output (MIMO) systems, such as unmanned aerial vehicles (UAVs), unmanned vehicles, etc. Therefore, this is a problem for the generality of the research method, and this paper aimming at the control problem of MIMO nonlinear systems with system uncertainties and external disturbances, a resilient control approach is proposed based on the event-triggered extended state observer (ETESO) with neural networks (NNs) in this paper. Firstly, the constraint problem of the tracking error is transformed into an unconstrained problem based on the performance function, then the NNs are employed to approximate the uncertainties, and the ETESO with NNs is designed to estimate the combination of the approximation error and the external disturbance. Secondly, the perturbation of the controller gain is described by an external system, which is estimated by a fault observer. To avoid the problem of the differential explosion, the resilient controller is designed by the backstepping control method based on the command filter. Through the Lyapunov stability analysis, all signals of the entire system are uniformly ultimate bounded. Finally, the flight control experiment is shown to demonstrate the feasibility of the control scheme.

Application of unmanned aerial vehicle with computer vision as a tool for welfare monitoring of cage-cultured, river-based hybrid red tilapia

Application of unmanned aerial vehicle with computer vision as a tool for welfare monitoring of cage-cultured, river-based hybrid red tilapia

Domestic experience of unmanned aerial vehicles for forest conditions monitoring

Russia has vast forest resources that require constant conservation and protection measures, the implementation of which is currently impossible without the use of aviation or satellites. The widespread introduction of unmanned aerial vehicles will make it possible to effectively monitor the condition and predict changes in forest lands. The article discusses standard methods for monitoring the condition of forests and their advantages and disadvantages, highlighting the main existing threats to forests. The classification of unmanned aerial vehicles is given. The advantages of using unmanned aerial vehicles in forestry are highlighted. A classification of the areas of application of unmanned aerial vehicles in forestry is given.

Novel synergistic framework design and optimization for hydrogen-electric hybrid power system in unmanned aerial vehicle applications

Novel synergistic framework design and optimization for hydrogen-electric hybrid power system in unmanned aerial vehicle applications

Fault tolerant control of an octorotor UAV using sliding mode for applications in challenging environments

This paper presents the development of fault-tolerant controller and their application for multirotor unmanned aerial vehicles – specifically an octorotor – in challenging environments e.g. nuclear power plant inspection or other dull, dirty and dangerous applications. This paper considers a combination of sliding mode control robustness properties (to deal with actuator faults) and control allocation (to automatically redistribute the control signals to healthy actuators, especially in the event of actuator failures). The resultant controller has the ability to operate in both fault-free and fault/failure conditions without reconfiguring the main baseline controller. The proposed controller also has the ability to operate for up to six rotor failures which represent an under-actuation condition i.e., a case when only two rotors are available. The under-actuation scenarios are conditions when most FTC schemes are not able to operate due to the lack of redundancy. The simulation results conducted on the nonlinear model with wind/gusts and sensor noise, show a good tracking performance under various fault-free and fault/failure scenarios (over-actuation, sufficient actuation and under-actuation conditions).

Беспилотные мобильные средства: инновации и угрозы

The paper presents the classification of unmanned mobile vehicles and their most widespread variety - unmanned aerial vehicles (UAVs). The scope of application of UAVs is described, as well as the threats associated with their terrorist and criminal use are considered. Measures of protection against illegal use of UAVs have been defined.

Defect Detection Image Processing for Drone Inspection on Wide-Body Aircraft Surface

The dependence on Unmanned Aerial Vehicles (UAVs) has greatly increased in many sectors around the globe. UAVs are in high demand and their technology is developing quickly, due to their ability to handle a variety of issues in a sophisticated manner. UAVs deployment in the aviation industry is still in the trial phase, thus certain adjustments must be made to make sure the UAVs meet safety standards. Safety is the most important factor in the aviation sector since it involves people’s lives. UAVs are required to make the maintenance of an aircraft more efficient. For instance, UAVs are capable of replacing the labor-intensive inspection procedure with conducive and safe regulation. Additional tools or sensors need to be added to the UAVs system to ensure the objective of applying UAVs is achieved. The camera mounted on the drone is able to enhance the functionality and widen the range of applications of UAVs. This thesis presents the UAV system that is able to assist during an aircraft inspection. The camera mounted on the drone is installed with an image processing program to identify the defect caused by a lightning strike.

ТАКСОНОМІЧНИЙ МЕТОД ВИБОРУ СПОСОБУ ВЕКТОРИЗАЦІЇ ПОТОЧНОГО ЗОБРАЖЕННЯ ДЛЯ ОПТИКО-ЕЛЕКТРОННОГО МОДУЛЯ БЕЗПІЛОТНОГО ЛІТАЛЬНОГО АПАРАТА

In the article, a taxonomic method for selecting the optimal vectorization approach for processing current images in the optical-electronic module of unmanned aerial vehicles (UAVs) was developed. The primary goal of this method is to optimize UAV navigation systems, which is particularly relevant due to the need to improve data processing efficiency in conditions of limited access to satellite navigation systems. This is critically important for ensuring high autonomy and accuracy of UAVs during the performance of various tasks. The need for such a method arose from the specific challenges faced by UAVs when operating in complex and unpredictable conditions. Analysis has shown that the use of vector images can significantly reduce the time required for information processing. This is possible due to the smaller volume of data that needs to be processed compared to traditional raster images. Reducing information processing time is critically important for the operational capability of UAVs to respond to dynamic changes in the operational environment, especially in critical situations. The taxonomic approach applied in the study allows for systematic classification and evaluation of different vectorization methods in terms of their processing speed, accuracy of results, and data retention efficiency. This enables the identification of the most suitable method for the specific operational conditions in which the UAV is used, thereby optimizing the overall system performance. Furthermore, the results of this research are significant not only in the scientific field but also in practical applications. By improving autonomous navigation systems for UAVs, the study directly contributes to enhancing their effectiveness in complex and unpredictable conditions. This is particularly relevant for missions that require a high level of precision and reliability, such as those performed by military UAVs and emergency response. Enhanced navigation capabilities allow these UAVs to perform complex maneuvers and make real-time decisions based on processed vectorized images, thereby reducing the risk of errors and increasing mission success rates. An improved vectorization method could lead to significant enhancements in UAV navigation systems, making them more resistant to failures and capable of operating in less structured environments without heavy reliance on satellite signals. This enhancement is vitally important for both military and civilian UAV applications, where operational flexibility and reliability are extremely important.

Spatial Reliability Enhanced Correlation Filter: An Efficient Approach for Real-Time UAV Tracking

Traditional discriminative correlation filter (DCF) has received great popularity due to its high computational efficiency. However, the lightweight framework of DCF cannot promise robust performance when the tracker faces appearance variations within the background. These unpredictable appearance variations always distract the filter. Most existing DCF-based trackers either utilize deep convolutional features or incorporate additional constraints to elevate tracking robustness. Despite some improvements, both of them hamper the tracking speed and can only roughly alleviate the distractions of appearance variations. In this paper, a novel spatial reliability enhanced learning strategy is proposed to handle the problems aforementioned. By monitoring the variation of response produced in detection phase, a dynamic reliability map is generated to indicate the reliability of each background subregion. Then, label adjustment is conducted to repress the distractions of these unreliable areas. Compared with the conventional way of constraint where a new term is always added to realize the desired goal, label adjustment is simultaneously more efficient and effective. Moreover, to promise the accuracy and dependability of the reliability map, an adaptively updated response pool recording reliable historical response values is proposed. Extensive and exhaustive experiments on three challenging unmanned aerial vehicle (UAV) benchmarks, i.e., UAV123@10fps, DTB70 and UAVDT, which totally include 243 video sequences, validate the superiority of the proposed method against other state-of-the-art trackers and exhibit a remarkable generality in a variety of scenarios. Meanwhile, the tracking speed of 65.2FPS on a cheap CPU makes it suitable for real-time UAV applications.

Assessment of 5G Connectivity for UAV Operations in Urban Environments: An Analysis of Network Performance and UAV Communication Architecture

This article presents an in-depth analysis of the integration of 5G connectivity for unmanned aerial vehicle (UAV) operations in urban environments, focusing on network performance and the architectural framework necessary for optimal UAV communication. As UAVs become increasingly prevalent in urban applications, from surveillance to delivery services, the demand for robust and reliable communication systems has become paramount. This study explores the unique challenges posed by urban settings, such as signal obstruction and high-density network traffic, and examines how 5G technology offers solutions through advanced features like beamforming. By detailing the setup and evaluation of a UAV communication architecture that incorporates 5G modules, including the use of the NVIDIA Jetson AGX Orin Developer Kit for real-world testing, this article highlights the significant improvements in data rate, latency, and reliability achieved with 5G networks compared to traditional communication technologies. The findings underscore the transformative potential of 5G connectivity in enhancing UAV operational efficiency and reliability in complex urban landscapes. Through case studies and practical insights, the article also provides a glimpse into the future of urban UAV applications, paving the way for further research and development in this dynamic field.

An Approach to Preliminary Design of a Quadrotor Cargo UAV

Unmanned aerial vehicles (UAV) are widely used in many different application areas today. UAVs are very cheaper than the other aerial platform and also their give opportunity to users in operating flexibility. It can be mentioned that the cargo transportation of UAV application area has high potential to grow. Compared to traditional highway delivery methods, cargo drones can offer cost savings by eliminating the need for human drivers, reducing fuel consumption, and optimizing delivery routes. Cargo drones can revolutionize the e-commerce industry by offering same-day or even same-hour delivery options. This can improve customer satisfaction, reduce shipping costs, and enable businesses to expand their operations. The main purpose of the study is to develop a preliminary design method for a quadrotor Cargo UAV to be used for cargo transportation. Within the scope of preliminary design activities, the initial sizing, optimizations and performance analyzes of the components were made. By using these results of the design, it was observed that the number of design iterations and the design time were significantly reduced.