UAVs Research Articles

Countering Unmanned Aircraft Systems – A Multi-Domain Effort

Abstract In the last decades, the proliferation of the unmanned aircraft systems (UASs) has altered the modern battlefield and the need to counter these inexpensive, flexible, and expendable systems has become paramount. UASs come in a variety of sizes and capabilities, the larger ones may achieve effects compared to a cruise missile and the smaller systems are difficult to detect as they manoeuvre across the battlefield in order to successfully conduct tactical-level strikes. So it is a must to understand that countering this kind of threat is a shared and joint responsibility and the approach has to be a comprehensive one, covering a broad spectrum of military, civil and legal perspective on this subject matter. Moreover, as it is clear that there is a need to employ multi-domain solutions to nullify the UAS threat, nations should aim to achieve technical interoperability and standardization given by a common doctrine and operating procedures.

Communication Technologies as a Medium for Control and Data Transfer in the Unmanned Aircraft Systems

Abstract The currently available communication technologies used as a medium between the main elements of unmanned aircraft systems – unmanned aerial vehicles and command centers – are discussed. The advantages and disadvantages of different types of communication technologies are analyzed, as well as the relationship between their technical parameters and the operational characteristics of the overall unmanned aerial system. General conclusions have been drawn regarding the correct selection of communication technology as a medium between the main elements of the unmanned aerial system and the tasks it solves.

Characteristic Elements of Combat Drones in Military Actions. Unmanned Aerial Vehicles Procured by Romanian Armed Forces

Abstract Developments in the war of the future have brought to the fore unmanned aircraft or drones used in national and/or multinational military actions, as particularly important means to achieve operational success. The parameters related to this modern, flexible and particularly maneuverable combat system allow the conjugation of capabilities necessary to fulfill the missions received by the operational structures during preparation and conduct of operations. The present study first provides a general approach to drone use in military actions, taking into account aspects from previous armed conflicts, as well as from the ongoing war in Ukraine. The objective of the study points to a series of important drone purchases that will be made by our country, to increase the combat potential of the Romanian joint and tactical forces, which will act on national territory and within the North Atlantic Alliance, against any aggressive forces of an unfriendly state.

Wireless Electrification System for Photovoltaic Powered Autonomous Drone Charging

Wireless Electrification System for Photovoltaic Powered Autonomous Drone Charging

Performance evaluation of BLDC motor drive mounted in aerial vehicle (drone) using adaptive neuro-fuzzy

The development of autonomous drones equipped with cameras and various sensors has paved the way for their application in agriculture and perimeter security. These aerial drones require specific power, acceleration, high torque, and efficiency to meet the demands of agricultural tasks, utilizing built-in brushless DC (BLDC) motors. However, a common challenge drone’s face is maintaining the desired speed for extended periods. Enhancing the performance of BLDC motors through advanced controllers is crucial to address this issue. This research paper proposes optimizing the size and speed of brushless DC motors for aerial vehicles using an adaptive fuzzy inference system and supervised learning techniques. When these drones carry loads, the BLDC motors must dynamically adjust the drone's speed. During this phase, the motors must control their speed and torque using artificial intelligence controllers like adaptive neuro-fuzzy inference systems (ANFIS) to enhance the drone's functionality, resilience, and safety. This research has conducted analyses focused on improving the performance of BLDC motors explicitly personalized for unmanned aerial vehicle (UAVs). The proposed method will be implemented using MATLAB/Simulink, expecting to significantly enhance the BLDC motor's performance compared to conventional controllers. Comparative analyses will be conducted between traditional and ANFIS controllers to validate the effectiveness of the proposed approach.

Исследование модернизации морского пассажирского порта на основе цифрового двойника и оценка инфраструктуры с помощью динамических данных от беспилотных авиационных систем

The current state of the maritime passenger transportation industry is considered, as well as the factors influencing the chosen industry are investigated (competition between ports in the sea region, new environmental requirements and a shortage of space for new ports and terminals in megacities). Models of the evolution of seaports and terminals in the regions of the seas are analyzed and the need to solve the problem of forecasting development, reasonable modernization is revealed infrastructure. The importance of integrating passenger ports into urban transport systems and ensuring effective interconnection of maritime transport with regional transport systems is noted. Special attention is paid to the growth and development potential of sea ferries and cruises in the Baltic Sea region, the historical importance of St. Petersburg for cruise tourism and the need for the gradual restoration of the port and the development of new route networks are noted. The necessity of developing new methods for modernizing the infrastructure of passenger seaports based on the creation of digital models and the use of dynamic data is substantiated. As a solution, it is proposed to create a new digital model of a marine passenger port using information obtained from unmanned aircraft systems. This model will accurately take into account the infrastructural features of passenger ports and terminals, as well as the established priority of berths for the service of cruise and ferry ships. For multi-scenario modeling, a new digital model of the marine passenger port of St. Petersburg “Marine Façade” is proposed. To analyze the simulation results, the developed software modules in the Python programming language are proposed to describe the behavior strategies of the decision maker (port manager). To describe the decision-making process in the conditions of uncertainty that arises when making a decision on the modernization of the port infrastructure, the choice of the Wald criterion was justified as a criterion. A series of experiments was performed, based on the data, digital 2D and 3D models of a marine passenger port were formed for subsequent use in the AnyLogic environment, and a digital twin was built. A distinctive feature of the model is the up-to-date information on the state of the transport infrastructure and integration with data on ship calls. The presented model, methods of working with the results of multi-dimensional modeling, the use of unmanned aircraft systems, and the development of a model based on decision-making under uncertainty can be applied to other passenger seaports and terminals, which emphasizes the universality of the proposed approach.

Обеспечение общественной безопасности в процессе использования беспилотных воздушных судов

The article is devoted to the urgent problem of legal regulation of the use of unmanned aerial systems and unmanned aircraft in the Russian Federation. Based on the analysis of changes in Russian legislation that came out in 2023, an assessment of the main areas of use of unmanned aircraft systems in economic activities is carried out. The author characterizes the powers of the federal executive authorities in the field of ensuring public safety when using unmanned aircraft. The current directions of the legal regulation of unmanned aircraft flights in the Russian Federation are reviewed.

Monitoring Nodal Transportation Assets with Uncrewed Aerial Vehicles: A Comprehensive Review

Monitoring Nodal Transportation Assets with Uncrewed Aerial Vehicles: A Comprehensive Review

DNN-PolSAR: Urban Image Segmentation and Classification using Polarimetric SAR based on DNNs

Synthetic Aperture Radar (SAR) image segmentation and classification is a popular technique for learning and detection of objects such as buildings, trees, monuments, crops water-bodies, hills, etc. SAR technique is being used for urban development and city-planning, building control of municipal objects, searching best locations, detection of changes in the existing systems, etc. using polarimetry based on Deep Neural Networks. In this paper, weproposed a technique for Urban Image Segmentation and Classification using Polarimetric SAR based on Deep NeuralNetworks (DNN-PolSAR). In our proposed DNN-PolSAR technique, we useMask-RCNN, LinkNet, FPN, and PSP- Net as model architectures, whereas ResNet50, ResNet101, ResNet152, and VGG-19 are used as backbone networks.We first apply polarimetric decomposition on airborne Uninhabited Aerial Vehicle Synthetic Aperture (UAVSAR) im- ages of urban areas and then the decomposed images are fed to DNNs for segmentation and classification. We then simulate DNN-PolSAR considering different hyper-parameters and compare the obtained scores of hyper-parametersagainst used model architectures and backbone networks. In comparison, it is found that DNN-PolSAR based on FPN model with ResNet152 performed the best for segmentation and classification. The mean Average Precision (mAP) score of the DNN-PolSAR based on FPN with a pixel accuracy of 90.9% is 0.823, which outperforms other Deep Learning models.

Towards Fully Autonomous Drone Tracking by a Reinforcement Learning Agent Controlling a Pan–Tilt–Zoom Camera

Towards Fully Autonomous Drone Tracking by a Reinforcement Learning Agent Controlling a Pan–Tilt–Zoom Camera

АРХІТЕКТУРА СИСТЕМИ АВТОНОМНОГО КЕРУВАННЯ ДЛЯ FPV-ДРОНІВ

Drone technologies and robotic systems, that can be used to optimize or replace human labor in different areas, are continuing to develop and expand their area of application. Computational hardware, that can be used as an extension to basic drone hardware, is becoming more powerful for a smaller price and size. Autonomous drone control provides a practical solution for issues that are present when a drone is controlled manually by an operator. There are limitations that exclude the possibility of operator control and some solutions are much less effective if there is no autonomous algorithm. A large distance, radio interference or a huge amount of data to be analyzed are not as critical if a drone is capable to make decisions autonomously without an operator. Because of the features of a basic amateur FPV-drone its flight controller does not operate enough computing power to execute complex algorithms such as object detection, object tracking, calculation of a proper trajectory etc. In cases like this a companion computer should be used. Depending on an area of application, drone control algorithms may vary. Flight controllers’ firmware has some embedded functionality with relatively simple algorithms like pre-defined flight routes that use GCS-coordinates. In the case when more complex behavior is required (image processing, AI integration or autonomous decision making with manual controls), such firmware provides an ability to accept various drone commands that correspond to the MAVLink communication protocol. This work investigates important details of companion computers integration with flight controllers with examples and describes hardware and software aspects of implementation of autonomous drone controls. The research also provides solutions to problems that can be possible when implementing such a system.

Avian eye-inspired perovskite artificial vision system for foveated and multispectral imaging.

Avian eyes have deep central foveae as a result of extensive evolution. Deep foveae efficiently refract incident light, creating a magnified image of the target object and making it easier to track object motion. These features are essential for detecting and tracking remote objects in dynamic environments. Furthermore, avian eyes respond to a wide spectrum of light, including visible and ultraviolet light, allowing them to efficiently distinguish the target object from complex backgrounds. Despite notable advances in artificial vision systems that mimic animal vision, the exceptional object detection and targeting capabilities of avian eyes via foveated and multispectral imaging remain underexplored. Here, we present an artificial vision system that capitalizes on these aspects of avian vision. We introduce an artificial fovea and vertically stacked perovskite photodetector arrays whose designs were optimized by theoretical simulations for the demonstration of foveated and multispectral imaging. The artificial vision system successfully identifies colored and mixed-color objects and detects remote objects through foveated imaging. The potential for use in uncrewed aerial vehicles that need to detect, track, and recognize distant targets in dynamic environments is also discussed. Our avian eye-inspired perovskite artificial vision system marks a notable advance in bioinspired artificial visions.

UAV Multi-Dynamic Target Interception: A Hybrid Intelligent Method Using Deep Reinforcement Learning and Fuzzy Logic

With the rapid development of Artificial Intelligence, AI-enabled Uncrewed Aerial Vehicles have garnered extensive attention since they offer an accessible and cost-effective solution for executing tasks in unknown or complex environments. However, developing secure and effective AI-based algorithms that empower agents to learn, adapt, and make precise decisions in dynamic situations continues to be an intriguing area of study. This paper proposes a hybrid intelligent control framework that integrates an enhanced Soft Actor–Critic method with a fuzzy inference system, incorporating pre-defined expert experience to streamline the learning process. Additionally, several practical algorithms and approaches within this control system are developed. With the synergy of these innovations, the proposed method achieves effective real-time path planning in unpredictable environments under a model-free setting. Crucially, it addresses two significant challenges in RL: dynamic-environment problems and multi-target problems. Diverse scenarios incorporating actual UAV dynamics were designed and simulated to validate the performance in tracking multiple mobile intruder aircraft. A comprehensive analysis and comparison of methods relying solely on RL and other influencing factors, as well as a controller feasibility assessment for real-world flight tests, are conducted, highlighting the advantages of the proposed hybrid architecture. Overall, this research advances the development of AI-driven approaches for UAV safe autonomous navigation under demanding airspace conditions and provides a viable learning-based control solution for different types of robots.

Very Low Level Flight Rules for Manned and Unmanned Aircraft Operations

An analysis of the development of legal regulations regarding unmanned civil aviation leads to the conclusion that the current air traffic rules are among the key issues that require amending. Are drones allowed to fly at any height? Can drones fly freely over a person’s house or garden, several meters above the ground? What is the minimum allowable height for drone flights? The method of study consisted of content analysis of the existing legislation. Current doctrines were confronted with the existing regulations, documents, materials, safety reports, and statistics. The results of the study show that the existing air traffic rules, precisely in the case of aircraft operations performed by manned and unmanned aviation at very low heights, are definitely practical in nature. First, in most countries violations of air traffic rules are prohibited acts subject to criminal penalty. Second, determining the principles of air traffic for air operations is of crucial importance for determining legally permissible interference in property ownership. The urban air mobility is outside the scope of this research.

Research on Path Planning Method based on Graph Search Algorithm

Path planning, crucial in robotics and autonomous vehicles, involves finding efficient routes from start to finish while avoiding obstacles. Graph search algorithms like BFS, DFS, and A* are commonly used for this purpose. This research focuses on analyzing these algorithms' performance and applicability in diverse scenarios. The study provides a comprehensive overview of path planning's definition, application domains, and fundamental principles. It then delves into the core graph search algorithms: BFS explores nodes layer by layer, ensuring the shortest path is found first but suffering from high time complexity. DFS explores nodes in a depth-first manner, potentially leading to shorter paths but risking getting trapped in local optima. In contrast, A* combines the strengths of BFS and DFS by using heuristic functions to guide the search for the cheapest path to the goal. Despite their utility, graph search algorithms have limitations. The high time complexity of A* in large-scale environments and the potential for local optima are key challenges. To address these, research explores improved methods like GBFS and bidirectional A* search. The future direction of research includes developing more efficient heuristic functions, exploring hybrid algorithms, parallelizing path planning, and applying these methods to new domains like autonomous drones and self-driving cars. This research paves the way for more robust and efficient path planning algorithms in various applications.

Analysing the impacts of extreme torrential events using multi‐temporal LiDAR datasets—The Schöttlbach catchment, Upper Styria, Austria

AbstractExtreme precipitation events in small alpine catchments trigger hazardous hydro‐geomorphic processes that cause considerable damage to settlements and infrastructure. In summer 2011 and 2017, two flood events mobilizing large amounts of sediments struck the town of Oberwölz (Styria, Austria) located at the outlet of the Schöttlbach catchment. We used data from local weather stations and precipitation radar to analyse the meteorological settings that caused the flooding. We compiled a consistent sediment budget for the 2017 event by combining geomorphic mapping, connectivity analysis, high‐resolution airborne LiDAR (ALS) and uncrewed aerial vehicle (UAV)‐borne LiDAR (ULS), data from other authors for the 2011 event and external information (e.g., event analysis and excavation data). The 2017 event mobilized higher sediment volumes than the 2011 event (131 000 m3 vs 90 000 m3) even though 24‐h precipitation and peak discharges were lower in 2017. First assumptions that the larger sediment output was caused by the reworking of the 2011 flood deposits proved to be incorrect. The impacts of the 2011 event affected the resilience of the geomorphic system resulting in a significantly higher hillslope sediment supply. We conclude that sediment transport in alpine catchments can increase disproportionately when recurrence intervals fall below a critical level.

An analytical view on Unmanned Aircraft Systems

<p>Unmanned Aircraft Systems (UAS) is a booming technology with a future perspective and does have a huge potential to transfigure warfare and enable up-to-date civilian applications. It furthermore matures in a technological way as to be impinged into the civil society. In 2010, the importance of scientific applications in the respective field was demonstrated by DOD in the contemporary years. In recent years, UAS has played an integral role in a number of missions that are public, like law enforcement, which is local, board surveillance, weather monitoring, wildlife surveys, and military training. UAS do force some challenges that are numbered as lacking a pilot who is on-board in order to see and hence avoid supplemental aircraft, and furthermore, the extensive discrepancy in the missions related to UAS, and in order to implement the operations in the NextGen time frame impinged in NAS, the capabilities of the respective topic must be communicated. The applications of UAS are numbered as Ariel Mapping and Meteorology, intelligence, remote sensing, surveillance and reconnaissance, environmental monitoring and agriculture, border security, security applications and law enforcement, counter insurgency, electronic attacks, attack strikes, communication relays, target identification, and designation. Via this survey paper, it can be concluded that UAS is emerging as a valuable and helpful technology having tremendous potential for revolting warfare and enabling new applications w.r.t the UAS field.<strong></strong></p>

Тенденции и потенциал развития технологичных видов спорта в студенческой среде

The development of modern technologies leads to transformation of all the spheres of society, including sports. One of the key trends of recent years is emergence and fast spread of high-tech (innovative) sports, where digital technologies are embedded directly into the process of competition, such as phygital (combined functional and digital) sport, drone (unmanned aircraft) racing, sports programming and others. These sports are now bringing together people of different ages and interests. The article is aimed to analyse the current state of hi-tech sports in Russia in the period of the key sporting event for their development – the multisport tournament “Games of the Future” (Phygital Games), held in 2024 in Kazan, Russia. The article also considers the current state and prospects of high-tech sports within the framework of student sports and other students’ and youth activities. Student sports are open to change and flexible which makes them one of the most promising areas for the spread of new sports disciplines.

Design and Development of Quadcopter for Agro-Chemical Spray in Agricultural Field

The advent of Agricultural Drones promises to revolutionize modern farming practices by employing autonomous drones for crop surveillance and pesticide application. Outfitting quadcopters with spraying mechanisms presents numerous advantages over traditional methods. Firstly, it facilitates precise and targeted application of agro-chemicals, thereby minimizing wastage and environmental pollution. Furthermore, quadcopters exhibit the capability to effortlessly navigate challenging terrains, accessing areas previously unreachable by conventional spraying equipment and ensuring comprehensive crop coverage. Additionally, their autonomous operation or remote human supervision enhances operational efficiency, resulting in reduced labor costs. This initiative explores the integration of unmanned aerial vehicles (UAVs) into agricultural practices, specifically emphasizing their role in precisely spraying agro-chemicals. The project encompasses the entire development cycle, from design and development to the deployment of customized agricultural drones capable of autonomous flight and accurate pesticide distribution. The incorporation of quadcopters for precise agro-chemical spraying marks a significant advancement in agricultural technology, offering precision, efficiency, and sustainability. Ongoing research, development, and collaboration play a crucial role in realizing the transformative benefits of this innovative approach, ultimately enhancing agricultural productivity and environmental stewardship.

Exploration of UAV Application Skill Competition and Talent Training Mode of UAV Application Technology Major

By 2035, China will gradually establish an unmanned air transportation service system covering manned air transport, and form a batch of unmanned aircraft enterprises that are in an international leading position in the fields of aviation manufacturing, flight monitoring and operation, etc. In January 2022, the Civil Aviation Administration of China (CAAC), the Development and Reform Commission (NDRC), and the Ministry of Transportation (MOT) jointly issued the 14th Five-Year Plan for the Development of Civil Aviation. Plan, proposing to accelerate the technological innovation of drones, improve relevant laws and regulations, and carry out high-quality services to realize the positive and innovative development of the drone industry. In February 2020, China added 16 new occupations, of which drone installation and maintenance worker and drone pilot have been officially included in the National Occupational Classification Catalog. The article discusses the drone application skill competition and the talent cultivation path of drone application technology for related personnel s reference.