Підходи до адаптації налаштувань поля зору операторів під час тренування та експлуатації дронів

The use of unmanned aerial vehicles allows the countries that use them to significantly reduce the loss of manpower and equipment during the combat mission and at the same time significantly increase the effectiveness of the use of high-precision and conventional means of destruction. The greatest experience in the use of unmanned aerial vehicles was acquired by countries that are actually advanced in terms of military technology (in particular, the USA, Israel, Turkey, etc.), which took an active part in armed conflicts in the Middle East, the North Caucasus, etc. In addition, in modern conditions, the threat of uncontrolled spread of the use of unmanned aerial vehicles of a light class, which can be used for the purpose of carrying out terrorist acts on important state and military facilities, is growing. Unmanned aerial vehicles have become so important to success on the battlefield that they are sometimes used by the military to destroy enemy drones. In addition, it is with the help of unmanned aerial vehicles that one side receives the coordinates of military targets and command posts of the opposite side, which are subsequently destroyed by accurate artillery strikes. In the article, based on the analysis of modern wars and armed conflicts, combat experience and features of the use of unmanned aerial vehicles of the armed forces of the russian federation, an analysis of unmanned aerial vehicles for typical tasks, in particular, conducting reconnaissance, adjusting fire, striking and electronic warfare, was carried out. In particular, the conducted analysis indicates a tendency to increase the scale of use of unmanned aerial vehicles by the armed forces of the russian federation in conditions of a full-scale armed conflict (not excluded due to the end of stocks of high-precision missiles), in contrast to the experience of the combat use of individual unmanned aerial vehicles in the East of the country and the expansion of the range of tasks.

The conducted SWOT analysis made it possible to develop problematic issues that are proposed during the operation of unmanned aerial vehicles, proposals were made for the creation of a mobile complex of the use of unmanned aerial vehicles based on the chassis of a truck. Formulation of the problem. During hostilities, unmanned aerial vehicles (UAVs) were widely used. The massive use of the latest robotic (automated) weapons and military equipment on the battlefield is changing the nature of units' actions. Currently, almost every combat unit has a UAV application group. The high efficiency of their use is confirmed by high results on the battlefield. The security and defense forces of Ukraine are armed with dozens of types of UAVs for various purposes and with various capabilities for lifting cargo and carrying explosives. The use of UAV combat units in the field. Launches of lethal vehicles are carried out by hand or with the help of launch devices. With this mobile application group, the BPLA, although it is at a distance from the line of the next combat encounter, does not have sufficient security and protection from enemy fire. Preparation for use, maintenance of UAVs and charging of batteries in stationary conditions the day before, which reduces the efficiency of actions.The deployment of mobile groups of UAV operators is carried out on vehicles that are available to the military unit at the time, and which are not adapted for the high-quality performance of the combat mission by the group. UAV operators and equipment are not protected from exposure to low ambient temperatures and have no protection from small arms and shrapnel damage. Time indicators of deployment on the terrain of the complex for launching UAVs and folding after the completion of a combat mission need improvement. Analysis of recent research and publications. Scientific studies on improving the actions of units equipped with UAVs were carried out in the National Guard even before the beginning of the full-scale invasion of the Russian Federation. For example, in [1-2], data are given regarding the need for intelligence information and the development of a rational procedure for the use of intelligence unmanned aerial vehicles. In [3], the methodological apparatus for researching the problems of using information technologies and telecommunication systems in the process of military management is presented. The purpose of the article is to justify the need to create a mobile complex for the use of unmanned aerial vehicles based on a truck chassis. Provide recommendations on the creation of a mobile complex for the use of unmanned aerial vehicles.

Nowadays, in the course of war between Ukraine and the russian federation, there is a large-scale employ of various weapon systems that are used on land, in the air, and at sea. Unlike the enemy, Ukraine Forces prefer to utilize asynchronous methods of armed struggle. In order to successfully implementation of these asynchronous methods is necessary used to contemporary unmanned aerial vehicles and unmanned air systems. It is known that at the beginning phase of the war the Ukrainian defenders were used unmanned aerial vehicles and unmanned air systems on the principle of “controlled chaos”. As a result of these active operations, the Ukrainian defenders could discourage and defeat enemy. Therefore, in order to secure effective usage of unmanned aerial vehicles and unmanned air systems it is necessary to introduce a clear hierarchy with clear classification features. This task is certainly relevant today for Ukrainian NAVY. It is the significant task, because the Ukrainian NAVY has some experience in the combat use of unmanned aerial vehicles and unmanned air systems, but they need its systematization and comprehensive implementation, taking into account the specifics of conducting combat operations at Black sea. At the same time, in order to improve functionality and effectiveness of the unmanned aerial vehicles and unmanned air systems the developers must apply information technologies such as, internet of military things, cloud technologies and artificial intelligence. For instance, if developers wanted to implementation of internet of military things technologies, they would be able to ensure intercommunication among different groups of aerial vehicles and simplify to control process of them. In the proposed paper, the authors tried to perform capabilities analysis of usage of different types unmanned aerial vehicles and unmanned air systems with various control systems and military categories based on the use of NATO standards. In addition, the authors performed this analysis considering different types Ukrainian NAVY ships and support vessels. Moreover, the authors of the paper also proposed a classification for unmanned aerial vehicles of Ukrainian NAVY.

Traffic management in smart cities using unmanned aerial vehicles (UAVs), commonly known as drones, is an innovative and promising approach to address the growing challenges associated with urban transportation. UAVs can be deployed in various ways to monitor, analyze, and improve traffic flow and safety in smart cities. Traffic surveillance and monitoring, traffic flow optimization, emergency response, public safety, parking management, environmental monitoring, traffic surveys, event and congestion management, infrastructure inspection, and public transport support are some ways in which UAVs can be used for traffic management in smart cities. Collaborations between government agencies, law enforcement, transportation departments, and drone operators are essential for the successful integration of UAVs into the smart city infrastructure. Additionally, advanced technologies like artificial intelligence and machine learning can be used to process and analyze the vast amounts of data collected by drones, allowing for more proactive and efficient traffic management in smart cities.

In the 21 st century, unmanned systems (especially unmanned aerial vehicles) will play a dominant role in the operational fields. Thanks to the technological developments witnessed in many fields, the use of unmanned aerial vehicles for military purposes is becoming easier. Looking at the operations carried out over the last 25 years, it can be seen that most were conducted in residential areas, where and techniques, tactics and equipment with asymmetric effects will make significant differences. In addition to this, the more loss of life in operations, the more governments come under pressure from the public. Taking these factors into consideration, it is believed that unmanned aerial vehicles, which can be used to increase dominance in operations and prevent loss of life, will be used more often and more effectively in the future. It is also believed that unmanned aerial vehicles will be used as assault media in both residential areas and in other operational environments in order to take advantage of the high level asymmetric effect.

The publication deals with the issue of ensuring the stability of an unmanned aerial vehicle flight by speed. An analysis of the physical essence of the process of ensuring the unmanned aerial vehicle stability by speed is presented. Attention is paid to the flight modes in which the operator (external pilot) may encounter difficulties in the practical piloting of the unmanned aerial vehicle. The possible causes of abnormal situations when flying the unmanned aerial vehicle at speeds close to the borderline low are analyzed. Possible actions of the operator (external pilot) to return the unmanned aerial vehicle to the operating speed range from the area of instability are considered. The article shows the features of stability and controllability of an unmanned aerial vehicle in a route flight mode. Attention is paid to the complexity of piloting and safety of flight in the second modes. The article demonstrates the method of determining the boundary between the first and second flight modes. The features of unmanned aerial vehicle management and ensuring stability in the first and second modes are shown. The issue of dynamic stability of the unmanned aerial vehicle is investigated. Numerical modeling of the longitudinal movement of the unmanned aerial vehicle in free, uncontrolled flight was carried out, trajectories for the unmanned aerial vehicle of the selected configuration with a change in speed and angle of inclination of the trajectory in time were obtained. Graphs of movement trajectories with changes in speed and height over time were constructed, graphs of transient processes were constructed for cases of stable and unstable flight modes. An analysis of the external factors that most affect the flight parameters in various conditions of unmanned aerial vehicle use was carried out.

Unmanned aerial vehicles (known as drones) and artificial intelligence are attracting academic and industrial attention. Unmanned aerial vehicles (UAVs) have increased the ability to manage and supervise from remote locations. Unmanned aerial vehicles are employed in a variety of purposes and are becoming extremely popular. Recent advancements in unmanned drones and artificial intelligence have created a new opportunity for independent flying and maintenance. Artificial intelligence and deep learning are already driving the advancement of unmanned aerial vehicles and ensuring their independent future. Computer vision has made significant advances in image feature extraction and classification, as well as object recognition, making this a very appealing research subject when used on unmanned aerial vehicles. Because UAVs learn via techniques and apply them for decision making purposes, artificial intelligence is also vital and beneficial, but it can also be hazardous and severe. Artificial intelligence has decreased the number of obstacles faced by unmanned aerial vehicles while also boosting their capabilities and allowing them to enter new markets. The combination of Unmanned Drones and Artificial intelligence has resulted in quick and accurate results. The integration of UAVs and artificial intelligence has aided in real-time surveillance, data collection and analysis, and forecasting in computer/wireless network infrastructure, smart cities, the armed services, agricultural production, and mining. This study obtained and consolidated studies on the usage of UAVs, along with artificial intelligence and related algorithms, in various domains and countries. The goal was to illustrate overall scope and significance of artificial intelligence models in improving UAV performance, problem solving, and a variety of application domains.

Orchard monitoring is a vital direction of scientific research and practical application for increasing fruit production in ecological conditions. Recently, due to the development of technology and the decrease in equipment cost, the use of unmanned aerial vehicles and artificial intelligence algorithms for image acquisition and processing has achieved tremendous progress in orchards monitoring. This paper highlights the new research trends in orchard monitoring, emphasizing neural networks, unmanned aerial vehicles (UAVs), and various concrete applications. For this purpose, papers on complex topics obtained by combining keywords from the field addressed were selected and analyzed. In particular, the review considered papers on the interval 2017-2022 on the use of neural networks (as an important exponent of artificial intelligence in image processing and understanding) and UAVs in orchard monitoring and production evaluation applications. Due to their complexity, the characteristics of UAV trajectories and flights in the orchard area were highlighted. The structure and implementations of the latest neural network systems used in such applications, the databases, the software, and the obtained performances are systematically analyzed. To recommend some suggestions for researchers and end users, the use of the new concepts and their implementations were surveyed in concrete applications, such as a) identification and segmentation of orchards, trees, and crowns; b) detection of tree diseases, harmful insects, and pests; c) evaluation of fruit production, and d) evaluation of development conditions. To show the necessity of this review, in the end, a comparison is made with review articles with a related theme.

The use of unmanned aerial vehicles (UAVs) in agriculture in general, and precision agriculture in particular, is expanding significantly every year. UAVs are employed in various tasks, including sowing, monitoring crop growth and yields, field mapping, and spraying crops with plant protection products (PPP) or applying fertilizers. Precision agriculture enables the integration of geospatial data, GIS and remote sensing technologies, artificial intelligence, Big Data, the Internet of Things, and other innovative solutions. UAVs provide opportunities for rapid monitoring, analyzing field conditions and dynamics, identifying problem areas requiring managerial intervention, evaluating the effectiveness of agronomic practices, and storing photogrammetric data and high-resolution images efficiently. Modern UAVs, accessible to farmers, not only deliver current information on plant condition and growth dynamics but also allow for protective treatment of fields and perennial plantations using pesticides. UAVs can provide georeferenced data on the state of cultivated crops, significantly assisting farmers in maintaining high yields. Moreover, UAVs equipped with multispectral and RGB cameras enable the prompt storage of agricultural images in the near-infrared spectrum, facilitating monitoring of vegetation health and condition. UAV imaging offers much greater detail compared to satellite imagery, achieving resolutions down to centimeters per pixel, thanks to flight altitudes ranging from 100 to 600 meters above ground. The paper outlines the use of UAVs in precision agriculture and explores field monitoring methods using UAVs. The implementation of UAV imaging technology allows for the creation of electronic field maps and the rapid adoption of managerial decisions based on the collected data. The NDVI index obtained with UAVs provides a more comprehensive and detailed representation of current conditions on individual field sections, a level of detail that is difficult to achieve with satellite imagery. It is noted that our country has strong potential for adopting UAVs in agriculture, considering their technical, economic, and human resources.

The appearance in widespread use of unmanned aerial vehicles, both multi-rotor and wing-carrying aircraft, revealed the possibility of their use in the activities of the State Emergency Service of Ukraine. They can be used for emergency reconnaissance, aerial surveying, search operations, aviation chemical work related to the circulation of hazardous substances, monitoring of territories and objects, transmission of radio signals, delivery to the site of emergencies various types of payload, conducting alerting, lighting emergency situations and direct firefighting. Therefore, the issue of using unmanned aerial vehicles in the activities of the State Emergency Service of Ukraine is relevant. In essence, the use of an unmanned aerial vehicle is reduced to two main types of work - observation or work around a point object or movement over long distances to ensure work on the earth's surface. It is clear that the technical characteristics of the unmanned aerial vehicle determines its suitability for use in the relevant types of work. One of these characteristics is the range of radio communication, the busiest channel of which is real-time video communication, which is essential for most assigned tasks. The article attempts to estimate the range of video data transmission by radio for the most common models of multi-rotor unmanned aerial vehicles of mass production and video data transmission systems that can be used optionally. To this end, we analyze the characteristics of video transmission systems, factors that affect the quality of video communication and others. Existing mass-produced models are best suited to work around a point object. Their use for long-distance flights will be limited by the range of video data transmission. By overcoming this situation, the authors see the use of unified unmanned aerial vehicles equipping them with optional video transmission systems.

<p>Magnetic mapping is commonly used in the academic and industrial sectors for a wide variety of objectives. To comply with a broad range of survey designs, the use of unmanned aerial vehicles (UAVs) has become frequent over the recent years. The majority of existing systems involves a magnetic acquisition equipment and its carrier (an UAV in this context) with no -or very few- connections between the two systems. Terremys is conceiving and optimizing UAVs specifically adapted for geophysical magnetic acquisitions together with the appropriate processing tools, and performs magnetic surveying in challenging environments. Terremys’ “Q6” system weights 2.5 kg in air, including UAV & instrumentation, and allows 30 min swarm or individual flights.</p><p>Rotary-wing UAVs are found to be the most adaptive systems for a wide range of contexts and constraints (extensive range of flights heights even with steep slopes). They offer more flight flexibility than fixed-wing aircrafts. One of the major problems in the use of rotary-wings UAVs for magnetic mapping is the magnetic field generated by the aircraft itself on the measurements. Towing the magnetic sensor 2 to 5 m under the aircraft reduces data positioning accuracy and decreases the performances of the UAV, which can be critical for high-resolution surveys. To overcome these problems, a deployable 1 m long boom is rigidly attached to the UAV. The UAV magnetic signal can be divided between 1-the magnetic field of the whole equipment and 2-a low to high frequency magnetic field mostly originating from the motors. The magnetization of the system is the principal source of magnetic noise. It is modelled and corrected by calibration-compensation processes permitted by the use of three-component fluxgate magnetometers. The time-varying noise depends on the motors rotational speed and is minimized by optimizing the UAV components and characteristics along with the boom’s length.</p><p>The final set-up is able to acquire magnetic data with a precision of 1 to 5 nT at any height from 1 to 150 m above ground level. The high-precision magnetic measurements are coupled with a centimetric RTK navigation system to allow for high-resolution surveying. The quality of the obtained data is similar to that obtained with ground or aerial surveys with conventional carriers and matches industrial standards. Moreover, Terremys’ systems merge in real-time data from all the aircraft instruments in order to integrate magnetic measurements, positioning information and all the UAV’s flight data (full telemetry) into a unique synchronized data file. This opens up many possibilities in terms of QA/QC, data processing and facilitates on-field workflows.</p><p>Case studies with diverse designs, flight altitudes and targets are presented to investigate the acquisition performances for different applications, as distinct as network positioning, archaeological prospecting or geological mapping.</p><p>The full integration of the magnetic sensor to the drone opens the possibility for implementation additional sensors to the system. The adjoining of other magnetic sensors would allow multi-sensors surveying and increases daily productivity. Diverse geophysical sensors can also be added, such as thermal/infrared cameras, spectrometers, radar/SAR.</p>

With the advances in computation, sensor, communication and networking technologies, utilization of Unmanned Aerial Vehicles (UAVs) for military and civilian areas has become extremely popular for the last two decades. Since small UAVs are relatively cheap, the focus is changing, and usage of several small UAVs is preferred rather than one large UAV. This change in orientation is dramatic, and it is resulting to develop new networking technologies between UAVs, which can constitute swarm UAV teams for executing specific tasks with different levels of intra and inter vehicle communication especially for coordination and control of the system. Setting up a UAV network not only extends operational scope and range but also enables quick and reliable response time. Because UAVs are highly mobile nodes for networking, setting up an ad-hoc network is a challenging issue, and this networking has some requirements, which differ from traditional networks, mobile ad-hoc networks (MANETs) and vehicular ad-hoc networks (VANETs) in terms of connectivity, routing process, services, applications, etc. In this paper, it is aimed to point out the challenges in the usage of UAVs as mobile nodes in an ad-hoc network and to depict open research issues with analyzing the opportunities and future works.

The possibilities of using artificial intelligence in the agricultural sector were investigated, in particular, the optimization of the analysis of the phases of vegetation of bast crops. The implementation of this task was most effective within the framework of a traditional mechanism for studying plants in the reference time of their life and through the integration of hardware and software complexes, including a client part consisting of an unmanned aerial vehicle (helicopter, airplane or combined type), photo-video recording modules and a transmission device significant data, as well as the server part, which includes a server in which a convolutional neural network and a database equipped for specific tasks function, in which information about the studied objects and their analyzed features is segmented, as well as the receiving device. The application of advances in science and technology, especially information technology, in the state sector of agriculture will significantly increase the effectiveness of solving strategic tasks in this area.

In recent years, low-altitude and low-volume plant protection operations using unmanned aerial vehicle (UAV) sprayer developed rapidly in China with the advantages of high efficiency, labour saving, high safety, high terrain adaptability, high flexibility, water and chemicals saving, and high intelligence. With the UAV application technology in field crops is becoming more and more mature, aerial spraying operations in orchards are promising and in the ascendant, but a high risk of UAV spray drift is appearing due to high working height and fine droplets sprayed in slope orchards, highlighting the necessity of the study on the spray drift characteristics of UAV chemicals application for fruit trees. Therefore, based on previous research, a novel type of measuring method of spray drift for UAV chemicals application in orchard was proposed in this study and an artificial orchard test stand (vineyard) and 3 airborne drift frame collectors were designed and built, and a set of field drift test bench was firstly used to collect aerial spray drift droplets at different downwind distances, together with ground drift collectors and canopy deposition collectors. An airborne drift index (ADX) of UAV’s spray was initially applied for quantitative analysis to compare spray drift characteristics of different models of unmanned aircrafts and variable operation parameters. Fluorescence tracer Pyranine water solution was prepared at the concentration of 0.1% as the spray liquid. Four typical types of plant protection UAV (a single-rotor oil-powered helicopter, a 6-rotor motor drone and two models of 8-rotor motor drones) equipped with conventional hollow cone nozzle ‘TR 80-0067’ and air-induction anti-drift nozzle ‘IDK 120-015’were tested in the artificial vineyard, and results of canopy deposition distribution, ground sediment drift, near-ground drift, and airborne drift were obtained and analysed, and different sampling collectors for spray drift were evaluated and compared. The results showed that: Under the environmental conditions that the nominal crosswind speed was 2.4-3.6 m/s, the temperature was 29.8-34.3 ℃ and relative humidity was 10.7%-30.6%, at the flight height of 1.5 m (3.5 m from the ground) and the speed of 2.0 m/s the air-induction nozzle IDK can significantly reduce the level of downwind spray drift of UAV, optimize the uniformity of deposition distribution and increase the effective utilization rate of chemicals; There was no significant difference in the drift characteristics of the 4 types of unmanned aircraft, and the vortex generated by the combination of the rotor’s downwash airflow and the external wind was an important factor on spray drift; Buffer zone of UAV aerial spraying operation in vineyards should be set at at least 15 m; The lower the canopy deposition rate (P 0), the larger the average average drift rate (AADR) and 90% cumulative drift distancex90% of the field drift test bench (P 0), the greater the ADX value (P 0) all indicated the higher spray drift risk, respectively; Both these sampling collectors and their evaluation index could assess the downwind drift characteristics effectively; the relationship between the UAV spray drift rate βdep% and the downwind distance x was described by the exponential function. The results of this study are expected to provide references and data supports for the R&D of UAV dedicated for orchard spraying, the formulation of standards on spray drift field measuring method for UAV orchard operations and the selection of aerial application working parameters in orchards.

The use and applications of unmanned aerial vehicles (UAVs) in geotechnical engineering is rapidly growing, leading to changes in the way that data is acquired, analyzed and processed. UAVs can reach areas previously inaccessible via ground or helicopter, while also being quickly deployed. Cameras are the current standard for data collection and 3D model creation.
 There are multiple types of UAV’s currently available. Quadcopters can take off and land in spatially constrained areas, but carry a small stabilized camera producing low quality models. Octocopters permit an increased payload, so a higher quality camera can be attached, allowing for increased model accuracy. Flight time is reduced by the additional weight. Fixed wing UAVs create higher quality photogrammetry models, and are commonly deployed over large surface areas. Transport Canada certification must be approved prior to any flights occurring for research or work. A detailed application must be created, including a flight plan and demonstration of prior flight experience.
 At the White Canyon site in B.C., a Phantom 4 Quadcopter was flown for geotechnical analysis of a complex geometry slope, which has previously been studied for several years. The terrain has occluded the data available from the ground or from permissible helicopter flight paths. Therefore, detailed information from the slope has not been previously available. The process of using a UAV to obtain these data sets, to develop a full 3D model of these areas of the slope is discussed, considering the accuracy and quality of the data available.