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Nowadays, great efforts of ongoing research are devoted to hybrid-electric propulsion technology that offers various benefits, such as reduced noise and pollution emissions and enhanced aircraft performance and fuel efficiency. The ability to estimate the performance of an aircraft in any flight situation in which it may operate is essential for aircraft development. In the current study, a simulation model was developed that allows estimating the flight performance and analyzing the mission of a fixed-wing multi-rotor Unmanned Aerial Vehicle (UAV) with a hybrid electric propulsion system (HEPS), with both conventional and Vertical Takeoff and Landing (VTOL) capabilities. The control is based on the continuous specification of pitch angle, propulsion thrust, and lift thrust to achieve the required conditions of a given flight segment. Six different missions were considered to analyze the effect of control parameters exhibiting the most influence on the UAV mission performance. An appropriate set of control parameters was selected through a multidimensional parametric study. The results show that the control parameters, if not well tuned, affect the mission performance: for example, in the deceleration transition, a longer time to reduce the cruise speed to stand still may be the result because the controller struggles to adjust the pitch angle. In addition, the implemented methodology captures the effects of transient maneuvers, unlike typical quasi-static analysis without the complexity of full simulation models.

Benefiting from the deployment flexibility and the line-of-sight (LoS) channel conditions, unmanned aerial vehicle (UAV) has gained tremendous attention in data collection for wireless sensor networks. However, the high-quality air-ground channels also pose significant threats to the security of UAV aided wireless networks. In this paper, we propose a short-packet secure UAV-aided data collection and transmission scheme to guarantee the freshness and security of the transmission from the sensors to the remote ground base station (BS). First, during the data collection phase, the trajectory, the flight duration, and the user scheduling are jointly optimized with the objective of maximizing the energy efficiency (EE). To solve the non-convex EE maximization problem, we adopt the first-order Taylor expansion to convert it into two convex subproblems, which are then solved via successive convex approximation. Furthermore, we consider the maximum rate of transmission in the UAV data transmission phase to achieve a maximum secrecy rate. The transmit power and the blocklength of UAV-to-BS transmission are jointly optimized subject to the constraints of eavesdropping rate and outage probability. Simulation results are provided to validate the effectiveness of the proposed scheme. peerReviewed

The two-source energy balance model estimates canopy transpiration (Tr) and soil evaporation (E) traditionally from satellite partitions of remotely sensed land surface temperature (LST) and the Priestley-Taylor equation (TSEB-PT) at seasonal time with limited accuracy. The high spatial–temporal resolution spectral data collected by unmanned aerial vehicles (UAVs) provide valuable opportunity to estimate Tr and E precisely, improve the understanding of the seasonal and the diurnal cycle of evapotranspiration (ET), and timely detect agricultural drought. The UAV data vary in spatial resolution and the uncertainty imposed on the TSEB-PT outcome has thus far not being considered. To address these challenges and prospects, a new energy flux modelling framework based on TSEB-PT for high spatial resolution thermal and multispectral UAV data is proposed in this paper. Diurnal variations of LST in agricultural fields were recorded with a thermal infrared camera installed on an UAV during drought in 2018 and 2019. Observing potato as a test crop, LST, plant biophysical parameters derived from corresponding UAV multispectral data, and meteorological forcing variables were employed as input variables to TSEB-PT. All analyses were conducted at different pixelation of the UAV data to quantify the effect of spatial resolution on the performance. The 1 m spatial resolution produced the highest correlation between Tr modelled by TSEB-PT and measured by sap flow sensors (R2 = 0.80), which was comparable to the 0.06, 0.1, 0.5 and 2 m pixel sizes (R2 = 0.76–0.78) and markedly higher than the lower resolutions of 2 to 24 m (R2 = 0.30–0.72). Modelled Tr was highly and significantly correlated with measured leaf water potential (R2 = 0.81) and stomatal conductance (R2 = 0.74). The computed irrigation requirements (IRs) reflected the field irrigation treatments, ET and conventional irrigation practices in the area with high accuracy. It was also found that using a net primary production model with explicit representation of temperature influences made it possible to distinguish effects of drought vis-a-vis heat stress on crop productivity and water use efficiency. The results showed excellent model performance for retrieving Tr and ET dynamics under drought stress and proved that the proposed remote sensing based TSEB-PT framework at UAV scale is a promising tool for the investigation of plant drought stress and water demand; this is particularly relevant for local and regional irrigations scheduling. info:eu-repo/semantics/publishedVersion

The purpose of this work is the analysis of the power supply system of unmanned aerial vehicle. One of the most important tasks of this system is to ensure the smallest possible losses in order to achieve greater endurance of the aircraft, which means – the ability to complete the mission. The presence of an inactive component of consumed power obviously reduces the efficiency of the entire unmanned aerial vehicle. Considering also that due to the influence of wind, speed changes and other factors, the power system spends a significant amount of time in the transition mode, the impact of this phenomenon becomes even more significant. Thus, the phenomenon of the occurrence of exchange power in the power supply system of an unmanned aerial vehicle is analyzed. One of the most common solutions for unmanned aerial vehicles is the use of a BLDC motor, which is a further development of DC motors and was created with the aim of improving their basic characteristics. This type of engine has gained its popularity due to numerous advantages: high reliability, efficiency, speed and others. The principles of control of the BLDС engine are given. The unmanned aerial vehicle power supply system, built on the basis of a buck converter and a bridge inverter, was analyzed. An equivalent circuit of the converter is built, taking into account the losses in the electric circuit. On its basis the relations for determining the value of exchange power in the power supply system are derived. With the help of these expressions, it is possible to determine the value of the exchange energy at an arbitrary time interval in the real power supply system of the aircraft. A model of the power supply system of an unmanned aerial vehicle with a BLDC engine was built in the Matlab Simulink software environment. A time diagram is obtained, on the basis of which it is possible to draw a conclusion about the content of exchange power in the converter circuit. To minimize this phenomenon, it is necessary to develop a compensation system or an intelligent control system. Метою даної роботи є аналіз системи електроживлення безпілотного літального апарату. Одне з найважливіших завдань цієї системи – забезпечити якомога менші втрати, для досягнення більшої витривалості літака, а значить – здатності виконати місію. Наявність неактивної складової споживаної потужності явно знижує ефективність всього безпілотного літального апарату. Враховуючи також, що через вплив вітру, зміни швидкості та інших факторів енергосистема проводить значну кількість часу в перехідному режимі, вплив цього явища стає ще більш значним. Таким чином, проаналізовано явище виникнення обмінної потужності в системі живлення безпілотного літального апарату. Одним із найпоширеніших рішень для безпілотного літального апарату є використання двигуна BLDC, який є подальшим розвитком двигунів постійного струму і створений з метою покращення їх основних характеристик. Цей тип двигуна отримав свою популярність завдяки численним перевагам: високим надійності, коефіцієнта корисної дії, швидкості та іншим. Наведено принципи керування двигуном BLDC. Проаналізовано систему живлення безпілотного літального апарату, побудовану на основі понижувального перетворювача та мостового інвертора. Побудована еквівалентна схема перетворювача з урахуванням втрат в електричному колі. На її основі виведено співвідношення для визначення величини обмінної потужності в системі електропостачання. За допомогою цих виразів можна визначити величину обмінної енергії на довільному інтервалі часу в реальній системі живлення літака. У програмному середовищі Matlab Simulink побудовано модель системи електроживлення безпілотного літального апарату з BLDC двигуном. Отримано часову діаграму, на підставі якої можна зробити висновок про вміст обмінної потужності в схемі перетворювача. Щоб мінімізувати це явище, необхідною є розробка системи компенсації або інтелектуальної системи керування.

Nowadays, the unmanned aerial vehicle (UAV) has a wide application in transportation. For instance, by leveraging it, we are able to perform accurate and real-time vehicle speed detection in an IoT-based smart city. Although numerous vehicle speed estimation methods exist, most of them lack real-time detection in different situations and scenarios. To fill the gap, this paper introduces a novel low-altitude vehicle speed detector system using UAVs for remote sensing applications of smart cities, forging to increase traffic safety and security. To this aim, (1) we have found the best possible Raspberry PI’s field of view (FOV) camera in indoor and outdoor scenarios by changing its height and degree. Then, (2) Mobile Net-SSD deep learning model parameters have been embedded in the PI4B processor of a physical car at different speeds. Finally, we implemented it in a real environment at the JXUST university intersection by changing the height (0.7 to 3 m) and the camera angle on the UAV. Specifically, this paper proposed an intelligent speed control system without the presence of real police that has been implemented on the edge node with the configuration of a PI4B and an Intel Neural Computing 2, along with the PI camera, which is armed with a Mobile Net-SSD deep learning model for the smart detection of vehicles and their speeds. The main purpose of this article is to propose the use of drones as a tool to detect the speeds of vehicles, especially in areas where it is not easy to access or install a fixed camera, in the context of future smart city traffic management and control. The experimental results have proven the superior performance of the proposed low-altitude UAV system rather than current studies for detecting and estimating the vehicles’ speeds in highly dynamic situations and different speeds. As the results showed, our solution is highly effective on crowded roads, such as junctions near schools, hospitals, and with unsteady vehicles from the speed level point of view.

During flight tests of unmanned aerial vehicles (UAVs), the assessment of individual parameters, such as: range and flight duration (spatial and temporal parameters) is associated with the involvement of a significant resource (time, space, material and technical, etc.), which often raises problematic questions regarding their implementation. At the same time, in most cases, the customer usually puts forward fundamental and clear requirements to ensure the required range and duration of the flight. These indicators generally characterize the capabilities of complexes to perform tasks as intended. However, during the conducted tests, for a number of complexes, they were not fully evaluated (confirmed), including due to unfavorable conditions for conducting tests, as well as the presence of space and time limitations, first of all, the imperfection of the existing testing facilities. Given the above, the article substantiates, builds and analyzes the practical implementation, based on the results of a flight experiment, of a methodological approach to the operational assessment of certain flight characteristics, primarily the range and duration of flight during UAV flight tests. At the same time, an increase in the reliability of the data obtained is achieved through the use of the proposed complex indicator and savings in material and time resources due to the optimization of the program of the relevant test flights. The previously proposed complex indicator - the coefficient of technical perfection of the UAV, which simultaneously takes into account the perfection of the design, aerodynamic layout and efficiency of the power plant, allows to verify the reliability of the values of the parameters of the maximum range and duration of the UAV flight obtained during flight tests The theoretical and practical calculation (during a flight experiment) of the coefficient of technical perfection of a UAV with an electric propulsion system based on the experimentally obtained characteristics of the maximum range and duration of flight is presented and compared. В ході проведення льотних випробувань безпілотних літальних апаратів (БпЛА), оцінка окремих параметрів, таких як: дальність та тривалість польоту (просторово-часові параметри) пов’язана із залученням значного ресурсу (часового, просторового, матеріально-технічного, тощо), що часто викликає проблемні питання щодо їх реалізації. При цьому, у більшості випадків замовником, як правило висуваються принципові та чіткі вимоги щодо забезпеченням необхідних дальності та тривалості польоту. Дані показники загалом характеризують можливості комплексів щодо виконання завдань за призначенням. Проте, в ході проведених випробувань, для ряду комплексів, вони не були повністю оцінені (підтверджені), у тому числі внаслідок несприятливих умов проведення випробувань, а також наявності просторово-часових обмежень, перш за все – недосконалості наявної полігонно-випробувальної бази. Враховуючи зазначене, у статті обґрунтовано, побудовано та проведено аналіз практичної реалізації, на підставі результатів льотного експерименту, методичного підходу до оперативної оцінки окремих льотно-технічних характеристик, в першу чергу, дальності та тривалості польоту під час льотних випробувань БпЛА. При цьому, досягається підвищення достовірності отриманих даних за рахунок застосування запропонованого комплексного показника та економія матеріально часового ресурсу завдяки оптимізації програми відповідних тестових польотів. Раніш запропонований комплексний показник - коефіцієнт технічної досконалості БпЛА, що одночасно враховує досконалість конструкції, аеродинамічної компоновки та економічності силової установки дозволяє здійснити перевірку достовірності отриманих, в ході льотних випробувань, значень параметрів максимальної дальності та тривалості польоту БпЛА Наведено та порівняно теоретичний та практичний розрахунок (в ході льотного експерименту) коефіцієнту технічної досконалості БпЛА з електричною силовою установкою за експериментально отриманими характеристиками максимальних дальності та тривалості польоту.

Dangers associated with poor air quality are driving deployments of air quality monitoring technology worldwide. Having a comprehensive understanding of the health effects of pollutants requires understanding both the distribution and dispersion of pollutants in the environment, but currently this information is highly difficult to capture. This article presents a vision for city-scale air pollution monitoring that uses unmanned aerial vehicles (UAVs) to complement current ground and infrastructure-based measurements with a vertical profile of pollutants. We highlight the key requirements and research challenges, demonstrate the benefits UAVs bring through measurements from an industrial and a residential location, and establish a research roadmap for the path forward.

Quadcopters have unstable systems, and one of the main reasons for the irregularity of their systems may be the behavior of the output of certain types of control units. But the development that an event in the control methods made the control of these systems very effective to achieve the maximum stability required. Examples of methods with modern controllers we mention here are the linear quadratic regulator (LQR) controller, Besides the (MPC) model predictive controller, there is also the integral proportionally derivative (PID)which we worked on developing in this research. This paper aims to deal with compensation for position tracking error of quadrotor. To address this problem, we designed an adaptive PID controller that enhances the tracking performance and tests the proposed controller on two different trajectories against the performance of the normal PID controller. Through the simulation results using MATLAB the suggested strategy was shown to be effective in lowering the errors associated tracking of intended trajectories in X and Y orientations.

The emergence of internet-of-things (IoT) devices in homes and industry, has resulted in the current and future generation of wireless communications facing unique challenges in spectral efficiency, energy efficiency, and massive connectivity issues. Non-orthogonal multiple access (NOMA) has been proposed as a viable solution to address these challenges as it offers low-latency, spectral efficiency, and massive connectivity capabilities, which are key requirements in upcoming next-generation networks. In addition, another technology that has emerged as a solution to spectral efficiency and coverage is an unmanned aerial vehicle (UAV). Therefore, the combination of UAVs with NOMA has great potential to minimize the challenges and maximize the benefits. Specifically, we investigate the outage performance of the NOMA-UAV network over Nakagami-m channel fading. To this end, we derive a closed-form outage performance metric. The formulated framework is validated using simulations to verify the effectiveness of the proposed solution.

This work is devoted to the development of a system for automatic determination of the flight task for unmanned aerial vehicles. To implement such a system, the QT framework (a library of C++ classes and a set of tools for creating cross-platform applications) was used. It is proposed to introduce forecasting and routing modules into the system of automated determination of the flight task. An interface is developed for building a flight task that can be used to download, track key metrics from the unmanned aerial vehicles, and adjust the mission of the flight task. Advanced QT/Qml frameworks were used, which will allow the software product to be used on different operating systems, which will add flexibility in the use of system components. Дану роботу присвячено розробці системи автоматичного визначення польотного завдання для безпілотних літальних апаратів. Для реалізації такої системи використовувався фреймворк QT (бібліотека класів C++ та набір інструментального програмного забезпечення для створення крос-платформних додатків). До складу системи автоматизованого визначення польотного завдання запропоновано ввести модулі прогнозування та маршрутизації. Розроблено інтерфейс для побудови польотного завдання, яке може бути використане для завантаження, відстеження ключових метрик із безпілотного літального апарата та коригування місії польотного завдання. Було використано передові фреймворки QT/Qml, що дозволить використовувати програмний продукт на різних операційних системах, що додасть гнучкості у використанні системних компонентів. Дану роботу присвячено розробці системи автоматичного визначення польотного завдання для безпілотних літальних апаратів. Для реалізації такої системи використовувався фреймворк QT (бібліотека класів C++ та набір інструментального програмного забезпечення для створення крос-платформних додатків). До складу системи автоматизованого визначення польотного завдання запропоновано ввести модулі прогнозування та маршрутизації. Розроблено інтерфейс для побудови польотного завдання, яке може бути використане для завантаження, відстеження ключових метрик із безпілотного літального апарата та коригування місії польотного завдання. Було використано передові фреймворки QT/Qml, що дозволить використовувати програмний продукт на різних операційних системах, що додасть гнучкості у використанні системних компонентів.

With the widespread use of unmanned aerial vehicles (UAVs) in life, the real-time recognition of UAVs has become an important issue. The authors of this paper mainly studied the application of the random forest (RF) algorithm in the outdoor real-time recognition of UAVs. Mel-Frequency Cepstral Coefficient (MFCC) features were extracted from sound signals firstly, and then the RF method was combined with weighted voting to obtain the improved random forest (IRF) method to identify UAV sounds and environmental sounds. An experimental analysis was conducted. The modeling time of the IRF method increased by 9.52% compared with the RF method, and the recognition rate of the IRF method decreased with the increase of the distance from the microphone; however, the recognition rate of the IRF method was always higher than that of the RF method, and the recognition rate of the IRF method for the mixed samples was always higher than 90%. When the distance was 10 m, the IRF method still had a recognition rate of 91.29%. The experimental results verify the effectiveness of the IRF method for the outdoor real-time recognition of UAVs and its practical application feasibility.

In this study, to reduce the average symbol error rate, and improve coverage and reliability of unmanned aerial vehicles (UAVs) to ground communication systems. In this case, we propose a reconfigurable intelligent surfaces (RISs) assisted for UAV to ground communication scheme, where radio frequency (RF) signal generator sends an unmodulated carrier signal from UAVs to the RIS. At reconfigurable intelligent surface, the RIS modulates each signal, and RIS is as a signal generator. We carry out a performance analysis of UAV-to-ground communication systems with RIS-assisted and without RIS for subcarrier quadrature amplitude modulation(SC-QAM) technique. The analytical expressions of average symbol error rare (ASER) and average channel capacity (ACC) is derived. From the results, it is show that with RIS assisted can effectively improve the reliability and coverage of the UAVs to ground communication systems.

The combination between two remote surveying methods is presented herein as a pioneering approach for landslide airborne monitoring. The survey of an active landslide by UAV-based RGB photogrammetry and infrared thermography, sided by the knowledge of the field condition, allowed increasing the scientific experience on the remote sensing of slope instability phenomena by analyzing multiple aspects related to the evolution of key slope features. In this research, the state and distribution of activity of a landslide was monitored by matching data arising from three-dimensional models of the slope, built by exploiting the aerial RGB photogrammetric technology, and thermal outcomes, resulting from the airborne application of infrared thermography principles. In this frame, thermal anomalies detected during different monitoring campaigns allowed recognizing peculiar features along the unstable slope that could be related to specific kinematic elements involved in the landslide activity. Forming cracks, developing scarps, wet terrain portions, and loose material are some of the elements that could be located by integrating thermal outcomes with Digital Surface Models of the slope. Thanks to the different thermal behavior of such elements, strengthened herein by a novel approach of thermal data processing (i.e. the study of thermal slope profiles), the lateral and retrogressive evolution of the studied movement was first hypothesized and then verified in field. Achieved results show that the location of thermal anomalies well corresponds to field structures, which sometimes are hardly detectable by in situ or RGB surveys, thus suggesting the high potential of the methodological approach developed for this study. The scientific validity of presented data gains relevance thanks to the positive field validation. This paves the way to further studies aimed at implementing the infrared aerial survey of landslides, which surely could bring benefits to practical applications in terms of survey speed and spatial coverage, especially in areas characterized by bad field logistics.

The classification of semantic segmentation-based unmanned aerial vehicle (UAV) application based on the datasets used in this work and the necessary data preprocessing steps for the optimization and implementation of the models are also involved. The optimization of the various models was done using the evaluation metrics and loss functions because deep neural networks (DNNs) are just about writing a cost function and its subsequent optimization. convolutional neural network (CNN) is a common type of artificial neural network (ANN) that has found application in numerous tasks, such as image and video recognition, image classification, recommender systems, financial time series, medical image analysis, and natural language processing. CNN is developed to automatically and adaptively learn spatial feature hierarchies via backpropagation using numerous building blocks, such as pooling, convolution, and fully connected layers. The result of identification was excellent. The image segmentation was detected and comprehend the actual components of an image down to the pixel level. The result created an entire image segmentation masks with instances using the new label editor in the label box.

In order to exploit seasonally favourable habitats for feeding and breeding, humpback whalesMegaptera novaeangliaeundertake one of the longest migrations in the animal kingdom. Stored energy is crucial for a successful migration, but few studies have investigated the relationship between migration timing and body condition in baleen whales. Using unmanned aerial vehicles, we quantified the body condition of east Australian humpback whales. We collected data on 513 individuals (48 calves, 166 juveniles, 251 adults, and 48 lactating females) during their northbound and southbound migrations between June and October 2020. For adults and juveniles, we explored the loss of body condition between migration direction (north versus south) as well as the relationship of migration timing (day of year) and body condition. We found a significant loss in body condition between the northbound and southbound migrations for both adults (9.8%) and juveniles (18.3%). However, migration timing did not influence body condition for either reproductive class. Cow/calf pairs were analysed using relative calf length (percentage of maternal length) as a proxy for days postpartum. We found a positive curvilinear relationship between migration timing and calf body condition. However, lactating females showed no relationship between migration timing and body condition. Whilst body condition is important for capital breeding whales, the lack of a correlation found for adults and juveniles suggests that body condition is not the main driver of migration timing from feeding or breeding grounds. However, calf body condition may be a significant factor for the migration timing of cow/calf pairs.

UAVs or drones as an alternative solution to providing high-quality Internet service in difficult terrain are environmentally friendly and do not consume electricity during the day as is the case with communication towers. But the developers of the network face difficulties in the drone communication system associated with the need to take into consideration unpredictable weather conditions and terrain, as well as the short life of the drone's batteries. Therefore, the object of this study is the process of managing UAV traffic through the use of gNB-IoT in 5G. The possibility of using a mobile UAV repeater during traffic management using radio resources (RR), radio access network (RAN), the infrastructure with broadcasting tools and dynamic connection using MU-MIMO modulation is shown. The use of these tools makes it possible to connect the drone to the wired base network from the provider and then restore the radio frequency signal and broadcast to another coverage area where this subscriber does not have network coverage, use the channel quality indicator (CQI) representation as a QoE function. Undoubtedly, traffic management is the process of obtaining information about traffic control from one endpoint to another, which confirms the reliability and management of data transmission. Meanwhile, drone traffic management can be used to reduce time delays and remove network interference by relying on Internet of Things programs that use NB-5G technology. The UAV's traffic management improvement process uses a proposed algorithm to generate dynamic flow data management to enhance traffic processing of flow control in the IoT

Cracks in constructions may result in negative consequences in terms of expenditure and safety. This in turn highlights the importance of finding ways to detect these cracks easily and effectively. Hence, technological advances play significant role in enabling effective and innovative ideas, such as the use of autonomous drones and artificial intelligence solutions. In this research, we utilise a type of drone called an unmanned aerial vehicle, equipped with a high-speed camera that can capture images of cracks in buildings, and pass the information to the system. We utilised a dataset that has images collected from different Middle East Technical University (METU) campus buildings with various concrete surfaces (with and without cracks). The crack detection approach uses statistical measures and a support vector machine that prevents overfitting, attains a good rate of accuracy, tackles problems in real-time, and can train a model when a small dataset exists. The combination of an unmanned aerial vehicle, artificial intelligence, and digital image processing gives excellent results. Performance metrics reported for seven rounds of experiments showed rates of accuracy in detection ranging from 83.3–100% (with 100% achieved in two rounds). This demonstrates the effectiveness of our proposed detection system in detecting cracks in constructions.

This study examines the use of leaf area index (LAI) to inform variable-rate irrigation (VRI) for irrigated alfalfa (Medicago sativa). LAI is useful for predicting zone-specific evapotranspiration (ETc). One approach toward estimating LAI is to utilize the relationship between LAI and visible vegetation indices (VVIs) using unmanned aerial vehicle (UAV) imagery. This research has three objectives: (1) to measure and describe the within-field variation in LAI and canopy height for an irrigated alfalfa field, (2) to evaluate the relationships between the alfalfa LAI and various VVIs with and without field average canopy height, and (3) to use UAV images and field average canopy height to describe the within-field variation in LAI and the potential application to VRI. The study was conducted in 2021–2022 in Rexburg, Idaho. Over the course of the study, the measured LAI varied from 0.23 m2 m−2 to 11.28 m2 m−2 and canopy height varied from 6 cm to 65 cm. There was strong spatial clustering in the measured LAI but the spatial patterns were dynamic between dates. Among eleven VVIs evaluated, the four that combined green and red wavelengths but excluded blue wavelengths showed the most promise. For all VVIs, adding average canopy height to multiple linear regression improved LAI prediction. The regression model using the modified green–red vegetation index (MGRVI) and canopy height (R2 = 0.93) was applied to describe the spatial variation in the LAI among VRI zones. There were significant (p < 0.05) but not practical differences (

Geomorphometry research largely relies on 3-dimentional land surface models, especially for natural landforms with steep slopes and large complex artificial structures. The traditional Digital Elevation Model (DEM) encounters difficulties in representing detailed features in such scenes. To address this issue, this paper introduces a concept of a “true 3D surface” and proposes a multiple Unmanned Aerial Vehicle (UAV) collaborative method for high-quality reconstruction of a true 3D surface. We established an evaluation model of scene reconstruction based on the Multi-View Stereo (MVS) modeling rules, and utilized the Fibonacci approach to select the optimal viewpoints. We also adopted the method of finding the next-best-view for each UAV in turn to extend the multi-UAV trajectory. This method involved trade-offs between energy consumption and scene reconstruction to enhance the contribution of viewpoints for improved reconstruction quality of the true 3D surface. Real flight experiments were conducted over the Wuhan University Teaching Building and the Fangshiwan Bridge in Chibi, which revealed a significant improvement in the completeness and precision of the true 3D surface constructed by our proposed method when compared to vertical photography techniques.

[ES] En el presente trabajo se explora posibles soluciones a dos hechos correlacionados que podrían comprometer hasta cierto punto nuestro futuro. Por un lado, el crecimiento de la flota de aeronaves pequeñas en los próximos años, ya sean tripuladas o no, es una realidad. El acceso a estas aeronaves por parte de un público cada vez más mayoritario crece año a año y, al mismo tiempo, los fabricantes adaptan sus aeronaves a misiones que hace unos años no éramos capaces de contemplar. Por otro lado, y por desgracia, el cambio climático también es una realidad que no solo compromete nuestro futuro, sino también nuestro presente. Hoy en día la alerta climática es y debe ser elevada, y si no encontramos soluciones que ayuden a paliar este problema, la vida en el planeta podría cambiar irremediablemente para peor. Ambos hechos se encuentran implícitamente relacionados. La fabricación y operación de vehículos contribuye notablemente a aumentar la huella de carbono. Por lo tanto, el aumento de flota en los próximos años puede tener un impacto notablemente negativo en las emisiones contaminantes y gases de efecto invernadero globales. Es por ello por lo que organismos oficiales y sectores de desarrollo científico y tecnológico impulsan la investigación de posibles soluciones. Este trabajo intenta poner su grano de arena para minimizar este problema común. Se propone la utilización de múltiples tecnologías con el objetivo de disminuir el combustible requerido por aeronaves de 25kg al despegue, y de esta forma, disminuir las emisiones asociadas a su operación. Las tecnologías aplicadas son la hibridación eléctrica en serie, la propulsión eléctrica distribuida y la ingestión de capa límite. Por separado, estas tecnologías han demostrado múltiples ventajas, especialmente en términos de mejora propulsiva y aerodinámica de las aeronaves, lo que repercute directamente en el consumo de combustible. Sin embargo, este trabajo propone la utilización simultánea de todas ellas con el objetivo de disminuir aún más el consumo de combustible y, por tanto, las emisiones contaminantes y gases de efecto invernadero. Para ello, tras estas páginas se eligen los parámetros principales de esta aeronave y se acompaña de un exhaustivo análisis del comportamiento fluidodinámico. Con la comprensión de su comportamiento, es posible optimizar la selección de sus componentes, de forma que se obtienen mejoras importantes en el consumo de combustible. Este ahorro de combustible se muestra en comparación con aeronaves similares en tamaño y peso, pero que no incluyen estas tecnologías, logrando para un mismo alcance un ahorro del 16% del peso del combustible. La realización de este trabajo se centra en el empleo de herramientas computacionales apoyándose sobre todo en la dinámica de fluidos computacional (CFD). Esta herramienta principal se verá complementada con el uso de descomposición modal para realizar los análisis y de la creación de una base de datos que ayude a crear modelos rápidos útiles en futuros diseños preliminares y conceptuales de aeronaves de este tipo., [CA] En aquest treball s'exploren possibles solucions a dos fets correlacionats que podrien comprometre d'alguna manera el nostre futur. Per un costat, el creixement de la flota d'aeronaus de xicoteta dimensió en el futur, tant tripulades com no tripulades, és una realitat. L'accés a aquestes aeronaus per part d'un públic cada cop més majoritari creix any rere any i, al mateix temps, els fabricants adapten les aeronaus a feines que anys enrere no eren capaços d'assolir. Per l'altre costat, malauradament, el canvi climàtic és un fet que compromet tant el nostre futur com el nostre present. Hui en dia l'alerta climàtica és elevada i, si no trobem solucions per a pal·liar aquest problema la vida al nostre planeta, podria canviar irremeiablement a pitjor. Ambdós fets es troben implícitament relacionats. La fabricació i l'operació de vehicles contribueix notablement a augmentar l'empremta de carboni. Per tant, l'increment de flota en els pròxims anys pot tindre un efecte negatiu molt notable en les emissions contaminants i gasos d'efecte hivernacle globals. És per això que organismes oficials i sectors de desenvolupament científic i tecnològic impulsen la investigació de possibles solucions. Aquest treball intenta aportar el seu granet de sorra per minimitzar aquest problema comú. Es proposa la utilització de múltiples tecnologies amb l'objectiu de reduir el combustible emprat per aeronaus de fins a 25kg i, per tant, disminuir les emissions associades a la seua operació. Les tecnologies aplicades són la hibridació elèctrica en sèrie, la propulsió elèctrica distribuïda i la ingestió de capa límit. Separadament, aquestes tecnologies han demostrat múltiples avantatges, especialment en termes de millora propulsiva i aerodinàmica de les aeronaus, repercutint directament en el consum de combustible. No obstant, aquest treball proposa la utilització simultània de totes elles amb l'objectiu de reduir encara més el consum de combustible i, per tant, les emissions contaminants i gasos d'efecte hivernacle. Per fer-ho, en les darreres pàgines es trien els paràmetres principals de l'aeronau i s'acompanyen d'una exhaustiva anàlisi del comportament de la dinàmica de fluids. Comprenent el seu comportament, és possible optimitzar la selecció dels seus components, de manera que s'obtenen millores importants en el consum de combustible. L'estalvi de combustible es mostra en comparació amb aeronaus similars en mida i pes, però que no inclouen aquestes tecnologies, aconseguint per a un mínim abast un estalvi del 16% del pes del combustible. La realització d'aquest treball es centra en l'ús d'eines computacionals recolzant-se sobretot en la dinàmica de fluids computacional (CFD). Aquesta eina principal es veurà complementada amb l'ús de descomposició modal per a elaborar les anàlisis i de la creació d'una base de dades que ajude a crear models ràpids i útils en futurs dissenys conceptuals i preliminars d'aeronaus d'aquest tipus., [EN] The present work explores possible solutions to two correlated events that could compromise our future to some extent. On the one hand, the growth of the fleet of small aircraft in the coming years, whether manned or not, is a reality. Access to these aircraft by an increasing majority of the public grows year after year and at the same time, manufacturers adapt their aircraft to missions that we could not contemplate a few years ago. On the other hand, and unfortunately, climate change is also a reality that compromises not only our future but also our present. Today the climate alert is and must be elevated. If we do not find solutions that help alleviate this problem, life on the planet could irremediably change for the worse. Both facts are implicitly related. The manufacture and operation of vehicles contribute significantly to increasing the carbon footprint, so the increase in the fleet in the coming years may have an extremely negative impact on global polluting and greenhouse gas emissions. That is why official organizations and scientific and technological development sectors promote research for possible solutions. This work tries to do its bit to minimize this common problem. Multiple technologies are proposed to reduce the fuel required by 25kg aircraft at takeoff and, thus, reduce the emissions associated with their operation. The applied technologies are electric series hybridization, distributed electric propulsion, and boundary layer ingestion. Separately, these technologies have shown multiple advantages, especially in terms of improving aircraft propulsion and aerodynamics, which directly affects fuel consumption. Nevertheless, this work proposes the simultaneous use of all of them to reduce fuel consumption further and, therefore, polluting and greenhouse gas emissions. To do this, after these pages, the main parameters of this aircraft are chosen and accompanied by an exhaustive analysis of the fluid dynamic behavior. With an understanding of its behavior, it is possible to optimize its components' selection so that significant fuel consumption improvements are obtained. This fuel saving is shown in comparison with similar aircraft in size and weight, but that does not include these technologies, achieving a saving of 16% of fuel weight for the same range. This work's conduction focuses on employing computational tools mainly based on computational fluid dynamics (CFD). This primary tool will be complemented by the use of modal decomposition to carry out the analyses, and the creation of a database that will help create quick models useful in future conceptual and preliminary designs of this type of aircraft., The respondent would like to acknowledge the financial support received through contract FPI-UPV PREDOCFD/19 of Subprograma 2 of Universitat Politècnica de València

Turkey increasingly sees itself as mid-tier power capable of projecting influence from beyond its near periphery. This research examines the motivations for Turkey’s overtures to sub-Saharan Africa within the broader context of its evolving foreign policy. It also explains how Turkey fulfills a growing role within the sub-African market with unmanned aerial vehicles (UAVs), or drones, by examining case studies of Ethiopia and Nigeria, among others. Moreover, it explores the implications—both domestic and within sub-Saharan Africa—that arise from Turkey’s use of drones as a tool of its foreign policy. Many contemporary authors look at the role of Turkey’s drone sales in the context of the last few years when Turkey initially exported drones. This thesis argues that Turkey’s drone outreach continues the evolution of Turkey's foreign policy from at least the early 2010s, and the growing sub-Saharan African market provides Turkey with new opportunities to project influence while serving domestic economic and political interests. Finally, Turkey’s rapid increase in drone sales also highlights how the security landscape of sub-Saharan Africa continues to shift. This change and Turkey’s increased involvement in the region contribute to a potentially significant, though still nascent, impact on the interests and policy of the United States across the region. Outstanding Thesis Lieutenant Commander, United States Navy Approved for public release. Distribution is unlimited.

In January 2021, the DOD released its first Counter-Small Unmanned Aircraft Systems Strategy to address the growing risk to military personnel, facilities, and assets posed by the rapid technological advancement and proliferation of sUAS. Existing counter-drone capabilities—heavily reliant on electronic warfare to disrupt the communication link between user and device—no longer address an evolving threat that includes autonomous drones, COTS technology, and an increasing number of drones in the airspace that can overwhelm a C-sUAS operator. To counter the increasingly complex small drone threat, the Army-led Joint Counter-sUAS Office is pursuing materiel and non-materiel solutions for its new system-of-systems approach. One vexing C-sUAS challenge involves radar detection systems discriminating some sUAS from other flying objects, like birds, due to their comparable size, slow movement, and low altitude. Inaccurate or inefficient sUAS classification using radar data can be a force protection threat due to the limited number of electro-optical sensors and human operators for classification at-scale. This thesis uses bird and drone radar track data from two different training environments to explore hidden structure in the data, develop independent unsupervised and supervised learning models using the two datasets, and experiment with data sampling and feature engineering to improve upon model robustness to different environments and dynamic environmental conditions. Lieutenant Colonel, United States Army Approved for public release. Distribution is unlimited.

This study proposes a ducted-fan flight array (DFA) system that can change the array based on the mission environment and validate the feasibility through ground and flight tests. This DFA can carry out normal formation flight as separated UAV members and can also cooperate as a single entity by physical connection. The ducted-fan unmanned aerial vehicle (UAV) is manufactured in-house and equipped with a connected surface and an assembly device on the side to perform connection and separation tasks. Moreover, the control system was designed using an open-source autopilot environment, and the communication environment for multi-UAV flight was constructed using the Robot Operating System (ROS). Then, ground and preliminary experimental tests verified the feasibility and performance of the DFA system for connected and separated flight.

This paper models an operation problem of an unmanned aerial vehicle for the emergency medical service (UEMS) system. The model is set up as a location-allocation problem. The coverage distance and capacity of the UEMS facility are modeled as functions of UAVs assigned. The allocation of the demand point is constrained by the variable coverage distance of each facility. The robust optimization approach is used over the cardinality-constrained uncertain demand, which leads to a nonlinear optimization problem. The UEMS location-allocation problem (ULAP) is reformulated to a solvable problem. An extended formulation and corresponding branch-and-price (B&P) algorithm are also proposed, which strengthen the linear programming relaxation bound. The subproblem of the B&P algorithm is defined as a robust disjunctively constrained integer knapsack problem. Two solution approaches of mixed-integer linear programming reformulation and decomposed dynamic programming are designed for the subproblem. To provide time-efficient solutions for large-scale problems, a restricted master heuristic (RMH) is proposed based on the extended formulation. In computational experiments, the B&P algorithm provided a strong lower bound, and the RMH could find an effective feasible solution within an applicable computation time.

During the design and construction of new products, it is necessary to evaluate their effectiveness and technical thoroughness already at the preliminary design stage. For unmanned aerial vehicle systems (hereinafter referred to as UAVs), one of the areas of such assessment can be the ratio of the overall tactical and technical requirements to the estimated flight and technical properties of the prospective model to the characteristics of the best analogues. However, such estimates are associated with a high degree of uncertainty in the early stages of UAV design. There is a question of a priori evaluations with the use of multicriteria approaches arises. At the same time, the use of multicriteria methods of evaluation of complex technical systems, such as UAVs requires the use of large amounts of data with significant time consumption, so the search for comprehensive evaluation indicators, as proposed in this article, is considered to be relevant. This article deals with the complex evaluation of the technical efficiency of unmanned aerial vehicles equipped with turbojet propulsion system (hereinafter — turbojet). For this purpose, the composition and content of the relevant methodological apparatus for assessing efficiency and a comprehensive indicator of technical excellence of unmanned aerial vehicles with turbojet engines are substantiated. In contrast to existing approaches, the obtained comprehensive indicator allows to evaluate UAVs on the minimum necessary information about its flight data, which allows to use the proposed methodological apparatus for assessing UAVs already at the design stages. In accordance with the proposed methodological apparatus, the actual comparative assessment of the UAV group with turbojets was carried out. A differential scale for evaluating the technical perfection of UAVs has been constructed. This approach, in the opinion of the authors, will allow to increase the reliability of comparative evaluations of UAVs with turbojets for the minimum required amount of output data. При розробці та створені нових зразків виникає необхідність оцінки їх ефективності та технічної досконалості вже на етапі попереднього проектування. Для безпілотних авіаційних комплексів (далі – БпАК) одним із напрямків такої оцінки може бути співвідношення обґрунтованих тактико-технічних вимог та очікуваних льотно-технічних властивостей перспективного зразка із характеристиками кращих аналогів. Проте, такі оцінки пов’язані із високим ступенем невизначеності на ранніх стадіях проєктування безпілотних літальних апаратів БпЛА. Виникає питання апріорних оцінок із використанням багатокритеріальних підходів. При цьому, застосування багатокритеріальних методів оцінки складних технічних систем, як БпАК вимагає застосування великих масивів даних із суттєвими витратами часу, тому пошук та застосування комплексних показників оцінки, як пропонується у статті, вважається актуальним. У статі розглянуто питання комплексної оцінки технічної досконалості безпілотних літальних апаратів, що оснащенні турбореактивною силовою установкою (далі – ТРД). Для цього обґрунтовано склад та зміст відповідного методичного апарату з оцінки економічності та комплексний показник технічної досконалості БпЛА із ТРД. На відміну від існуючих підходів, отриманий комплексний показник keр, дозволяє здійснювати оцінку БпЛА за мінімально необхідною інформацією про його льотно-технічні данні, що дозволяє застосовувати запропонований методичний апарат для оцінки БпАК вже на етапах його проектування. Відповідно до запропонованого методичного апарату проведено фактичну порівняльну оцінку групи БпЛА з ТРД. Побудовано диференційну шкалу оцінки технічної досконалості БпЛА. Такий підхід, на думку авторів, дозволить підвищити достовірність порівняльних оцінок БпЛА з ТРД за мінімально необхідним масивом вихідних даних.

Identifying objects from drone images is a state-of-the-art task for artificial neural networks. Since drones are always moving at different altitudes, the scale of the object varies greatly, making it difficult to optimize the networks. Moreover, flying at high speeds and low altitudes leads to blurred images of densely populated objects during movement, which is a problem when solving the problem of recognizing and classifying small sized objects. This paper addresses the above problem solutions and solves them by applying an additional prediction model to identify objects of different scales. We also modify the loss function to penalize larger objects more and vice versa to encourage recognition of smaller objects. To achieve improvements, we use advanced techniques such as multiscale testing, image blurring, object rotation, and data distortion. Experiments with a large data set show that our model has good performance in drone images. Compared to the baseline model (YOLOv5), our model shows significant improvements in object recognition and classification. Идентификация объектов по изображениям дронов – одна из самых современных задач для искусственных нейронных сетей. Поскольку дроны всегда перемещаются на разной высоте, масштаб объекта сильно различается, что затрудняет оптимизацию сетей. Более того, полет на больших скоростях и малых высотах приводит к нечеткому изображению густонаселенных объектов во время движения, что является проблемой при решении задачи распознавания и классификации небольших по размеру объектов. В данной статье рассматриваются решения вышеуказанных проблем и они решаются путем применения дополнительной модели прогнозирования для идентификации объектов разного масштаба. Мы также модифицируем функцию потерь, чтобы более крупные объекты ставить в невыгодное положение и наоборот, чтобы стимулировать распознавание более мелких объектов. Чтобы добиться улучшений, используются передовые методы, такие как многомасштабное тестирование, размытие изображения, поворот объекта и искажение данных. Эксперименты с большим набором данных показывают, что рассмотренная модель хорошо работает на изображениях дронов. По сравнению с базовой моделью (YOLOv5) рассмотренная модель демонстрирует значительные улучшения в распознавании и классификации объектов. Ідентифікація об’єктів із зображенням дронів – одне з найсучасніших завдань для штучних нейронних мереж. Оскільки дрони завжди переміщуються на різній висоті, масштаб об’єкта сильно варіюється, що ускладнює оптимізацію мереж. Більше того, політ на великих швидкостях і малих висотах призводить до нечіткого зображення густонаселених об’єктів під час руху, що є проблемою під час вирішення завдання розпізнавання та класифікації невеликих за розміром об’єктів. У статті розглядаються розв’язання вищевказаних проблем і вони вирішуються шляхом застосування додаткової моделі прогнозування для ідентифікації об’єктів різного масштабу. Ми також модифікуємо функцію втрат, щоб більші об'єкти ставити в невигідне становище і навпаки, щоб стимулювати розпізнавання дрібніших об'єктів. Щоб досягти покращень, використовуємо передові методи, такі як багатомасштабне тестування, розмиття зображення, поворот об’єкта та спотворення даних. Експерименти з великим набором даних показують, що розглянута модель добре працює на зображеннях дронів. Порівняно з базовою моделлю (YOLOv5) розглянута модель демонструє значні покращення у розпізнаванні та класифікації об’єктів.

The subject of the article is methods of reducing quadcopter magnetometer crosstalk by changing the design and settings of the copter to improve the quality of its work during the monitoring of ground objects. The relevance of the development is determined by the need to increase the physical safety of quadcopters when monitoring ground facilities in various industries because the magnetometer is the most noise-sensitive sensor, and its failure leads to the fall and loss of the drone. The purpose of the article is to determine the optimal design and settings of the quadcopter in terms of its physical safety and quality of work during monitoring of ground facilities in various industries. The research task is to check whether it is possible to protect the magnetometer placed inside the drone body from the power cables crosstalk by grounding, shielding and changing the initial settings of the copter, namely by changing the value of the startup power factor of the motors. Research methods are as follows: theory of automatic control, methods of optimal control and hardware design methods. Conclusions. The role of the drone magnetometer in the monitoring of ground objects has been studied. The study has shown that copters at monitoring ground objects must be equipped with a magnetometer and GPS. The magnetometer is the most sensitive to interference of all sensors. If it does not work properly, the entire drone navigation system stops working. We have carried out experimental studies of the influence of quadcopter design and settings on the quality of its magnetometer work, and hence on work of the copter as a whole. In this paper it is proposed to place a magnetometer inside the body of the drone that will increase its physical safety and simplify the design of the drone, but at the same time it will increase the coupling from the power cables of motors, so it is necessary to choose effective methods of protection. It has been tested whether it is possible to protect the magnetometer from interference from power cables when placing it inside the drone body by grounding, shielding and changing the initial settings of the copter, namely by changing the value of the startup power factor of the motors. The results of the experiments showed that to protect against the interference for magnetometer placed inside the drone body, it is necessary to combine shielding of the magnetometer and decreasing of the startup power factor of the motors.

The authors showed that it is possible to quickly collect up-to-date information on the agricultural land condition using an unmanned aerial vehicle. It was noted that the use of ground control points increases the accuracy of project measurements, helps to compare the project post-processing results with the real measurements. (Research purpose) To compare the results of standard and high-precision post-processing of aerial survey data using ground control points. (Materials and methods) Aerial photography was carried out on a 1.1- hectare breeding field. The authors used DJI Matrice 200 v2 unmanned aerial vehicle with a GNSS L1/L2 receiver and a modified DJI X4S camera, five control points sized 50 × 50 centimeters and an EMLID Reach RS2 multi-frequency GNSS receiver. The results of scientific research into the use of ground control points during aerial photography were studied. (Results and discussion) It was found out that the error of georeferencing images obtained by an unmanned aerial vehicle without control points is significantly higher during the standard data processing compared to the high-precision one. The project error when using five control points is 3.9 times higher during the standard data processing. (Conclusions) It was shown that using ground control points it is possible to improve the project measurement accuracy, as well as compare the project post-processing results with the measurements on the ground. It was detected that the high-precision monitoring enables the use of fewer ground control points. It was found out that in order to obtain data with the accuracy of 2-4 centimeters in plan and height, at least 3 ground control points need to be used during the high-precision post-processing.

The modern economy completely changed by offering to industry groups the capability to reorganize their operating processes. Nowadays we become observers of similar in scale revolutionary transformations: technologies for the use of unmanned aerial vehicles substantially modified business models and new operating conditions have been developed in various sectors from industries, agriculture to the emergency, parcel delivery or movie industry. In the very near future, clients’ enterprises from multiple sectors of the economy will recognize the first effect of the use of unmanned aerial vehicles (UAVs) in diverse fields - from commercial sectors to examining and exploring the environment or to reduce the impacts of unexpected disasters. The aim of the present review paper is to analyse the opportunities and advantages of using the application of UAVs technologies. On the other hand, not only the devices (drones) themselves are of importance, but also their wider utilization to acquire extraordinary volumes of data.

The article discusses the methodological issues of remote mapping objects of archaeological heritage using unmanned aerial vehicles. A section of the Yustyd river valley on the territory of the Kosh-Agach district of the Altai Republic was chosen as a polygon. The survey area in 2021 covered the territory of the right bank with the maximum concentration of large objects, first of all, khirgisuurs, which are distinguished by a variety of shapes and internal structures. For multispectral shooting of archaeological sites, an unmanned aerial vehicle DJI Inspire 1 (ver. 2.0) was used, a design feature of which was an additional mini-platform located in the rear of the hull. The platform was mounted for the installation of a Parrot Sequoia camera and an additional battery — a source of autonomous power supply for the camera. The process of photogrammetric processing of images was a computer automated digital processing of photographic materials with the subsequent creation of a mosaic orthomosaic. Agisoft Metashape software was chosen for photogrammetric processing of materials. The results obtained were subjected to index (thematic) processing of multispectral images based on a combination of green, red and near infrared channels. In the course of a comparative analysis of the constructed images, the following regularities were found. The MCARI index makes it possible to detect burial mounds and structural elements expressed in geometry (plan). Detection of various “anomalies” characterizing the presence of small elements in the turf layers is possible with additional filter processing. Thus, it has been established that multispectral imaging is a new high-tech tool for performing work: archaeological exploration, searching for new objects and clarifying the configuration of previously studied objects, when mapping stand-alone sites and archaeological complexes in general., В статье рассматриваются методические вопросы картографирования объектов археологического наследия дистанционным образом с помощью беспилотных аппаратов. В качестве полигона был выбран участок долины р. Юстыд на территории Кош-Агачского района Республики Алтай. Участок съемки 2021 г. охватывал территорию правого берега с максимальной концентрацией объектов больших размеров, прежде всего херексуров, отличающихся разнообразием формы и внутреннего строения. Для мультиспектральной съемки археологических памятников использовали беспилотный летательный аппарат DJI Inspire 1 (ver. 2.0), конструктивной особенностью которого являлась дополнительная мини-платформа, расположенная в задней части корпуса. Платформа была смонтирована для установки камеры Parrot Sequoia и дополнительной батареи — источника автономного питания камеры. Процесс фотограмметрической обработки снимков представлял собой компьютерную автоматизированную цифровую обработку фотоматериалов с последующим созданием мозаичного ортофотоплана. Для фотограмметрической обработки материалов была выбрана программа Agisoft Metashape. Полученные результаты были подвергнуты индексной (тематической) обработке мультиспектральных снимков на основе комбинации зеленого, красного и ближнего инфракрасного каналов. В ходе сравнительного анализа построенных изображений обнаружены следующие закономерности. Индекс MCARI позволяет обнаруживать курганные могильники и элементы конструкции, выраженные в геометрии (плане). Детектирование различных «аномалий», характеризующих наличие мелких элементов в задернованных слоях, возможно при дополнительной обработке фильтрами. Таким образом, установлено, что мультиспектральная съемка является новым высокотехнологичным инструментом при выполнении археологической разведки, поиске новых объектов и уточнении конфигурации ранее исследованных объектов, при картографировании отдельно стоящих памятников и археологических комплексов в целом.

Single unmanned aerial vehicle (UAV) multitasking plays an important role in multiple UAVs cooperative control, which is as well as the most complicated and hardest part. This paper establishes a three-dimensional topographical map, and an improved adaptive differential evolution (IADE) algorithm is proposed for single UAV multitasking. As an optimized problem, the efficiency of using standard differential evolution to obtain the global optimal solution is very low to avoid this problem. Therefore, the algorithm adopts the mutation factor and crossover factor into dynamic adaptive functions, which makes the crossover factor and variation factor can be adjusted with the number of population iteration and individual fitness value, letting the algorithm exploration and development more reasonable. The experimental results implicate that the IADE algorithm has better performance, higher convergence and efficiency to solve the multitasking problem compared with other algorithms.

The article presents the development of the unmanned glider tug project, a description of the stages of a new technical solution, submitted to the patent office in December 2017 and developed to date. The proposed towing system consists of a universal drone ground control station and a tugboat rigidly connected to the sailplane. The proposed solution is aimed at reducing operating costs and limiting the number of people necessary to service sailplane flights. В статье представлена разработка проекта беспилотного буксира-планера, описание этапов нового технического решения, представленного в патентное ведомство в декабре 2017 года и разработанного на сегодняшний день. Предлагаемая буксирная система состоит из универсального наземного поста управления дроном и буксира, жестко связанного с планером. Предложенное решение направлено на снижение эксплуатационных расходов и ограничение количества людей, необходимых для обслуживания полетов планеров. У статті представлено розробку проекту безпілотного буксира-планера, опис етапів нового технічного рішення, представленого до патентного відомства у грудні 2017 року та розробленого на сьогоднішній день. Пропонована буксирна система складається з універсального наземного поста керування дроном і буксира, жорстко пов'язаного з планером. Запропоноване рішення спрямоване на зниження експлуатаційних витрат та обмеження кількості людей, необхідних обслуговування польотів планерів.

The article presents the development of the unmanned glider tug project, a description of the stages of a new technical solution, submitted to the patent office in December 2017 and developed to date. The proposed towing system consists of a universal drone ground control station and a tugboat rigidly connected to the sailplane. The proposed solution is aimed at reducing operating costs and limiting the number of people necessary to service sailplane flights. В статье представлена разработка проекта беспилотного буксира-планера, описание этапов нового технического решения, представленного в патентное ведомство в декабре 2017 года и разработанного на сегодняшний день. Предлагаемая буксирная система состоит из универсального наземного поста управления дроном и буксира, жестко связанного с планером. Предложенное решение направлено на снижение эксплуатационных расходов и ограничение количества людей, необходимых для обслуживания полетов планеров. У статті представлено розробку проекту безпілотного буксира-планера, опис етапів нового технічного рішення, представленого до патентного відомства у грудні 2017 року та розробленого на сьогоднішній день. Пропонована буксирна система складається з універсального наземного поста керування дроном і буксира, жорстко пов'язаного з планером. Запропоноване рішення спрямоване на зниження експлуатаційних витрат та обмеження кількості людей, необхідних обслуговування польотів планерів.

The frequent intrusion of unmanned aerial vehicles (UAVs) into civil aviation airports poses a severe challenge to the safety management of the airport. The subsequent flight delays and even the closure of the runway have seriously affected the normal operation of the airport. To measure the collision risk of the Unmanned-Manned (U-M) encounter (intruding UAV to manned aircraft), a collision risk assessment platform is developed in this paper to predict the U-M encounter collision risk of the airport restricted area. The designed platform can be used to dynamically generate 3D trajectories of the U-M encounter, and to assess the collision risk with the changing of the relative distance in the probabilistic curve. Further, to predict the collision risk of the airport restricted area, the collision risk heatmap representation is then introduced. A case study of Changi Airport, Singapore is employed to generate the runway collision risk heatmap based on the designed collision risk assessment platform. The results demonstrate how the collision risk of the separate runway and the integrated runway distributes. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Submitted/Accepted version This project is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme.

High-altitude platform (HAP) are stations on an object at an altitude of around 15-50 km at a specified nominal fixed point relative to Earth. Tethered high-altitude platform (tHAP) are unmanned aerial vehicle that are connected to the ground via a tether with a lift height of 100 − 150 meters, and a multi-copter as high altitude mode. The reliability of the tHAP can be assessed with a focus on the tether that connects it to the ground. This article proposes a Markov model which obtain the reliability of the tHAP. The tether is considered to be made up of multiple wires in such a way that the tether still operates for a given number of functioning wires. The failure rates of the wires are dependent on the number of failed wires. Through the reliability analysis of the proposed Markov model, the key performance measures such as reliability of the system, mean time between failures and the probability of the system being reliable are computed. The optimal number of wires is also obtained via the numerical computation of the performance measures.

The potential impact of a grand unified theory of the brain on the robotics community might be immense, as it might hold the key to the general artificial intelligence. Such a theory might make revolutionary leaps in robot intelligence by improving the quality of our lives. The last two decades have witnessed the rise of one such brain theory - the free energy principle (FEP) - that seems to be successful in explaining a large body of cognitive functions. The tremendous amount of research centering FEP is a testament to its popularity within the neuroscience community. This raises two important questions: i) since biological systems are fundamentally different from robots, will FEP be useful in solving real robotics problems? ii) if so, will it outperform classical robot algorithms? To answer these questions, this thesis takes a step in the direction of applying FEP on three class of robotics challenges, with a special focus on Unmanned Aerial Vehicle (UAV): i) action, ii) perception and iii) active perception. This thesis demonstrates the usefulness of FEP in solving these challenges, and shows that FEP is particularly beneficial in dealing with colored (non-white) noise during estimation (perception) when compared to classical methods, marking the utility of FEP not only in neuroscience, but also in robotics. With these results, this thesis aims to contribute to the rise of FEP as a unified theory of robot intelligence.

A novel terminal sliding mode control is introduced to control a class of nonlinear uncertain systems in finite time. Having command on the definition of the final time as an input control parameter is the goal of this work. Terminal sliding mode control is naturally a finite-time controller though the time cannot be set as input, and the convergence time is not exactly known to the user before execution of the control loop. The sliding surface of the introduced controller is equipped with a finite-time gain that finishes the control task in the desired predefined time. The gain is found by partitioning the state-dependent differential Riccati equation gain, then arranging the sub-blocks in a symmetric positive-definite structure. The state-dependent differential Riccati equation is a nonlinear optimal controller with a final boundary condition that penalizes the states at the final time. This guides the states to the desired condition by imposing extra force on the input control law. Here the gain is removed from standard state-dependent differential Riccati equation control law (partitioned and made symmetric positive-definite) and inserted into the nonlinear sliding surface to present a novel finite-time terminal sliding mode control. The stability of the proposed terminal sliding mode control is guaranteed by the definition of the adaptive gain of terminal sliding mode control, which is limited by the Lyapunov stability condition. The proposed approach was validated and compared with state-dependent differential Riccati equation and conventional terminal sliding mode control as independent controllers, applied on a van der Pol oscillator. The capability of the proposed approach of controlling complex systems was checked by simulating a flapping-wing flying robot. The flapping-wing flying robot possesses a highly nonlinear model with uncertainty and disturbance caused by flapping. The flight assumptions also limit the input law significantly. The proposed terminal sliding mode control successfully controlled the illustrative example and flapping-wing flying robot model and has been compared with state-dependent differential Riccati equation and conventional terminal sliding mode control.

In order to detect special nuclear materials and other radioactive materials in Security and Defense scenarios, normally, a combination of neutron and gamma-ray detection systems is used. In particular, to avoid illicit traffic of special nuclear materials and radioactive sources/materials, radiation portal monitors are placed at seaports to inspect shipping-container cargo. Despite their large volume (high efficiency), these detection systems are expensive, and therefore only a fraction of these containers are inspected. In this work, a novel mobile radiation detection system is presented, based on an EJ-200 plastic scintillator for the detection of gamma rays and beta particles, and a neutron detector EJ-426HD plastic scintillator (with 6Li) embedded in a compact and modular moderator. The use of silicon photomultipliers in both detectors presented advantages such as lightweight, compactness, and low power consumption. The developed detection system was integrated in a highly maneuverable multirotor. Monte Carlo simulations were validated by laboratory measurements and field tests were performed using real gamma-ray and neutron sources. The detection and localization within one meter was achieved using a maximum likelihood estimation algorithm for 137Cs sources (4 MBq), as well as the detection of 241Am–beryllium (1.45 GBq) source placed inside the shipping container.

Beyond the obvious burdens of moving refined petroleum products around the battlespace, and the inherent risks, the increasing cost of hydrocarbon fuels and their associated environmental impact have led to heightened demand for the use of alternative fuels in military applications. Hydrogen is one promising alternative fuel due to its high gravimetric energy density, large abundance, limited environmental impact, renewability, and ability to be produced in situ. The goal of this thesis is to develop a set of operational scenarios that demonstrate the plausibility and advantages of using hydrogen-powered unmanned aerial vehicles (UAVs) for naval operations. Use cases for hydrogen-powered UAVs are identified from operational experience and usage of other UAV types currently in operation. Systems modeling language (SysML) tools are used to present these use cases in readable diagrams. Each use case is explained by a written scenario, sequence diagram, and high-level operational concept graphic. Hydrogen-powered UAVs can be effectively used in numerous naval applications while providing advantages, mostly due to their increased flight endurance and low signature. Researchers can apply this same process to general hydrogen fuel usage in all naval operations to better prove its efficacy and justify continued research and development. The next step for this research is to demonstrate the operational capabilities of hydrogen-powered UAVs through flight testing. Outstanding Thesis Lieutenant, United States Navy Approved for public release. Distribution is unlimited.

Previous research has demonstrated the operational benefits of supplementing unmanned aircraft systems (UAS) with solar power. With limits to energy storage based on aircraft cost and weight, supplementing aircraft power systems with solar technology can meet modern requirements with current technology. The focus of this research is to determine the potential increase in the range and endurance of the AeroVironment Switchblade 300 unmanned aerial vehicle (UAV) through the inclusion of advanced thin-film flexible solar cells. In lieu of a fully operational test aircraft, the research developed a prototype solar enhanced Switchblade 300 using comparable components and a production Switchblade 300 airframe to conduct real world experimentation in the feasibility of solar enhancement. The research also extrapolated empirical data to estimate the effects of solar enhancement on similar Group 1 UAS. A 23.7% increase in endurance was achieved on the prototype solar enhanced Switchblade 300 and a more than 83.3% increase is feasible using higher efficiency solar cells. More than a 108% increase is theoretically feasible for the Switchblade 600 UAV based on scaled empirical data. These findings indicate that current production small electric tube-launched UAS have significant potential for improvement and could leverage future advances in solar technology to gain significant technological advantages for the warfighter. Captain, United States Marine Corps Approved for public release. Distribution is unlimited.

Yield estimation in vineyards is an essential issue for performing cropping practices to reach the desired production quality or quantity. Sporadic manual measurements have been traditionally made. In the last decade, vegetation indices (VIs) and geometric parameters obtained from unmanned aerial vehicle (UAV) imagery have been related to different vine biophysical features. This research aimed to evaluate the potential of VIs and green canopy cover (GCC; as a measure of plant vigour) obtained from conventional (or red, green, blue; RGB) and multispectral sensors that monitor spatial intraplot variability for yield predictions. The yield components traditionally sampled in an early growth cycle stage (pea berry size) were combined with UAV imagery-based products. The proposed methodology was applied to a vineyard in southeastern Spain during the 2019 and 2020 growing seasons. Rain-fed and irrigated treatments were implemented. Flights were performed throughout the growth cycle using RGB and multispectral cameras mounted on a UAV. Orthoimages were generated. Computer vision techniques were used to segment these orthoimages to obtain vegetation-only masks. Simple and multiple linear regression techniques were evaluated by using VIs alone, VIs combined with GCC and yield components as predictors. The RMSE values ranged from 0.21 kg vine to 0.39 kg vine when yield components, RGB or multispectral VIs were employed. Therefore, with all the advantages that their use entails, RGB and multispectral sensors are a good option for estimating the final yield of vineyards despite calibration being required for each season and grapevine plot., This work was supported by the Ministry of Science, Innovation and Universities, grant numbers RTC-2017-6365-2 and PID2020-115998RB-C22; by the Government of Castilla-La Mancha, grant number SBPLY/17/180501/000251; and by FEDER funds.

At present, there exists a prioritization of identifying novel and innovative approaches to managing the small Unmanned Aircraft Systems (sUAS) threat. The near-future sUAS threat to U.S. forces and infrastructure indicates that current Counter-UAS (C-UAS) capabilities and tactics, techniques, and procedures (TTPs) need to evolve to pace the threat. An alternative approach utilizes a networked squadron of unmanned aerial vehicles (UAVs) designed for sUAS threat interdiction. This approach leverages high performance and Size, Weight, and Power (SWaP) conformance to create less expensive, but more capable, C-UAS devices to augment existing capabilities. This capstone report documents efforts to develop C-UAS technologies to reduce energy consumption and collaterally disruptive signal footprint while maintaining operational effectiveness. This project utilized Model Based System Engineering (MBSE) techniques to explore and assess these technologies within a mission context. A Concept of Operations was developed to provide the C-UAS Operational Concept. Operational analysis led to development of operational scenarios to define the System of Systems (SoS) concept, operating conditions, and required system capabilities. Resource architecture was developed to define the functional behaviors and system performance characteristics for C-UAS technologies. Lastly, a modeling and simulation (M&S) tool was developed to evaluate mission scenarios for C-UAS. Outstanding Thesis Civilian, Department of the Navy Civilian, Department of the Navy Civilian, Department of the Navy Civilian, Department of the Navy Civilian, Department of the Navy Approved for public release. Distribution is unlimited.

The search for disaster victims carried out by search-and-rescue (SAR) team mainly uses traditional methods, which are considered to take much time and effort, and pose a high risk for the search team and the victim. Based on this problem, we conducted research to assist disaster victim search. In this research, we designed a system using passive infrared (PIR) sensors to detect and measure the direction angle of the victim. Given the direction angle from different observation points’ perspectives, we determine the victim’s position using the triangulation method. we also designed a quadcopter unmanned aerial vehicle (UAV) to carry this sensor system across the disaster area. For monitoring purposes, a local website was designed to display data generated by the system. Based on test results, the system can determine a victim’s position with a distance difference of less than 5 m. The system can search victim in an empty land ±35 m×15 m wide in 14 minutes 20 seconds. The data monitoring system also displayed the victim’s position, the position of the observation points, and the UAV’s flight path.

Detection and recognition of objects in images is the main problem to be solved by computer vision systems. As part of solving this problem, the model of object recognition in aerial photographs taken from unmanned aerial vehicles has been improved. A study of object recognition in aerial photographs using deep convolutional neural networks has been carried out. Analysis of possible implementations showed that the AlexNet 2012 model (Canada) trained on the ImageNet image set (China) is most suitable for this problem solution. This model was used as a basic one. The object recognition error for this model with the use of the ImageNet test set of images amounted to 15%. To solve the problem of improving the effectiveness of object recognition in aerial photographs for 10 classes of images, the final fully connected layer was modified by rejection from 1,000 to 10 neurons and additional two-stage training of the resulting model. Additional training was carried out with a set of images prepared from aerial photographs at stage 1 and with a set of VisDrone 2021 (China) images at stage 2. Optimal training parameters were selected: speed (step) (0.0001), number of epochs (100). As a result, a new model under the proposed name of AlexVisDrone was obtained. The effectiveness of the proposed model was checked with a test set of 100 images for each class (the total number of classes was 10). Accuracy and sensitivity were chosen as the main indicators of the model effectiveness. As a result, an increase in recognition accuracy from 7% (for images from aerial photographs) to 9% (for the VisDrone 2021 set) was obtained which has indicated that the choice of neural network architecture and training parameters was correct. The use of the proposed model makes it possible to automate the process of object recognition in aerial photographs. In the future, it is advisable to use this model at ground stations of unmanned aerial vehicle complex control when processing aerial photographs taken from unmanned aerial vehicles, in robotic systems, in video surveillance complexes and when designing unmanned vehicle systems

Introduction. Unmanned aerial vehicles as quadcopters, twin rotors, fixed-wing crafts, and helicopters are being used in many applications these days. Control approaches applied on the quadrotor after decoupling the model or separate altitude control and trajectory tracking have been reported in the literature. A robust linear H∞ controller has been designed for both altitude control and circular trajectory tracking at the desired altitude. Problem. The ability of the quadrotor system to hover at a certain height and track any desired trajectory makes their use in many industrial applications in both military and civil applications. Once a controller has been designed, it may not be able to maintain the desired performance in practical scenarios, i.e. in presence of wind gusts. Originality. This work presents the control strategy to ensure both altitude control and trajectory tracking using a single controller. Purpose. However, there is a need for a single controller that ensures both altitude control and trajectory tracking. Novelty. This paper presents a robust H∞ control for altitude control and trajectory tracking for a six degree of freedom of unmanned aerial vehicles quadrotor. Methodology. Multi input multi output robust H∞ controller has been proposed for the quadrotor for altitude control and tracking the desired reference. For the controller validation, a simulation environment is developed in which a 3D trajectory is tracked by the proposed control methodology. Results. Simulation results depict that the controller is efficient enough to achieve the desired objective at minimal control efforts. Practical value. To verify that the proposed approach is able to ensure stability, altitude control, and trajectory tracking under practical situations, the performance of the proposed control is tested in presence of wind gusts. The ability of the controller to cater to the disturbances within fractions of seconds and maintaining both transient and steady-state performance proves the effectiveness of the controller., Вступ. Безпілотні літальні апарати, такі як квадрокоптери, двороторні апарати, апарати з нерухомими крилами та гелікоптери сьогодні використовуються у багатьох сферах застосування. У літературі повідомляється про підходи до керування, застосовані на квадрокоптері після від’єднання моделі або окремого контролю висоти та відстеження траєкторії. Надійний лінійний регулятор H∞ був розроблений як для контролю висоти, так і для відстеження кругової траєкторії на потрібній висоті. Проблема. Здатність квадрокоптерної системи зависати на певній висоті та відстежувати будь-яку бажану траєкторію робить їх застосування можливим у багатьох сферах як у військових, так і в цивільних цілях. Розроблений контролер може не підтримувати бажані характеристики у реальних умовах, тобто за наявності поривів вітру. Оригінальність. У цій роботі представлена стратегія керування, яка забезпечує як контроль висоти, так і відстеження траєкторії за допомогою одного контролера. Мета. Однак існує потреба в єдиному контролері, який забезпечує як контроль висоти, так і відстеження траєкторії. Новизна. У цій статті представлено надійний регулятор H∞ для контролю висоти та відстеження траєкторії для шести ступенів свободи безпілотних літальних апаратів. Методологія. Для квадрокоптера запропоновано багатовхідний багатовихідний надійний контролер H∞ для контролю висоти та відстеження бажаного курсу. Для перевірки контролера розробляється середовище моделювання, в якому тривимірна траєкторія відстежується за запропонованою методологією керування. Результати. Результати моделювання показують, що контролер є досить ефективним для досягнення бажаної мети при мінімальних зусиллях контролю. Практична цінність. Щоб переконатися, що запропонований підхід здатний забезпечити стабільність, контроль висоти та відстеження траєкторії в реальних ситуаціях, параметри запропонованого контролю перевіряються за наявності поривів вітру. Здатність контролера усувати порушення протягом кількох секунд і підтримувати як перехідні, так і стабільні показники доводить ефективність контролера.

International audience; The main contribution of this paper is the design of an event-triggered formation control for leader-following consensus in second-order multi-agent systems (MASs) under communication faults. All the agents must follow the trajectories of a virtual leader despite communication faults considered as smooth time-varying delays dependent on the distance between the agents. Linear matrix inequalities (LMIs)-based conditions are obtained to synthesize a controller gain that guarantees stability of the synchronization error. Based on the closed-loop system, an event-triggered mechanism is designed to reduce the control law update and information exchange in order to reduce energy consumption. The proposed approach is implemented in a real platform of a fleet of unmanned aerial vehicles (UAVs) under communication faults. A comparison between a state-of-the-art technique and the proposed technique has been provided, demonstrating the performance improvement brought by the proposed approach.

Aerial photogrammetry is increasingly being used to discover, document, and interpret the cultural heritage of landscapes. Information on the constructed cultural heritage left behind by the first cattle ranchers in the American West is being lost as the land is transformed and modified, and stewardship of the land changes across generations. An unmanned aerial vehicle (UAV) has been used in this research to record and interpret two surface water cattle tanks constructed by Texas cowboys in the mid-1880s. Similar size rocks have been used and placed in a similar pattern across the walls of both tanks. This similarity suggests both tanks were constructed at the same time. This research also demonstrates that UAV photogrammetry can be used to rapidly record and analyze the constructed cultural heritage of American West cowboys.