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Unmanned Aircraft Systems (UASs) have advanced technologically and surged exponentially over recent years. Currently, due to safety concerns, most civil operations of UAS are conducted in low-level uncontrolled area or in segregated controlled airspace. As the industry progresses, both operational and technological capabilities have matured to the point where UASs are expected to gain greater freedom of access to both controlled and uncontrolled airspace. Extensive technical and regulatory surveys have been conducted to enable the expanded operations. However, most surveys are derived from the perspective of UAS own operating mechanism and barely consider interactions of their non-segregated activities with the Air Traffic Management (ATM) system. Hence, to fill the gap, this paper presents a survey conducted from the perspective of Air Navigation Service Provider (ANSP), which serves to accommodate these new entrants to the overall national airspace while continuing flight safety and efficiency. The primary objectives of this paper are to: (A) describe what typical ANSP-supplied UAS Traffic Management (UTM) architecture is required to facilitate all types of civil UAS operations; (B) identify three major ANSP considerations on how UAS can be accommodated safely in civil airspace; (C) outline future directions and challenges related with UAS operations for the ANSP.

Moderni brezpilotni letalski sistemi ze zanašajo na globalne pozicijske sisteme za opravljanje avtonomnih misij in vračanje na točko vzleta ob izgubi brezžične povezave z operaterjem. Sprejem signala GPS je lahko moten ali onemogočen zaradi mnogih naravnih, namernih in elektromagnetnih razlogov, kar onemogoči prej omenjene sisteme. Namen našega dela je bil raziskati možnosti lokalizacije brezpilotnih sistemov v tem primeru. Za ta namen smo na podlagi teorije avtonomnih mobilnih sistemov, računalniškega vida in vgradnih sistemov predlagali pet metod lokalizacije brez signala GPS: inercialna odometrija, odometrija z modelom kvadrokopterja, dva pristopa vizualne odometrije in pristop z algoritmom SLAM. Delovanje vseh petih metod smo preverili na dveh podatkovnih zbirkah, ki smo ju posneli s pomočjo testnega kvadrokopterja in zajema podatkov senzorjev na njem. Kvalitativno oceno delovanja smo podali s pomočjo več metrik, ki opisujejo natančnost in uporabnost predlaganih metod. Ugotovili smo, da je vseh pet metod razen inercialne odometrije, ki ni dovolj natančna, primernih za praktično rabo v primeru odsotnosti GPS signala. Najboljše sta delovali metodi z optično odometrijo, ki pa zahtevata dobro oceno višine od tal. Odometrija z modelom kvadrokopterja je dosegla zadovoljive rezultate, vendar ne deluje dobro v vetrovnih razmerah. Ugotovili smo še, da vse metode razen SLAM delujejo na vgradnih sistemih z omejenimi sistemskimi sredstvi. Modern unmanned aerial vehicles rely on the global positioning system to carry out autonomous missions and return to launch if the control link is lost. GPS reception can be jammed or lost due to several natural, intentional, and electromagnetic causes, which disables autonomous systems. The purpose of this paper was to research localization options of unmanned aerial vehicles in those scenarios. Based on the theory of autonomous mobile systems, computer vision, and embedded systems, we proposed five localization methods without GPS reception: inertial odometry, odometry with quadcopter model, two approaches with visual odometry, and using SLAM. We have tested the performance of all five methods on two datasets, that we obtained using a test quadcopter platform and data captured by its sensors. We have used multiple metrics to evaluate the accuracy, precision, and usability of the proposed methods. We have concluded that all five methods are suitable for real-life use in the case of GPS signal absence, except for inertial odometry, which is not accurate enough. Optical odometry methods performed the best, but they require good ground-camera distance measurement. Odometry with quadcopter model worked well but does not give accurate estimates in windy environments. All methods except SLAM are appropriate for use on embedded systems with limited resources.

Includes supplementary material. Please contact rresources@nps.edu for access. When the Islamic State used Unmanned Aerial Vehicles (UAV) to target coalition forces in 2014, the use of UAVs rapidly expanded, giving weak states and non-state actors an asymmetric advantage over their technologically superior foes. This asymmetry led the Department of Defense (DOD) and the Department of Homeland Security (DHS) to spend vast sums of money on counter-unmanned aircraft systems (C-UAS). Despite the market density, many C-UAS technologies use expensive, bulky, and high-power-consuming electronic attack methods for ground-to-air interdiction. This thesis outlines the current technology used for C-UAS and proposes a defense-in-depth framework using airborne C-UAS patrols outfitted with cyber-attack capabilities. Using aerial interdiction, this thesis develops a novel C-UAS device called the Detachable Drone Hijacker—a low-size, weight, and power C-UAS device designed to deliver cyber-attacks against commercial UAVs using the IEEE 802.11 wireless communication specification. The experimentation results show that the Detachable Drone Hijacker, which weighs 400 grams, consumes one Watt of power, and costs $250, can interdict adversarial UAVs with no unintended collateral damage. This thesis recommends that the DOD and DHS incorporates aerial interdiction to support its C-UAS defense-in-depth, using technologies similar to the Detachable Drone Hijacker. DASN-OE, Washington DC, 20310 Captain, United States Marine Corps Approved for public release. Distribution is unlimited.

International audience; In this paper, we propose a new piecewise polynomial model (PwPM) for the modelling of an Unmanned Aircraft System (UAS) aerodynamic coefficients over a wide flight envelope, where they are characterized by nonlinear and hysteresis phenomena. An associated identification method using Constrained Least Squares (CLS) is then presented and successfully applied to experimental data obtained from wind tunnel measurements. The resulting fitting is finally compared with the similar piecewise models PWPFIT and AERODAS, showing a greater precision in its modelling, while maintaining their relative simplicity and computation performance.

Recent years have witnessed a booming of the industry of civil Unmanned Aircraft System (UAS). As an emerging industry, the UAS industry has been attracting great attention from governments of all countries and the aviation industry. UAS are highly digitalized, informationized, and intelligent; therefore, their integration into the national airspace system has become an important trend in the development of civil aviation. However, the complexity of UAS operation poses great challenges to the traditional aviation regulatory system and technical means. How to prevent collisions between UASs and between UAS and manned aircraft to achieve safe and efficient operation in the integrated operating airspace has become a common challenge for industry and academia around the world. In recent years, the international community has carried out a great amount of work and experiments in the air traffic management of UAS and some of the key technologies. This paper attempts to make a review of the UAS separation management and key technologies in collision avoidance in the integrated airspace, mainly focusing on the current situation of UAS Traffic Management (UTM), safety separation standards, detection system, collision risk prediction, collision avoidance, safety risk assessment, etc., as well as an analysis of the bottlenecks that the current researches encountered and their development trends, so as to provide some insights and references for further research in this regard. Finally, this paper makes a further summary of some of the research highlights and challenges.

Military strategists and technologists have welcomed the rise of remotely piloted aircraft (RPAs) in intelligence, surveillance, and reconnaissance (ISR) roles because of their persistence and expendability which provide operational flexibility to commanders and decision makers. Furthermore, RPAs generally cost less to operate than manned systems. However, some small manned ISR aircraft have low operating costs, have been proven in operations around the world, and do not require any new spending to develop. While pursuing RPAs to gain the benefits identified, the Marine Corps may incur costs that reduce overall value to the service. In this study, I conduct a cost-effectiveness analysis of two ISR systems to determine the alternative with the best value. The representative platforms analyzed are the unmanned RQ-21A and the manned MC-12W, to determine if the Marine Corps can realize greater value from a small manned aircraft than small RPAs for ISR missions. I find that the RQ-21A is a more effective platform based on the objective hierarchy established, with a measure of overall effectiveness (MOE) score of .721. However, it is more costly than the MC-12W on a cost per flight hour (CPFH) basis with a CPFH of $18,223. The MC-12W is a less effective platform based on the objective hierarchy established, with an MOE score of .497. However, it is less costly than the RQ-21A on a per flight hour basis with a CPFH of $6,079. Major, United States Marine Corps Approved for public release. Distribution is unlimited.

Unmanned Aircraft Systems (UAS), commonly known as drones, are becoming increasingly popular in civilian applications. However, the infrastructure to ensure the safe operations are still largely missing. In this dissertation, I addressed two problems related to a flight mission. First, I propose a flight planning system specifically for single multirotor UAS operations. The system generates a 4D trajectory at the pre-flight stage before an actual flight taking place. Safety is achieved by ensuring enough energy to finish a trip under environmental influences such as wind, as well as avoiding static obstacles. Second, I proposed a hybrid controller capable of performing trajectory following as well as single-helicopter collision avoidance. The controller enables a multi-rotor to follow the planned trajectory.In the first part of the dissertation, I first divide the flight planning system into two components: energy demand and energy supply. The demand side is determined by the performance of the UAS, the environment, and the flight trajectory, while the energy supply depends on the power source. Then, I focused on two specific problems on the energy demand side. First, I quantify the energy performance of a UAS by developing a theoretical power consumption model for multi-rotor Unmanned Aircraft Systems (UAS). The model is derived from the helicopter literature. The model parameters are identified and validated experimentally by flying an IRIS+ quadrotor UAS. Second, I solved the trajectory generation problem by formulating it as an optimal control problem. The cost to be optimized is the energy consumption or flight duration at the cruise phase of a flight mission, taking into account 3-dimensional wind field and terrain variation. The problem is solved numerically by the Ordered Upwind Method (OUM). By combining the optimized path with timestamps, we can generate 4D trajectories typically used in aviation flight planning, and thus maximize the software compatibility between manned and unmanned aviation. Simulation shows that the generated trajectories are able to avoid obstacles such as high-rise buildings and give energy consumption estimates along the entire trajectory.In the second part of the dissertation, I addressed the trajectory following problem with collision avoidance capability given a planned 4D trajectory. I analyzed the tracking performance of an IRIS+ quadrotor for a challenging trajectory. In the scenario, wind played a big role in the cross-track errors. The collision avoidance capability, or a safety controller, is integrated to the trajectory following controller by introducing a hybrid automaton, deciding when to start the avoidance action and what control actions to take. The hybrid controller is examined in a simple straight-line-following scenario to avoid a manned helicopter.

Στην παρούσα διπλωματική εργασία επιχειρήθηκε ο επαναπροσδιορισμός ορίων των γεωτεμαχίων στον Αναδασμό «Τμήμα Αργυροπούλι» Δήμου Τυρνάβου. Έγινε προσπάθεια διερεύνησης των αστοχιών των κτηματολογικών διαγραμμάτων και ελέγχθηκε αν το σφάλμα που εμφανίζεται στα γεωμετρικά στοιχεία των γεωτεμαχίων εμπίπτει στις διατάξεις του άρθρου 19α του ν.2664/98. Έτσι, στο πρώτο μέρος της εργασίας αιτιολογείται η εισαγωγή του παραπάνω άρθρου στο νομικό πλαίσιο του Κτηματολογίου, ενώ ειδική μνεία γίνεται και σε όλη τη διαδικασία εφαρμογής του. Στο δεύτερο μέρος της εργασίας, αρχικά, έγινε χαρτογράφηση της περιοχής μελέτης με την χρήση μη επανδρωμένων εναέριων μέσων (Unmanned Aircraft System). Ο παραγόμενος ορθοφωτοχάρτης ακριβείας μας έδωσε μετρητικές πληροφορίες και την εικόνα της πραγματικής σημερινής κατάστασης των ακινήτων, αλλά και βοήθησε στον έλεγχο της προτεινόμενης λύσης του επαναπροσδιορισμού ορίων των γεωτεμαχίων. Στη συνέχεια, σχεδιάστηκε ο αναδασμός στο προβολικό σύστημα Hatt, προκειμένου να διαπιστωθεί, εάν υπάρχουν προβλήματα στα γεωμετρικά στοιχεία των τεμαχίων κατά τον χρόνο σύνταξης του αναδασμού και στη συνέχεια πραγματοποιήθηκε ο μετασχηματισμός στο προβολικό σύστημα ΕΓΣΑ ’87. Στο τελευταίο στάδιο, από την οριζοντιογραφική απόδοση όλων των δεδομένων, διενεργήθηκαν όλοι οι έλεγχοι συμβατότητας, προκειμένου να διαπιστωθεί αν τα διαγράμματα του λειτουργούντος Κτηματολογίου απεικονίζουν ορθά τη γεωμετρική πληροφορία των γεωτεμαχίων στην περιοχή μελέτης. Τα αποτελέσματα (και στην εν λόγω περίπτωση) αποδεικνύουν τα σοβαρά σφάλματα που υπάρχουν στα κτηματολογικά διαγράμματα εκ της πρώτης γενιάς κτηματογραφήσεων λόγω του πιλοτικού τους χαρακτήρα, In this thesis there has been an effort to resurvey the boundaries of parcels in land consolidation “Department of Argyropouli” Municipality of Tyrnavos. There has been an effort to investigate the errors of cadastral diagrams and it was checked if the failure which appears in the geometrical data of the parcels, has to do with the provisions of article 19a of law 2664/1998. So, in the first part of this thesis, we justify the entrance of the specific article of the law in the legal framework of the Cadastral and we try to explain the procedure of applying it. In the second part of the thesis, firstly there has been an effort to map the specific landscape of study by using Unmanned Aircraft System. The specific orthophoto map which was produced gave us metrical information and full image of the real today’s situation of parcels, but it also helped to control the solution suggested as far as redefining boundaries of parcels is concerned. Moreover, the parcels of land consolidation were designed in «Hatt» reference system, in order tο find out if there are problems concerning the geometrical data of the parcels while land consolidation was conducted and after that, the coordinate transformation to the «Hellenic Geodetic Reference System 1987 was performed. Finally, by horizontal efficiency of all data used, all controls of compatibility were conducted, in order tο find out if the cadastral diagrams in function can depict geometrical information of landscapes in study, correctly. The results (this case included) can prove the serious faults that exist in cadastral diagrams from the beginning of the cadastral survey, due to their pilot character

The increasing unmanned aircraft system (UAS) applications in urban environments pose challenges for safe and efficient low altitude air traffic management. As an essential enabler to meet these challenges, pre-flight 4D routes optimization is required to conduct conflict detection and resolution (CD&R) and to generate conflict-free flight routes before departure. Existing studies on strategic deconfliction cover several types of strategies such as scheduling or rerouting. However, a single type of strategy used to solve different types of conflicts may lead to an unsafe and inefficient way of conflict resolution. This paper proposes an adaptive decision-making framework to optimize the resolution strategies used for different types of conflicts with explainable mechanisms. The proposed framework is formulated as a double-layer optimization problem with the considerations of scheduling, speed adjustment, and rerouting strategies for conflict resolution. The first layer of the framework is established as a probabilistic selection model to make decisions on which strategy should be selected for what type of conflict. The second layer is developed as a mixed-integer nonlinear programming (MINLP) model to optimize the decision variables of the strategies selected by the first layer. To solve the proposed double-layer optimization problem, we introduce and improve a novel meta-heuristic stochastic fractal search (SFS) algorithm with two major improvements of a penalty-guided fitness function and an exploitation-exploration balancing scheme. Simulation results demonstrate that the proposed adaptive conflict resolution framework successfully optimizes the strategies used for each type of flight conflict, which subsequently optimizes the 4D routes with significant reductions in total operational cost, number of flight conflicts, and flight delays. The improved stochastic fractal search (ISFS) algorithm is also proved effective and reliable in solving the proposed optimization problem in different traffic density scenarios. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation (NRF), Singapore, and the Civil Aviation Authority of Singapore (CAAS), under the Aviation Transformation Programme (ATP).

Various applications of unmanned aerial vehicles (UAVs) in urban environments facilitate our daily life and public services. However, UAV operations bring third party risk (TPR) issues, as UAV may crash to pedestrians and vehicles on the ground. It may also cause property damages to critical infrastructures and noise impacts to the public. Path planning is an effective method to mitigate these risks and impacts by avoiding high-risk areas before flight. However, most of the existing path planning methods focus on minimizing flight distance or energy cost, rarely considered risk cost. This paper develops a novel flight path optimization method that considers an integrated cost assessment model. The assessment model incorporates fatality risk, property damage risk, and noise impact, which is an extension of current TPR indicators at modeling and assessment levels. To solve the proposed integrated cost-based path optimization problem, a hybrid estimation of distribution algorithm (EDA) and CostA* (named as EDA-CostA*) algorithm is proposed, which provides both global and local heuristic in- formation for path searching in cost-based environments. A downtown area in Singapore is selected for the case study. Simulation results demonstrate the effectiveness of the developed cost-based path optimization model in reducing the risk cost. The statistical analysis for 100 sampled environments also shows the reliability of the proposed method, which reduced the cost by [42.64%, 44.15%] at 95% confidence level. Civil Aviation Authority of Singapore (CAAS) Accepted version This research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme on "Integration of Unmanned Aircraft Systems (UAS) into the Airspace." Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of National Research Foundation, Singapore and the Civil Aviation Authority of Singapore.

With the fast development of unmanned aircraft vehicle (UAV) operations in urban environments, the low-altitude air traffic is projected to be crowded. That would bring about problems such as how to determine the safe separation between two UAV operations. This paper proposes an evaluation framework for the determination of flight technical error (FTE) by investigating flight trajectory deviations, which is to support the establishment of separation requirement for UAV operations. Flight experiments are conducted by using a commonly used drone to collect flight trajectory data. Statistical analysis methods are used to investigate the trajectory deviations on lateral, longitudinal, and vertical axes. The normality tests are first conducted for the trajectory deviation data. The analysis of variance (ANOVA) is then performed to test the homogeneity of sample variances, while the regression analysis is conducted to investigate potential trends of the trajectory deviations with the change of flight heights. Statistical testing results show that the mean trajectory deviation in different flight times has no significant difference, whereas the mean trajectory deviation increases with the increase of flight height. The results also show that the linear increasing trend is more evident for deviations on the lateral track, while the quadratic increasing trend of trajectory deviation dominates on the longitudinal track. The deviations on vertical track is not significant compared with the ones on lateral and longitudinal tracks. This study investigates the flight technical error by analyzing the flight trajectory deviations, which will support the determination of separation requirement for safe UAV operations in low-altitude urban airspace. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme.

This chapter deals with the selection process of three different aircraft configurations that are appropriate for automated cargo operations at low altitudes and above sparsely populated areas. The selection process starts with a conceptual assessment of various aircraft types with respect to their suitability as an unmanned cargo aircraft (UCA) and subject to a set of specific top-level aircraft requirements (TLAR’s). Based on the TLAR’s and further characteristics like fuel efficiency, cargo space accessibility, technical simplicity or size, five fixed-wing aircraft and two rotorcraft are chosen for further investigations. A subsequent preliminary design study dimensions the fixed-wing aircraft for different wing spans based on flight performance requirements according to the TLAR’s. A possible mean to enhance take-off and landing performances is the integration of additional small propellers and to make use of the propeller slipstream effect. Therefore, this chapter furthermore investigates the benefits from the integration of additional electrically driven propellers. The second part of the study focusses on the comparison of a helicopter and a gyrocopter, presenting performance key parameters and discussing their respective advantages and disadvantages. This chapter concludes with the selection of a twin boom aircraft of 16 m wing span, a box wing of 12 m span and a gyrocopter with a rotor radius of 7 m and small supplementary wings for the use as UCA.

This paper presents a novel method of procuring and processing data for the assessment of civil structures via vibration monitoring. This includes the development of a custom sensor package designed to minimize the size/weight while being fully self-sufficient (i.e., not relying on external power). The developed package is delivered to the structure utilizing a customized Unmanned Aircraft System (UAS), otherwise known as a drone. The sensor package features an electropermanent magnet for securing it to the civil structure while a second magnet is used to secure the package to the drone during flight. The novel B-Spline Impulse Response Function (BIRF) technique was utilized to extract the Dynamic Signature Response (DSR) from the data collected by the sensor package. Experimental results are presented to validate this method and show the feasibility of deploying the sensor package on structures and collecting data valuable for Structural Health Monitoring (SHM) data processing. The advantages and limitations of the proposed techniques are discussed, and recommendations for further developments are made.

Цель: в статье рассмотрены вопросы эргодизайна комплексов беспилотных воздушных судов (КБПС), связанные с их анализом, проектированием и оценкой, основные эргодизайнерськие характеристики КБПС с позиций эргодизайнерського обеспечения проектирования и эксплуатации. Методы: аналитический, сравнительный. Результат: проектирование КБПС – это техническо-процессуальный комплекс, имеющий человекоцентрическую направленность и связи, структура которых содержит собственно проект предметной системы и описание процедур взаимодействия с ней. Главный смысл и особенность процесса эргодизайна системного объекта – это проектирование не только предметного, но и процессуального состава системы. Основные принципы проектирования КБВС – антропоцентрическая ориентированность проектных решений их элементов на основе системного анализа деятельности операторов и организация предметного пространства составляющих КБВС с позиции функционального комфорта. Обсуждение: процессы анализа, оценки, выработки и принятия решений базируются не только на количественных характеристиках, но и на факторах, не всегда имеющих количественные измерения (психологические, эстетические и т.п.). В определённых ситуациях на первом этапе эргодизайнерского проектирования КБПС – оценивании, – в случае невозможности использования строгих математических методов (алгоритмов, формул) следует полагаться на суждения специалистов-экспертов при условии, что эти суждения получены с помощью специально разработанных и формализованных процедур. Дальнейшие этапы эргодизайна КБПС будут рассмотрены в следующих статьях.

The tasks that unmanned aircraft systems solve include the detection of objects and determining their state. This paper reports an analysis of image recognition methods in order to automate the specified process. Based on the analysis, an improved method for recognizing images of monitored objects by a convolutional neural network using a discrete wavelet transform has been devised. Underlying the method is the task of automating image processing in unmanned aircraft systems. The operability of the proposed method was tested using an example of processing an image (aircraft, tanks, helicopters) acquired by the optical system of an unmanned aerial vehicle. A discrete wavelet transform has been used to build a database of objects' wavelet images and train a convolutional neural network based on them. That has made it possible to improve the efficiency of recognition of monitored objects and automate a given process. The effectiveness of the improved method is achieved by preliminary decomposition and approximation of the digital image of the monitored object by a discrete wavelet transform. The stages of a given method include the construction of a database of the wavelet images of images and training a convolutional neural network. The effectiveness of recognizing the monitored objects' images by the improved method was tested on a convolutional neural network, which was trained with images of 300 monitored objects. In this case, the time to make a decision, based on the proposed method, decreased on average from 0.7 to 0.84 s compared with the artificial neural networks ResNet and ConvNets. The method could be used in the information processing systems in unmanned aerial vehicles that monitor objects; in robotic complexes for various purposes; in the video surveillance systems of important objects, Одной из задач, которые решают беспилотные авиационные комплексы, является обнаружение и определение состояния объектов. С целью автоматизации данного процесса проведен анализ методов распознавания изображений. На основе проведенного анализа разработан усовершенствований метод распознавания изображений объектов мониторинга сверточной нейронной сетью с использованием дискретного вейвлет-преобразования. В основу метода положена задача обеспечения автоматизации обработки изображений в беспилотных авиационных комплексах. На примере обработки изображений (самолетов, танков, вертолетов) полученных оптической системой беспилотного летательного аппарата проверено работоспособность предложенного метода. Используется дискретное вейвлет-преобразование для создания базы данных вейвлет-образов объектов и обучения на их основе сверточной нейронной сети. Это позволило повысить оперативность распознавания объектов мониторинга и автоматизировать данный процесс. Эффективность усовершенствованного метода достигается путем предварительного разложения и аппроксимации цифрового изображения объекта мониторинга дискретным вейвлет-преобразованием. Этапами данного метода является – наработка базы данных вейвлет-образов изображений и обучение сверточной нейронной сети. Эффективность распознавания изображений объектов мониторинга усовершенствованным методом проверено на сверточной нейронной сети, которая прошла обучение изображениями 300 объектов мониторинга. При этом время на принятие решения, для предложенного метода, уменьшилось в среднем от 0.7 до 0.84с. по сравнению с искусственной нейронной сетью ResNet и ConvNets. Метод может быть использован: в системах обработки информации беспилотных летательных аппаратов, осуществляющих мониторинг объектов; в роботизированных комплексах различного назначения; системах видеонаблюдения важных объектов, Одним із завдань, що вирішують безпілотні авіаційні комплекси, є виявлення та визначення стану об’єктів. З метою автоматизації даного процесу проведено аналіз методів розпізнавання зображень. На основі проведеного аналізу розроблено удосконалений метод розпізнавання зображень об’єктів моніторингу згортковою нейронною мережею з використанням дискретного вейвлет-перетворення. В основу методу покладена задача забезпечення автоматизації обробки зображень в безпілотних авіаційних комплексах. На прикладі обробки зображень (літаків, танків, вертольотів) отриманих оптичною системою безпілотного літального апарату перевірено працездатність удосконаленого методу. Використовується дискретне вейвлет-перетворення для напрацювання бази вейвлет-образів об’єктів і навчання на їх основі штучної нейронної мережі. Це дозволило підвищити оперативність розпізнавання об’єктів моніторингу та автоматизувати даний процес. Ефективність удосконаленого методу досягається шляхом попереднього розкладу та апроксимації цифрового зображення об’єкта моніторингу дискретним вейвлет-перетворенням. Етапами даного методу є напрацювання бази даних вейвлет-образів зображень і навчання згорткової нейронної мережі. Ефективність розпізнавання зображень об’єктів моніторингу запропонованим методом перевірено на згортковій нейронній мережі, що пройшла навчання зображеннями 300 об’єктів моніторингу. При цьому час на прийняття рішення для запропонованого методу зменшився в середньому от 0.7 до 0.84с. у порівнянні з штучною нейронною мережею ResNet та ConvNets. Метод може бути використаний: в системах обробки інформації безпілотних літальних апаратів, що здійснюють моніторинг об’єктів; в роботизованих комплексах різного призначення; системах відео спостереження важливих об’єктів

International audience; A semi-parametric regression methodology is formulated to identify the unsteady lift characteristics of a small UAS undergoing dynamic stall. Based on the trailing edge separation model of Leishmann and Beddoes, the nonlinear evolution of the separation point is formulated so that it can be estimated by non-parametric Machine Learning methods. Validation of the methodology is presented with the identification of the lift coefficient based on quasi-steady wind tunnel tests.

In recent years, technological advances within civilian drone technology have opened up applications in emergency response, specifically search and rescue (SAR). Drones, also known as unmanned aircraft systems (UAS), unmanned aerial vehicles (UAVs), or unmanned assets, would be a huge boon to SAR, as they have the potential to cover large swathes of land quickly without endangering human searchers. However, while technological advances have enabled such applications, UAV function is greatly constrained by limited human-machine teaming capabilities and a restrictive regulatory environment. A lack of understandability and adjustability of automation will detract from the reliability of a system. To enable human-machine teaming during SAR, the technical portion of this work designed a graphical user interface to command a distributed constellation of semi-autonomous drones tasked with locating and triangulating a lost individual by their mobile phone signal. This interface focuses on reducing positional uncertainty over time, monitoring asset information at different levels of abstraction, and empowering an operator to influence asset behavior. This is done through spatiotemporal representations of search areas, UAS positions, communications signals, and an alert system. User evaluations with search and rescue professionals and usability experts validated the ability of the interface to aid operators in successfully addressing non-nominal situations. Current Federal Aviation Administration (FAA) UAV regulations prevent drones from being used at their full capacity. To better understand how these regulations have impacted SAR, the STS portion of this work took a random sample of the public comments on two FAA-proposed rules, Remote ID and Operations Over People, and explored them for common sentiments and key themes. These themes were then analyzed through the lenses of dual use technology transfer and Actor-Network theory. The public comments have demonstrated the successful transfer of technology between military and civilian spheres as well as the lack of stabilization within the civilian UAS network. Main points of conflict are the inclusion of recreational aircraft in rules designed for commercial use and the failure to practice evidence-informed policymaking, leading to overly restrictive regulations. The graphical user interface is a prototype that hopes to further the growing field of human-AI-robot teaming. Similarly, analysis of the proposed FAA rules demonstrates movement towards enabling basic applications of drone use. Together, an understandable interface and a favorable regulatory climate will allow the goal of using a semi-autonomous distributed constellation for search and rescue to be realized.

Understanding small remotely piloted aircraft system (sRPAS) to human head impacts is needed to better protect human head during sRPAS ground collision accidents. Recent literature reported cadaveric data on sRPAS to human head impacts, which provided a unique opportunity for developing validated computational models. However, there lacks an understanding of skull stress and brain strain during these impacts. Meanwhile, how slight changes in sRPAS impact setting could affect human head responses remains unknown. Hence, a representative quadcopter style sRPAS finite element (FE) model was developed and applied to a human body model to simulate a total of 45 impacts. Among these 45 simulations, 17 were defined according to cadaveric setting for model validation and the others were conducted to understand the sensitivity of impact angle, impact location, and impacted sRPAS components. Results demonstrated that FE-model-predicted head linear acceleration and rotational velocity agreed with cadaveric data with average predicted linear acceleration 4.5% lower than experimental measurement and average predicted of rotational velocity 2% lower than experimental data. Among validated simulations, high skull stresses and moderate level of brain strains were observed. Also, sensitivity study demonstrated significant effect of impact angle and impact location with 3° variation inducing 30% changes in linear acceleration and 29% changes in rotational velocity. Arm-first impact was found to generate more than two times higher skull stresses and brain strains compared to regular body-shell-first impact.