A Real-Time Synthesis Oriented Tanpura Model

Physics-based synthesis of tanpura drones requires accurate simulation of stiff, lossy string vibrations while incorporating sustained contact with the bridge and a cotton thread. Several challenges arise from this when seeking efficient and stable algorithms for real-time sound synthesis. The approach proposed here to address these combines modal expansion of the string dynamics with strategic simplifications regarding the string-bridge and string-thread contact, resulting in an efficient and provably stable time-stepping scheme with exact modal parameters. Attention is given also to the physical characterisation of the system, including string damping behaviour, body radiation characteristics, and determination of appropriate contact parameters. Simulation results are presented exemplifying the key features of the model.

On precise three-dimensional environment modeling via UAV-based photogrammetric systems

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.

Sistema de rádio comunicações para UAV

Os veículos aéreos não tripulados, mais conhecidos por drones, têm tomado atualmente uma posição importante na sociedade. Para além da sua importância no meio militar, têm sido cada vez mais utilizados para meios comerciais uma vez que o seu custo é relativamente baixo e podem ser utilizados para inúmeras aplicações. Devido à sua importância em missões de salvamento, reconhecimento de terreno e até mesmo de ataque, é fundamental uma boa comunicação entre a aeronave e a estação terrestre. Sendo a antena um dos principais elementos do sistema de comunicação, esta dissertação centrou-se no desenvolvimento de uma agregado de antenas a operar à frequência de 2.45GHz. Pretende-se que este agregado apresente polarização circular direita bem como um ganho e largura de banda elevados. Com o objetivo de se obter uma comunicação mais eficiente entre a aeronave e a estação terrestre, o agregado permitirá o redirecionamento do feixe principal do diagrama de radiação. Para tal, serão analisadas três abordagens distintas recorrendo a linhas de atraso e switches, permitindo que seja efetuado beamforming.

Vehicle Routing Problems that Minimize the Completion Time: Heuristics, Worst-Case Analyses, and Computational Results

In the standard Vehicle Routing Problem (VRP), we route a fleet of vehicles to deliver the demands of all customers such that the total distance traveled by the fleet is minimized. In this dissertation, we study variants of the VRP that minimize the completion time, i.e., we minimize the distance of the longest route. We call it the min-max objective function. In applications such as disaster relief efforts and military operations, the objective is often to finish the delivery or the task as soon as possible, not to plan routes with the minimum total distance. Even in commercial package delivery nowadays, companies are investing in new technologies to speed up delivery instead of focusing merely on the min-sum objective. In this dissertation, we compare the min-max and the standard (min-sum) objective functions in a worst-case analysis to show that the optimal solution with respect to one objective function can be very poor with respect to the other. The results motivate the design of algorithms specifically for the min-max objective. We study variants of min-max VRPs including one problem from the literature (the min-max Multi-Depot VRP) and two new problems (the min-max Split Delivery Multi-Depot VRP with Minimum Service Requirement and the min-max Close-Enough VRP). We develop heuristics to solve these three problems. We compare the results produced by our heuristics to the best-known solutions in the literature and find that our algorithms are effective. In the case where benchmark instances are not available, we generate instances whose near-optimal solutions can be estimated based on geometry. We formulate the Vehicle Routing Problem with Drones and carry out a theoretical analysis to show the maximum benefit from using drones in addition to trucks to reduce delivery time. The speed-up ratio depends on the number of drones loaded onto one truck and the speed of the drone relative to the speed of the truck.

Reconocimiento de una plataforma para aterrizaje de UAV mediante procesamiento de imágenes

En el año 2016 se vendieron en EE.UU más de un millón de Unmanned Aerial Vehicles (UAVs, Vehículos aéreos no tripulados), casi el doble que el año anterior, país del que se dispone de información. Para el año 2020 se estima que este mercado alcance los 5.600 millones de dólares en todo el mundo, creciendo a un ritmo del 30% anual. Este crecimiento demuestra que existe un mercado en expansión con muchas y diversas oportunidades de investigación. El rango de aplicaciones en los que se utiliza este tipo de vehículos es innumerable. Desde finales del s.XX, los UAVs han estado presentes en multitud de aplicaciones, principalmente en misiones de reconocimiento. Su principal ventaja radica en que pueden ser utilizados en situaciones de alto riesgo sin suponer una amenaza para ningún tripulante. En los últimos años, la fabricación de vehículos asequibles económicamente ha permitido que su uso se extienda a otros sectores. A día de hoy uno de los campos en los que ha adquirido gran relevancia es en agricultura, contribuyendo a la automatización y monitorización de cultivos, pero también se ha extendido su uso a diferentes sistemas, tales como seguridad, cartografía o monitorización, entre otros [1]. Es en esta situación en la que se propone el proyecto SALACOM [2], que explora la posibilidad de utilizar esta tecnología en sistemas de repuesta rápida para la detección y contención de vertidos contaminantes en entornos acuáticos con el apoyo de vehículos autónomos marinos de superficie (USV, Unmanned Surface Vehicles). En el mencionado proyecto se pretende utilizar sistemas UAVs para detectar y analizar las zonas de vertido y proveer la información respecto a la localización y las técnicas de contención adecuadas a los sistemas USV. Una vez se haya realizado el análisis de la situación del vertido, los USV trabajarían conjuntamente con los UAVs para desplegar las barreras de protección seleccionadas en la zona afectada. Para esto, los UAVs o drones, términos similares en lo que respecta a este proyecto y que a lo largo de esta memoria se usarán indistintamente, deben ser capaces de despegar desde los USV y volver a aterrizar sobre ellos una vez realizada su labor. El proyecto que se describe en la presente memoria se centra en la fase de aterrizaje y, más concretamente, en la detección de la plataforma seleccionada como plantilla mediante técnicas de tratamiento de imágenes. Esto serviría como sistema de apoyo para guiar el dron hacia la plataforma para que pueda realizar el descenso correctamente y finalizar así su misión o bien para realizar operaciones de recarga de la batería. El dron está equipado con la correspondiente cámara de visión a bordo, con la que obtiene las imágenes, las procesa e identifica la plataforma para dirigirse hacia ella, si bien, dado que el sistema de procesamiento de imágenes no se encuentra totalmente operativo, este trabajo se centra en el desarrollo de una aplicación software independiente del sistema de visión a bordo del dron, basada en el desarrollo de técnicas de reconocimiento de la plataforma. La plataforma a utilizar proviene de una patente [3], consistente en una figura geométrica con formas características, de muy difícil aparición en entornos de exterior. La figura pintada en negro se halla impresa sobre un panel de fondo blanco de 1m × 1m de superficie. En este trabajo se han explorado diversas opciones disponibles para realizar la identificación de las regiones de interés. El principal objetivo es realizar la selección de una tecnología que pueda cumplir potencialmente con los criterios necesarios para llevar a cabo la tarea y seleccionar los métodos de detección adecuados para realizar la identificación de la figura contenida en la plataforma. Se ha pretendido utilizar tecnologías de fácil uso, amplío soporte y, cuando ha sido posible, de código libre. Todo ello integrado en una aplicación informática, que es la que se presenta en el presente trabajo.

Comando e Controlo na Artilharia Antiaérea

O presente trabalho, subordinado à temática “Comando e Controlo na Artilharia Antiaérea”, pretende problematizar algumas das questões mais recentes relativas a matérias de segurança e defesa, fruto dos mais recentes acontecimentos. Por exemplo, refira-se o abate do voo comercial na Ucrânia, entre outros inúmeros casos que se constituem como fatores que levam a questionar a capacidade de defesa dos Estados face ao fácil acesso e baixo custo destes meios, à mercê de pessoas/organizações criminosas e terroristas. Assim, é premente a necessidade de aquisição, por parte dos Estados, nomeadamente de Portugal, de uma Artilharia mais robusta e com um sistema de Comando e Controlo automático capaz de combater as potenciais e prováveis ameaças aéreas. Esta investigação pretende, então, analisar o atual sistema de Comando e Controlo da Artilharia Antiaérea nacional, por forma a identificar as suas capacidades e, em paralelo, as suas vulnerabilidades. Concomitantemente pretende-se analisar o sistema perante as ameaças aéreas e as operações que deverá executar no âmbito dos compromissos internacionais, com o objetivo fulcral de identificar prováveis potencialidades que deverão integrar o referido sistema. Pretende-se, deste modo, propor uma revisão do atual sistema no sentido de colmatar as suas prováveis lacunas e capacitando-o para uma resposta eficaz e efetiva perante eventuais ameaças, na esteira dos compromissos internacionais. No início apresentamos uma ‘revisão de literatura’ para que o leitor se familiarize com os conceitos e nomenclatura em uso nesta reflexão. Subsequentemente, expõe-se a metodologia empregue e são abordados os sistemas de Defesa Aérea e de Artilharia Antiaérea e, posteriormente, o Comando e Controlo. De seguida, apresenta-se uma análise possível dos dados provenientes das entrevistas executadas. Baseando-nos na investigação realizada, conclui-se que a Artilharia Antiaérea corre o risco sério de não dispor de capacidade de defesa, a baixa e muito baixa altitude, se não forem adquiridos rapidamente os materiais imprescindíveis para que os sistemas possam cabalmente atuar.

Sistema drone para monitoreo de ganado bovino por reconocimiento de imágenes

61 p.

A practical MEMS gravimeter

The ability to measure tiny variations in the local gravitational acceleration allows – amongst other applications – the detection of hidden hydrocarbon reserves, magma build-up before volcanic eruptions, and subterranean tunnels. Several technologies are available that achieve the sensitivities required (tens of μGal/√Hz), and stabilities required (periods of days to weeks) for such applications: free-fall gravimeters, spring-based gravimeters, superconducting gravimeters, and atom interferometers. All of these devices can observe the Earth tides; the elastic deformation of the Earth’s crust as a result of tidal forces. This is a universally predictable gravitational signal that requires both high sensitivity and high stability over timescales of several days to measure. All present gravimeters, however, have limitations of excessive cost (£70 k) and high mass (<8 kg). In this thesis, the building of a microelectromechanical system (MEMS) gravimeter with a sensitivity of 40 μGal/√Hz in a package size of only a few cubic centimetres is discussed. MEMS accelerometers – found in most smart phones – can be mass-produced remarkably cheaply, but most are not sensitive enough, and none have been stable enough to be called a ‘gravimeter’. The remarkable stability and sensitivity of the device is demonstrated with a measurement of the Earth tides. Such a measurement has never been undertaken with a MEMS device, and proves the long term stability of the instrument compared to any other MEMS device, making it the first MEMS accelerometer that can be classed as a gravimeter. This heralds a transformative step in MEMS accelerometer technology. Due to their small size and low cost, MEMS gravimeters could create a new paradigm in gravity mapping: exploration surveys could be carried out with drones instead of low-flying aircraft; they could be used for distributed land surveys in exploration settings, for the monitoring of volcanoes; or built into multi-pixel density contrast imaging arrays.

Design, development and guidance of the Airborne’s quadrotor

The main goal of the Airborne project is to develop, at technology readiness level 8 (TRL8), a few selected robotic aerial technologies for quick localization of victims by avalanches by equipping drones with two forefront sensors used in SAR operations in case of avalanches, namely the ARVA and RECCO. This thesis focuses on the design, development, and guidance of the TRL8 quadrotor developed during the project. We present and describe the design method that allowed us to obtain an EMI shielded UAV capable of integrating both RECCO and ARVA sensors. Besides, is presented the avionics and power train design and building procedure in order to obtain a modular UAV frame that can be easily carried by rescuers and achieves all the performance benchmarks of the project. Additionally, in addition to the onboard algorithms, a multivariate regressive convolutional neural network whose goal is the localization of the ARVA signal is presented. On guidance, the automatic flight procedure is described, and the onboard waypoint generator algorithm is presented. The goal of this algorithm is the generation and execution of an automatic grid pattern without the need to know the map in advance and without the support of a control ground station (CGS). Moreover, we present an iterative trajectory planner that does not need pre-knowledge of the map and uses Bézier curves to address optimal, dynamically feasible, safe, and re-plannable trajectories. The goal is to develop a method that allows local and fast replannings in case of an obstacle pop up or if some waypoints change. This makes the novel planner suitable to be applied in SAR operations. The introduction of the final version of the quadrotor is supported by internal flight tests and field tests performed in real operative scenarios by the Club Alpino Italiano (CAI).

Surveillance risks in IoT applied to smart cities

Nowadays, cities deal with unprecedented pollution and overpopulation problems, and Internet of Things (IoT) technologies are supporting them in facing these issues and becoming increasingly smart. IoT sensors embedded in public infrastructure can provide granular data on the urban environment, and help public authorities to make their cities more sustainable and efficient. Nonetheless, this pervasive data collection also raises high surveillance risks, jeopardizing privacy and data protection rights. Against this backdrop, this thesis addresses how IoT surveillance technologies can be implemented in a legally compliant and ethically acceptable fashion in smart cities. An interdisciplinary approach is embraced to investigate this question, combining doctrinal legal research (on privacy, data protection, criminal procedure) with insights from philosophy, governance, and urban studies. The fundamental normative argument of this work is that surveillance constitutes a necessary feature of modern information societies. Nonetheless, as the complexity of surveillance phenomena increases, there emerges a need to develop more fine-attuned proportionality assessments to ensure a legitimate implementation of monitoring technologies. This research tackles this gap from different perspectives, analyzing the EU data protection legislation and the United States and European case law on privacy expectations and surveillance. Specifically, a coherent multi-factor test assessing privacy expectations in public IoT environments and a surveillance taxonomy are proposed to inform proportionality assessments of surveillance initiatives in smart cities. These insights are also applied to four use cases: facial recognition technologies, drones, environmental policing, and smart nudging. Lastly, the investigation examines competing data governance models in the digital domain and the smart city, reviewing the EU upcoming data governance framework. It is argued that, despite the stated policy goals, the balance of interests may often favor corporate strategies in data sharing, to the detriment of common good uses of data in the urban context.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Trajectory Planning in UAV-Aided Wireless Networks Via Reinforcement Learning

This thesis is focused on the design of a flexible, dynamic and innovative telecommunication's system for future 6G applications on vehicular communications. The system is based on the development of drones acting as mobile base stations in an urban scenario to cope with the increasing traffic demand and avoid network's congestion conditions. In particular, the exploitation of Reinforcement Learning algorithms is used to let the drone learn autonomously how to behave in a scenario full of obstacles with the goal of tracking and serve the maximum number of moving vehicles, by at the same time, minimizing the energy consumed to perform its tasks. This project is an extraordinary opportunity to open the doors to a new way of applying and develop telecommunications in an urban scenario by mixing it to the rising world of the Artificial Intelligence.