Long-Endurance Sensing and Mapping using a Hand-Launchable Solar-Powered UAV

ISSN:1610-743

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

Airframe assembly, systems integration and flight testing of a long endurance electric UAV

The need to adopt new techniques and practices in the Aerospace Industry branch is a consequence of technological development. The present work aims to study the use of solar power as a main energy source in the aviation, in this case for a flight of long endurance of an unmanned air vehicle. This master thesis follows on previous works of the LEEUAV, where it was done the design and construction of a long endurance unmanned aerial system. Thus, the main objective of this work is the systems integration, flight testing and concepts validation. LEEUAV, a prototype of 4.5 meters’ wingspan and ultralight structure partially covered by solar cells was designed to fulfil a continuous flight mission of at least 8 hours on the equinox. The 5.42Kg remotely piloted aircraft was successfully tested showing the agreement with theoretical calculations already made. The longest flight achieved lasted more than 8.5 hours’ resulting in a total distance travelled of more than 75 km. In order to validate the airworthiness concept of the LEEUAV several flight tests were performed and their respective data (static and total pressure, air temperature, ground speed and pitch angle) was collected for further analysis, using a flight controller with multiple sensors on board. The results obtained allowed to study the general performance of the aircraft, the main defects, agreement with the theoretical results as well as determine the real values of aerodynamic coefficients (????, ????), through a reading and processing flight data algorithm in Software MATLAB. Finally, some future expectations for upcoming work are suggested in order to make the LEEUAV an Unmanned Aerial Vehicle of reference.A necessidade de adoção de novas técnicas e práticas no ramo da Indústria Aeronáutica é uma consequência do desenvolvimento tecnológico. O presente trabalho aborda o uso de energia solar como principal fonte de energia na aviação, com enfoque num voo de grande autonomia de uma aeronave não tripulada. Esta tese de mestrado surge na sequência de trabalhos anteriores relativos ao LEEUAV, nos quais se efetuou o projeto e construção de uma aeronave não tripulada de grande autonomia. Assim, o principal objetivo deste trabalho é a integração de sistemas, testes de voo e validação de conceitos. O UAV Solar LEEUAV é um protótipo de 4.5 metros de envergadura e de estrutura ultraleve parcialmente coberto de células fotovoltaicas sendo projetado para cumprir uma missão de voo contínuo de pelo menos 8h no equinócio. O avião de 5.42kg foi testado com sucesso mostrando a concordância com os cálculos teóricos já elaborados. O voo mais longo conseguido foi de 3.13 horas correspondendo a uma distância total percorrida de 96.265 km. De modo a validar o conceito de aeronavegabilidade do LEEUAV foram efetuados vários voos de teste e recolhidos dados de voo (pressão estática e dinâmica, temperatura do ar, velocidade no solo e ângulo de arfagem) para posterior análise, utilizando um controlador de voo com múltiplos sensores a bordo. A análise dos resultados obtidos permitiu precisar o desempenho geral da aeronave, os principais defeitos, concordância com os resultados teóricos assim como determinar os valores reais dos coeficientes aerodinâmicos (???? , ????) através de um algoritmo de leitura e processamento de dados de voo, em Software MATLAB. Por fim, são referidas algumas sugestões para o desenvolvimento de novos trabalhos com o objetivo de tornar O LEEUAV num veículo aéreo não tripulado de referência

A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligence

Due to the advancements in cellular technologies and the dense deployment of cellular infrastructure, integrating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and beyond cellular networks is a promising solution to achieve safe UAV operation as well as enabling diversified applications with mission-specific payload data delivery. In particular, 5G networks need to support three typical usage scenarios, namely, enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). On the one hand, UAVs can be leveraged as cost-effective aerial platforms to provide ground users with enhanced communication services by exploiting their high cruising altitude and controllable maneuverability in three-dimensional (3D) space. On the other hand, providing such communication services simultaneously for both UAV and ground users poses new challenges due to the need for ubiquitous 3D signal coverage as well as the strong air-ground network interference. Besides the requirement of high-performance wireless communications, the ability to support effective and efficient sensing as well as network intelligence is also essential for 5G-and-beyond 3D heterogeneous wireless networks with coexisting aerial and ground users. In this paper, we provide a comprehensive overview of the latest research efforts on integrating UAVs into cellular networks, with an emphasis on how to exploit advanced techniques (e.g., intelligent reflecting surface, short packet transmission, energy harvesting, joint communication and radar sensing, and edge intelligence) to meet the diversified service requirements of next-generation wireless systems. Moreover, we highlight important directions for further investigation in future work.Comment: Accepted by IEEE JSA

Flexible Stereo: Constrained, Non-rigid, Wide-baseline Stereo Vision for Fixed-wing Aerial Platforms

This paper proposes a computationally efficient method to estimate the time-varying relative pose between two visual-inertial sensor rigs mounted on the flexible wings of a fixed-wing unmanned aerial vehicle (UAV). The estimated relative poses are used to generate highly accurate depth maps in real-time and can be employed for obstacle avoidance in low-altitude flights or landing maneuvers. The approach is structured as follows: Initially, a wing model is identified by fitting a probability density function to measured deviations from the nominal relative baseline transformation. At run-time, the prior knowledge about the wing model is fused in an Extended Kalman filter~(EKF) together with relative pose measurements obtained from solving a relative perspective N-point problem (PNP), and the linear accelerations and angular velocities measured by the two inertial measurement units (IMU) which are rigidly attached to the cameras. Results obtained from extensive synthetic experiments demonstrate that our proposed framework is able to estimate highly accurate baseline transformations and depth maps.Comment: Accepted for publication in IEEE International Conference on Robotics and Automation (ICRA), 2018, Brisban

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

A Low-cost Normalized Difference Vegetation Index (NDVI) Payload for Cubesats and Unmanned Aerial Vehicles (UAVs)

The focus of this research has been the design and fabrication of a Normalized Difference Vegetation Index (NDVI) payload configuration. This unique payload employs low-cost commercial off-the-shelf (COTS) hardware and equipment to assess photosynthetic activity and vegetation health through remote sensing on Cubesat or Unmanned Aerial Vehicle (UAV) platforms. The proposed NDVI imaging payload is comprised of three main subsystems: an electrical system, a software system, and a hardware system. The electrical system includes a custom designed printed circuit board (PCB), a single cell 3.7 V lithium-polymer battery, voltage regulator circuitry components, and wiring harnesses and connectors. The software system employs a master and slave system that communicates through general purpose input/output (GPIO) pin responses. Raspberry Pi Zero computer boards serve as the central processing units (CPUs) of the hardware subsystem, which also consists of the Pi-Cam standard red/green/blue (RGB) and Pi No-IR near-infrared (NIR) camera modules. A PCB was designed to be compatible with the Cubesat standard and lightweight component selections make it a desirable option for UAV flights. Open-source GIMP image processing software was used to analyze results from ground-based testing and flight testing on a UAV and general aviation (GA) aircraft at various altitudes to validate proof of concept. Raw NDVI and NDVI color map images were created from GIMP post-processing. Analysis of the results suggests that the angle of incidence of the sun with respect to the view angle of the imaging payload is a significant factor in the resulting NDVI values. Terrain also appeared to have an effect on the results where shadows were cast from the sun at low angles of incidence. Therefore, in the northern hemisphere it is recommended that image collection is performed roughly within the hours of 10 AM and 2 PM between the vernal and autumnal equinoxes to ensure a solar altitude of at least 35°. For best results, it has been verified that image data should be collected at the local time of maximum solar altitude for a particular date and location of interest (typically around noon). The information gather by this research can be used by scientists and technologist to potentially provide a means of enhancing their research and further developing technologies of UAV applications and space-based systems