Trajectory Generation and Tracking Control for Aggressive Tail-Sitter Flights

We address the theoretical and practical problems related to the trajectory generation and tracking control of tail-sitter UAVs. Theoretically, we focus on the differential flatness property with full exploitation of actual UAV aerodynamic models, which lays a foundation for generating dynamically feasible trajectory and achieving high-performance tracking control. We have found that a tail-sitter is differentially flat with accurate aerodynamic models within the entire flight envelope, by specifying coordinate flight condition and choosing the vehicle position as the flat output. This fundamental property allows us to fully exploit the high-fidelity aerodynamic models in the trajectory planning and tracking control to achieve accurate tail-sitter flights. Particularly, an optimization-based trajectory planner for tail-sitters is proposed to design high-quality, smooth trajectories with consideration of kinodynamic constraints, singularity-free constraints and actuator saturation. The planned trajectory of flat output is transformed to state trajectory in real-time with consideration of wind in environments. To track the state trajectory, a global, singularity-free, and minimally-parameterized on-manifold MPC is developed, which fully leverages the accurate aerodynamic model to achieve high-accuracy trajectory tracking within the whole flight envelope. The effectiveness of the proposed framework is demonstrated through extensive real-world experiments in both indoor and outdoor field tests, including agile SE(3) flight through consecutive narrow windows requiring specific attitude and with speed up to 10m/s, typical tail-sitter maneuvers (transition, level flight and loiter) with speed up to 20m/s, and extremely aggressive aerobatic maneuvers (Wingover, Loop, Vertical Eight and Cuban Eight) with acceleration up to 2.5g

Innovative Tools For Planning, Analysis, and Management of UAV Photogrammetric Surveys

The Unmanned Aerial System (UAV) is widely used in the photogrammetric surveys both for structures and small areas. The geomatics approach, for the several applications where the 3D modeling is required, focuses the attention on the metric quality of the final products of the survey. As widely known, the quality of results derives from the quality of images acquisition phase, which needs an accurate planning phase. Actually, the planning phase is typically managed using dedicated tools, adapted from the traditional aerial-photogrammetric flight plan. Unfortunately, UAV flight has features completely different from the traditional one, hence the use of UAV for photogrammetric applications today requires a growth in the planning knowledge. The basic idea of the present research work is to provide a tool for planning a photogrammetric survey with UAV, called \u201cUnmanned Photogrammetric Office\u201d (U.Ph.O.), that considers the morphology of the object, the effective visibility of its surface, in the respect of the metric precisions. The usual planning tools require the classical parameters of a photogrammetric planning: flight distance from the surface, images overlaps and geometric parameters of the camera. The created \u201cOffice suite\u201d U.Ph.O. allows a realistic planning of a photogrammetric survey, requiring additionally an approximate knowledge of the Digital Surface Model (DSM) and the attitude parameters, potentially changing along the route. The planning products will be the realistic overlapping of the images, the Ground Sample Distance (GSD) and the precision on each pixel taking into account the real geometry. The different tested procedures, the solution proposed to estimates the realistic precisions in the particular case of UAV surveys and the obtained results, are described in this thesis work, with an overview on the recently development of UAV surveys and technologies related to them

Design of a variable-span morphing wing

The present work focuses on the study, design and validation of a variable-span morphing wing to be tted to the UAV \Olharapo". Using an optimization code, which uses a viscous two-dimensional panel method formulation coupled with a non-linear liftingline algorithm and a sequential quadratic programming optimization routine, na aerodynamic analysis is performed to estimate the optimal values of wing span which ensure minimum drag across the ight speed envelope. The UAV ies in a relatively short speed range - from about 12 m/s to 30 m/s. Near its maximum speed it is possible to obtain a 20% drag reduction with the variable-span wing in comparison with the original xed wing. A stability analysis is also performed to estimate the roll rate available with asymmetric span control. The variable-span wing matches the aileron in terms of roll power and maximum roll rate. It is concluded that roll control is possible with asymmetric span control. A new electro-mechanical actuation mechanism is developed using a simple and cheap rack and pinion system. The wing model is designed with graphical CAD/CAM tools and then a full scale model is built for bench testing the wing/actuator system. The concepts used on the morphing wing for both xed and movable part are considered simple and e ective. The actuation concept is also feasible but needs improvements in the attenuator. A powerful servo is also needed to more easily deploy the wing. Some future modi cations at structural level and ideas for an in-flight automatic span controller are also presented.O presente trabalho centra-se no estudo, concepcão e validação de uma asa de envergadura variável para aplicação no UAV \Olharapo". Usando um código de optimização, que usa uma formulação de painéis viscoso bidimensional acoplado a um algoritmo de linha sustentadora não-linear e uma rotina de optimização de programação sequencial quadrática, é realizada uma análise aerodinâmica para estimar os valores óptimos de envergadura de forma a garantir um arrasto mínimo para todas as velocidades do envelope de voo. O UAV opera numa gama de velocidades relativamente pequena - de 12 m/s a 30 m/s, sensivelmente. Próximo da velocidade máxima é possível obter uma redução de 20% no arrasto com a asa de envergadura variável em comparação com a asa fixa original. É realizada uma análise de estabilidade com o objectivo de estimar a taxa de rolamento disponível com controlo assimétrico de envergadura. O desempenho da asa de envergadura variável é idêntico ao da asa original com ailerons em termos de poder de rolamento e de taxa de rolamento. Conclui-se que o controlo de rolamento pode ser efectuado com controlo assimétrico da envergadura. É feita a concepcão de um novo sistema actuador eletro-mecânico recorrendo a um sistema simples de pinhão e cremalheira. O modelo da asa é projectado recorrendo a ferramentas CAD/CAM e posteriormente construído para que o sistema asa/actuador seja testado em bancada. Os conceitos usados na asa morphing para a parte fixa e móvel são considerados simples e efectivos. O sistema de actuação é funcional mas necessita de melhoramentos ao nível do atenuador e requer um servo mais potente para uma actuação da asa mais fácil. Algumas modicações futuras a nível estrutural e algumas ideias para o desenvolvimento de um controlador para regulação automática da envergadura são também apresentadas

Nearshore Bathymetry Estimation from Drone Video Using PIV Technique

This research introduces a novel method to estimate nearshore bottom topography using an unmanned aerial vehicle (UAV), or drone. The UAV was manipulated over the area of interest to film video, and the Particle image velocimetry (PIV) technique was then applied to analyze the video frames in order to retrieve the wave speeds. Under the shallow water conditions, the wave dispersion relation can be simplified in a manner such that when the wave speed is known, the water depth can be inferred. In other words, when wave speed is known, water depth can be inferred. After combining the inferred water depths at multiple points from within the area of interest, the bathymetry was constructed. To validate the method, individual waves were recorded in the nearshore breaking zone during two trials at Freeport, Texas, USA. We measured the significant difference in intensity across the recorded images, as the intensity had a larger signal-to-noise ratio, and this improved the implementation of the PIV algorithm. We then compared the PIVestimated water depth with field measurement and observations, finding that the water depth was overestimated by 13.5%, which was primarily explained by non-linear wave breaking effects. We then introduced a correction factor, reducing the estimation error to within 6% of the true observed water depth. Though there are limitations, this new approach can lower the cost of developing bathymetric maps in the nearshore and result in greater flexibility across space and time. Further improvements in equipment and work on developing better correction factors may result in still greater precision

Mission-Oriented Autonomy for Intelligent, Adaptive, and Multi-Agent Remote Sensing of Ice Sheets using Unmanned Aerial Systems

Throughout our history, humanity has been developing and progressing technology in order to help us better understand the world in which we live. As climate change becomes an increasingly urgent global crisis, scientists have been tasked with developing models for better understanding the complex dynamics involved, as well as to more accurately forecast the long term effects on our environment. With respect to sea level rise, both our knowledge of these dynamics and the accuracy of these models can be improved through the routine collection of crucial data concerning glacier ice thickness and bedrock topology. To accomplish this, innovative solutions are being developed by groups of inter-disciplinary research teams, combining fields such as earth-science, radar systems, data science, and aerospace engineering. Through this collaboration, we have the potential to leverage breakthroughs in unmanned systems technology and miniaturized, specialized sensors for comprehensive, precise, and routine data collection of key polar research objectives. As Unmanned Aerial Systems (UASs) have become more reliable research platforms in recent years, they now have the capability to perform these remote sensing operations at a reduced cost compared to manned operations, while also providing repeatable, precision tracking capabilities along flight lines, enabling the surveying of tightly-spaced grids, and removing human flight crews from hazardous polar environments. However, the payload, range, and wind constraints for these platforms severely restrict their operational sensing footprint. Additionally, UASs generally have a much smaller wingspan compared to manned aircraft typically used in Earth Science missions, which becomes a challenging factor for incorporating efficient directive antennas at the low operating frequencies required for glacial sounding. The aim of this work is to address these issues and to enhance mission efficiency and the overall quality of data collection for these operations through the implementation of onboard mission-oriented autonomy that includes cognitive decision-making for intelligent survey operations, adaptive functionalities, and a scalable, robust framework for multi-agent operations. As opposed to conventional methods for polar research operations which generally involve single-agent missions, using standard waypoint guidance and fixed-routes planned by human operators, the unique contributions of the developed mission-oriented autonomy in this work include: 1) Automated flight line generation for rapid and reliable mission planning of tightly-spaced flight lines required for cross-track synthetic aperture radar processes and surface clutter suppression, with required spacing based on the operating frequency of the onboard radar system. 2) Implementation of Dubins Path guidance methods into polar research operations for precision end-to-end survey of mission flight lines while taking into account the kinematic constraints of the fixed wing aircraft, as well as for efficiently traversing to and from a home loiter location during mission operations. 3) Cognitive, real-time optimal path planning through mission flight lines utilizing both deterministic and stochastic Traveling Salesman Problem heuristics. 4) Modifications to these Traveling Salesman Problem heuristics for ensuring safe, feasible, and reliable operations in real-time by taking into account aircraft range constraints. 5) Collaborative Multi-Agent survey operations utilizing space partitioning and Hungarian Assignment for distributed task allocation, as well as morphing potential fields for collision avoidance. 6) Modifications for Multi-Agent deployment scheduling to reduce inter-agent interference for sensitive radar systems to improve coherency of the collected data, and to rapidly and efficiently deploy agents into and out of survey areas. 7) Modifications for Heterogeneous flight operations for increasing operational capabilities through cross-platform collaboration. 8) Failsafe features to instill robustness in Multi-Agent operations with respect towards accommodating and adapting to single-agent system failures, by automatically re-planning collaborative survey operations. In this work, the motivation for the creation of this mission-oriented autonomy is discussed, along with the methodology of each of the autonomy features, and the framework for implementation onto UAS platforms. Case studies are conducted for past and future polar research deployments using unmanned systems to assess the potential improvements in operational capabilities and data collection for the developed autonomy compared to conventional methods. Finally, the developed autonomy is implemented onto an embedded system for preliminary flight testing and validation, as well as used for intelligent mission planning for a manned operation

Condition Assessment of Concrete Bridge Decks Using Ground and Airborne Infrared Thermography

Applications of nondestructive testing (NDT) technologies have shown promise in assessing the condition of existing concrete bridges. Infrared thermography (IRT) has gradually gained wider acceptance as a NDT and evaluation tool in the civil engineering field. The high capability of IRT in detecting subsurface delamination, commercial availability of infrared cameras, lower cost compared with other technologies, speed of data collection, and remote sensing are some of the expected benefits of applying this technique in bridge deck inspection practices. The research conducted in this thesis aims at developing a rational condition assessment system for concrete bridge decks based on IRT technology, and automating its analysis process in order to add this invaluable technique to the bridge inspector’s tool box. Ground penetrating radar (GPR) has also been vastly recognized as a NDT technique capable of evaluating the potential of active corrosion. Therefore, integrating IRT and GPR results in this research provides more precise assessments of bridge deck conditions. In addition, the research aims to establish a unique link between NDT technologies and inspector findings by developing a novel bridge deck condition rating index (BDCI). The proposed procedure captures the integrated results of IRT and GPR techniques, along with visual inspection judgements, thus overcoming the inherent scientific uncertainties of this process. Finally, the research aims to explore the potential application of unmanned aerial vehicle (UAV) infrared thermography for detecting hidden defects in concrete bridge decks. The NDT work in this thesis was conducted on full-scale deteriorated reinforced concrete bridge decks located in Montreal, Quebec and London, Ontario. The proposed models have been validated through various case studies. IRT, either from the ground or by utilizing a UAV with high-resolution thermal infrared imagery, was found to be an appropriate technology for inspecting and precisely detecting subsurface anomalies in concrete bridge decks. The proposed analysis produced thermal mosaic maps from the individual IR images. The k-means clustering classification technique was utilized to segment the mosaics and identify objective thresholds and, hence, to delineate different categories of delamination severity in the entire bridge decks. The proposed integration methodology of NDT technologies and visual inspection results provided more reliable BDCI. The information that was sought to identify the parameters affecting the integration process was gathered from bridge engineers with extensive experience and intuition. The analysis process utilized the fuzzy set theory to account for uncertainties and imprecision in the measurements of bridge deck defects detected by IRT and GPR testing along with bridge inspector observations. The developed system and models should stimulate wider acceptance of IRT as a rapid, systematic and cost-effective evaluation technique for detecting bridge deck delaminations. The proposed combination of IRT and GPR results should expand their correlative use in bridge deck inspection. Integrating the proposed BDCI procedure with existing bridge management systems can provide a detailed and timely picture of bridge health, thus helping transportation agencies in identifying critical deficiencies at various service life stages. Consequently, this can yield sizeable reductions in bridge inspection costs, effective allocation of limited maintenance and repair funds, and promote the safety, mobility, longevity, and reliability of our highway transportation assets