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The present project is dealing with the finalization of a drone following the master thesis developed the previous years. It starts with a brief introduction of the work performed on the drone throughout the years. A platform is designed in order to carry the camera assembly. Extreme loading cases are test validating the effectiveness of the platform. Static analysis is performed in each case testing the stress distribution. The fabricated main landing gears are to be mounted on the first airframe. That end an L-shaped bracket made from aluminum alloy 7075 serves as the link between the main landing gears and the airframe. The stress distribution of three designs is explored performing static analysis. Later on, visibility is provided to the camera and the internal electronic parts are fixed to position. Finally, the total mass is computed and the longitudinal stability is validated.
UAV --- Drone --- Ingénierie, informatique & technologie > Ingénierie aérospatiale
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Aerospace engineering --- Aerospace engineering. --- Aeronautical engineering --- aircraft --- UAV --- aircraft maintenance --- aircraft safety --- Aeronautics --- Astronautics --- Engineering --- uav
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In this thesis, a review of the history of blended wing bodies has been done and the various advantages that blended wing bodies offer has been exposed. The increased aerodynamic per- formance as well as noise reduction assures blended wing bodies a bright future. The goal of the thesis was to aerodynamically study a blended wing body UAV and propose a new enhance geometry. To do that, two different methods of analysis were first validated through comparison with expe- rimental results of simple geometries (NACA wings). Those two methods included a low-fidelity one, PanAir and a higher fidelity one, SU2. PanAir results turned out to be quite accurate pro- vided that the drag coefficient was corrected. Some limitations of PanAir have, however, been highlighted namely when it was applied to configurations comprising flaps. SU2 showed better results but its computation time was much more important. A detailed analysis of the baseline design of the UAV was then performed. Different aerody- namic coefficients were investigated as well as the influence of parameters of the flow. The influence of sideslip angle, control surfaces and propulsion has been studied. Once the baseline geometry had been analysed, a parametric model of the geometry has been built. The idea was to change the geometry in order to improve the lift to drag ratio. First, the different parameters susceptible of being changed were studied separately to define the final set of varying parameters and their range of values. A combination of the different parameters led to the study of 1024 different cases that were all compared to one another in order to find the one that maximized the lift to drag ratio while maintaining the required lift. A new geometry has thus been proposed. The new geometry has been studied and compared to the old one to assess if it improved the aerodynamic performance. It turned out the new geometry induced an increase of 7% of the lift to drag ratio. The behaviour of the UAV when facing crosswind appeared to also be improved. Finally, a sensitivity analysis on the Reynolds was performed to see if a future wind tunnel test campaign on a reduced size model could be possible. Trends showed that it was safe to analyse the UAV at different Reynolds number when the presence of thrust was ignored. The introduction of thrust led to some dependencies on the Reynolds pointing to the fact that a wind tunnel test should be performed cautiously.
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This thesis focuses on the design of an experimental test bench optimised for fast and efficient measurements using an automatic processing of the test parameters. This test bench has been developed to characterise the aerodynamic performances of a single ducted fan UAV developed by the start-up Fleye - Flying Robot. The UAV and its aerodynamic characteristics are determined based on the interpretation of experimental measurements in the second part of this work. It includes a discussion on the main ducted fan aerodynamic effects such as the ram drag, the improved propeller efficiency and the control surfaces authority inside a duct. Furthermore, the potential of this test bench for performance optimisation of the UAV current design has been illustrated through a case study discussing the influence of the control surface geometry. Finally, the stability of the UAV and its design parameters have been discussed to provide information and guidelines for improvements of the current Fleye UAV prototype.
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The importance of biodiversity no longer needs to be demonstrated. The conservation of this heritage requires data whose collection methodology may vary according to the taxon studied and the target habitat. The constant evolution of technology allows new approaches to be developed in order to increase the quantity and/or quality of these data, in particular by studying new species and habitats. For several years, UAVs (unmanned aerial vehicles) have contributed to the enhancement of this database through imagery. To date, very few studies provide information on the effectiveness of UAVs for bioacoustic monitoring. Therefore, this master’s thesis aims to evaluate the potential of UAVs for bioacoustic monitoring of birds and bats by means of tests carried out under controlled conditions, i.e. by playing soundtracks of these taxa. The main objective is to compare detection distances and probabilities between UAVs (quadcopter & fixed-wing) and ground recordings. A few tests were also conducted in vivo to get a first insight into the effectiveness of this technique compared to standard methods: point counts (birds) and passive ground recordings (bats). All tests were conducted in Wallonia (Belgium). The songs of 9 bird species and the calls of 5 bat species, corresponding to a representative sample of the sound variability in terms of frequency and intensity, were played through a loudspeaker placed at different distances from the drone. This experiment was repeated at several altitudes. The effective detection radius (EDR) is lower for UAV-based recordings than ground-based recordings. Bats detectability is sensitive to altitude making the overall EDR twice smaller for a microphone flying at 5 m than for ground recordings. However, for the majority of bird species (5 out of 9), the EDR remains close for both methods (difference ≤ 20%) regardless of altitude. Under in vivo conditions, the drone has always detected fewer individuals than standard methods for both taxa. These initial results lead to the conclusion that UAV-based bioacoustic monitoring underestimate reality and cannot therefore substitute standard monitoring methods in the study area. For avian surveys, this method could be complementary to traditional ones in order to obtain data on the diversity or presence of target species in areas difficult to access for human beings. However, the poor performance of chiropterans tests does not justify such use. Obviously these results are only valid for our equipment, hence the use of quieter drones will clearly improve them. Extensive testing in less accessible areas such like tropical canopies should therefore be considered to reinforce these conclusions.
UAV --- drone --- bird --- bat --- bioacoustics --- monitoring --- Sciences du vivant > Sciences de l'environnement & écologie
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With the advent of climate change comes the fear wildfires will become a rising concern in the near future as is hinted by several environmental studies. This fear has already become a reality for some parts of the globe. This work implements and compares different deep learning architectures for flame semantic segmentation on RGB images of fires occurring in a natural environment taken from the ground or from an unmanned aerial vehicle (UAV). The Corsican Fire Database is exploited after comparing it to other candidate public datasets. Results are compared in terms of the intersection over union (IoU), the mean squared error (MSE), the binary accuracy and the recall metrics as well as their number of network parameters. The implemented architectures are the FLAME U-Net, the DeepLabv3+ architecture considering the EfficientNet-B4 and the ResNet-50 backbones, the Squeeze U-Net as well as the ATT Squeeze U-Net. Notable among the evaluated architectures, the DeepLabV3+ with an EfficientNet backbone was the one that achieved the best results with an IoU of 0.93 and a recall of 0.967 while exploiting 22M parameters; and the ATT Squeeze U-Net that scored very decently with an IoU of 0.893, a recall of 0.928 and the least amount of network parameters (885K). All implementations were made public.
deep learning --- segmentation --- forest fires --- uav --- corsican fire database --- Ingénierie, informatique & technologie > Sciences informatiques
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Nowadays, drone deliveries and urban air mobility are in conception and would arrive in our lives in the near future. These firsts are more often multi-rotor VTOL UAVs. This configuration is designed in order to operate in urban environments. The drones are likely to expose regularly to communities significant levels of noise. At the moment, no acoustic regulation exists to decrease the impact of disturbance in populated areas. However, the purpose of this research is to obtain a first understanding of the noise produced by a sUAV and on the impact on observers in the surroundings. Acoustic measurements of a sUAV multi-rotors have been performed in a free environment on the campus of the von Karman Institute for Fluid Dynamics. The recordings were conducted when the drone was hovering, flying over, tilting and in transition. The processing of the pressure data was focused on the power spectrum, the spectrogram and on three Sound Quality Metrics in order to give an evaluation of the noise annoyance. The power spectra and the spectrograms reveal that for all maneuvers except the hover, the main BPF peak takes a larger range of frequencies and these lasts are varying because of the varying rotational speed of the front and rear propellers. Also, they show that over 3000 Hz, the tonal noise becomes hidden by the broadband one which becomes dominant. Concerning the Sound Quality Metrics, they show that the overall Psychoacoustic Annoyance score is higher for the fly-over and transition maneuvers compared to the hovering flight. Therefore, the analysis with these different tools shows that the fly-over and the transition phase are the more annoying maneuvers for the human ear and have a greater impact on the community. However, the purpose of this research is to obtain a first understanding of the noise produced by a sUAV and on the impact on observers in the surroundings. Acoustic measurements of a sUAV multi-rotors have been performed in a free environment on the campus of the von Karman Institute for Fluid Dynamics. The recordings were conducted when the drone was hovering, flying over, tilting and in transition. The processing of the pressure data was focused on the power spectrum, the spectrogram and on three Sound Quality Metrics in order to give an evaluation of the noise annoyance. The power spectra and the spectrograms reveal that for all maneuvers except the hover, the main BPF peak takes a larger range of frequencies and these lasts are varying because of the varying rotational speed of the front and rear propellers. Also they show that over 3000 Hz, the tonal noise becomes hidden by the broadband one which becomes dominant. Concerning the Sound Quality Metrics, they show that the overall Psychoacoustic Annoyance score is higher for the fly-over and transition maneuvers compared to the hovering flight. Therefore, the analysis with these different tools shows that the fly-over and the transition phase are the more annoying maneuvers for the human ear and have a greater impact on the community.
Drone --- Aeroacoustics --- Noise --- Experiment --- Psychoacoustics --- Multi-Rotors --- UAV --- Ingénierie, informatique & technologie > Ingénierie aérospatiale
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This book is a reprint of the Special Issue “Intelligent Autonomous Decision-Making and Cooperative Control Technology of High-Speed Vehicle Swarms”,which was published in Applied Sciences.
hypersonic vehicle --- steady-state cruise --- aircraft parameter --- neural network --- cooperative guidance --- model prediction control --- multi-missile cooperative control --- multi-constraint cooperative guidance --- distributed control --- MAS --- flight control --- fixed-wing UAV --- UAV swarm formation --- distributed ad hoc network --- consistency theory --- formation obstacle avoidance --- multi-UAV --- deep deterministic policy gradient --- cooperative penetration --- dynamic-tracking-interceptor component --- swarm control --- distributed swarm --- dynamic task planning --- task assignment --- event-trigger --- UAV–UGV --- cooperative engagement --- optimal control --- time-varying output formation --- formation keeping --- n/a --- UAV-UGV
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Earth Observations (EO) encompasses different types of sensors (e.g., SAR, LiDAR, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in which ground observations may not be possible due to physical and/or political constraints. EO can provide high spatial, temporal and spectral resolution, stereo-mapping and all-weather-imaging capabilities, but not by a single satellite at a time. Improved satellite and sensor technologies, increased frequency of satellite measurements, and easier access and interpretation of EO information have all contributed to the increased demand for satellite EO data. EO, combined with complementary terrestrial observations and with physical models, have been widely used to monitor geohazards, revolutionizing our understanding of how the Earth system works.
LiDAR --- InSAR --- remote sensing --- earthquake --- UAV --- landslide --- land subsidence --- earth observation --- surface displacement --- geohazards --- deformation --- optical --- damage assessment
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This book explores the economic and broader societal rationale for using unmanned aerial vehicle (UAV) or "drone- technologies as a complement to the current transport and logistics systems in several use cases in East Africa. The specific use cases examined include medical goods deliveries, food aid delivery, land mapping and risk assessment, agriculture, and transport and energy infrastructure inspection. Across these applications, the case for using UAVs is examined within the context of logistics objectives-total operating costs, speed, availability, and flexibility-as well as human, or societal, objectives. In the public health use case, as more low- and middle-income countries explore opportunities to improve efficiency and performance in their health supply chains and diagnostics networks, they face myriad choices about how best to use UAVs to improve product availability and public health outcomes and to reach the last mile. The high-level findings from this analysis are that, if examining commodity categories individually and looking exclusively at costs, delivery with UAVs in general is still more expensive for most categories. Although the cost is still higher, the most cost-effective use case examples include the transport of laboratory samples to selected destinations and delivery of life-saving items and blood. However, "layering- several use cases can provide efficiencies and cost savings by allocating fixed costs across a greater number of flights and maximizing capacity and time utilization. From the perspective of public decision-makers, the cost effectiveness of UAVs cannot be analyzed without looking at the public health benefits, which may be substantial. Drone application in the other use cases examined in this book, such as mapping, risk assessment, and agriculture, is relatively more common than cargo drone operations, and the existing pilot initiatives in East Africa have delivered impressive results for speed and quality (precision). Food aid delivery by drones is still mostly at a planning, rather than implementation, stage. Drone applications are rapidly evolving, and several use cases could gain impact and scale over the coming years.
Cost Benefit Analysis --- Disruptive Technology --- Drone --- Food Aid --- Infrastructure --- Logistics --- Supply Chain --- UAS --- UAV --- Unmanned Aerial Vehicle --- Unmanned Aircraft System
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