Multicopter Drone Research Articles

Spatiotemporal characterization of PM2.5, O3, and trace gases associated with East Asian continental outflows via drone sounding

East Asian continental outflows with PM2.5, O3, and other species may determine the baseline conditions and affect the air quality in downwind areas via long-range transport (LRT). To gain insight into the impact and spatiotemporal characteristics of airborne pollutants in East Asian continental outflows, a versatile multicopter drone sounding platform was used to simultaneously observe PM2.5, O3, CO2, and meteorological variables (temperature, specific humidity, pressure, and wind vector) above the northern tip of Taiwan, Cape Fuiguei, which often encounters continental outflows during winter monsoon periods. By coordinating hourly high-spatial-resolution profiles provided by drone soundings, WRF/CMAQ model air quality predictions, HYSPLIT-simulated backward trajectories, and MERRA-2 reanalysis data, we analyzed two prominent phenomena of airborne pollutants in continental outflows to better understand their physical/chemical characteristics. First, we found that pollutants were well mixed within a sounding height of 500 m when continental outflows passed through and completely enveloped Cape Fuiguei. Eddies induced by significant fluctuations in wind speeds coupled with minimal temperature inversion and LRT facilitated vertical mixing, possibly resulting in high homogeneity of pollutants within the outflow layer. Second, the drone soundings indicated exceptionally high O3 concentrations (70–100 ppbv) but relatively low concentrations of PM2.5 (10–20 μg/m3), CO2 (420–425 ppmv), and VOCs in some air masses. The low levels of PM2.5, CO2, and VOCs ruled out photochemistry as the cause of the formation of high-level O3. Further coordination of spatiotemporal data with air mass trajectories and O3 cross sections provided by MERRA-2 suggested that the high O3 concentrations could be attributed to stratospheric intrusion and advection via continental outflows. High-level O3 concentrations persisted in the lower troposphere, even reaching the surface, suggesting that stratospheric intrusion O3 may be involved in the rising trend in O3 concentrations in parts of East Asia in recent years in addition to surface photochemical factors.

An Urban Traffic Dataset Composed of Visible Images and Their Semantic Segmentation Generated by the CARLA Simulator

A dataset of aerial urban traffic images and their semantic segmentation is presented to be used to train computer vision algorithms, among which those based on convolutional neural networks stand out. This article explains the process of creating the complete dataset, which includes the acquisition of the images, the labeling of vehicles, pedestrians, and pedestrian crossings as well as a description of the structure and content of the dataset (which amounts to 8694 images including visible images and those corresponding to the semantic segmentation). The images were generated using the CARLA simulator (but were like those that could be obtained with fixed aerial cameras or by using multi-copter drones) in the field of intelligent transportation management. The presented dataset is available and accessible to improve the performance of vision and road traffic management systems, especially for the detection of incorrect or dangerous maneuvers.

Study of drone self-noise estimation for low frequency noise measurement by multicopter drone

We are developing low-frequency noise measurement system with multi-copter type drone. The biggest obstacle to measurements is drone self-noise. Therefor the system records environment noise and propeller rotation timing signal and removes the self-noise from the recording offline. For a high cancellation performance, accurate self-noise estimation is very important to remove self-noise from recordings. Focusing on the reproducibility of the self-noise for each rotation, we proposed a method for estimating self-noise at arbitrary rotations during flight from prerecording self-noise data. When the proposed system was mounted on a toy drone and its self-noise cancellation performance was evaluated, high cancellation performance was obtained in the low frequency region. In the study, In this paper, we report a method and its evaluation for estimating the self-noise of the propeller 1 axis from the rotation signal of the propeller axis of the drone.

Multicopter drone mass distribution impacts on viability, performance, and sustainability

Multicopter drone mass distribution impacts on viability, performance, and sustainability

Flow Structure around a Multicopter Drone: A Computational Fluid Dynamics Analysis for Sensor Placement Considerations

This study presents a computational fluid dynamics (CFD) based approach to determine the optimal positioning for an atmospheric turbulence sensor on a rotary-wing uncrewed aerial vehicle (UAV) with X8 configuration. The vertical (zBF) and horizontal (xBF) distances of the sensor to the UAV center to reduce the effect of the propeller-induced flow are investigated by CFD simulations based on the k−ϵ turbulence model and the actuator disc theory. To ensure a realistic geometric design of the simulations, the tilt angles of a test UAV in flight were measured by flying the drone along a fixed pattern at different constant ground speeds. Based on those measurement results, a corresponding geometry domain was generated for the CFD simulations. Specific emphasis was given to the mesh construction followed by a sensitivity study on the mesh resolution to find a compromise between acceptable simulation accuracy and available computational resources. The final CFD simulations (twelve in total) were performed for four inflow conditions (2.5 m s−1, 5 m s−1, 7.5 m s−1 and 10 m s−1) and three payload configurations (15 kg, 20 kg and 25 kg) of the UAV. The results depend on the inflows and show that the most efficient way to reduce the influence of the propeller-induced flow is mounting the sensor upwind, pointing along the incoming flow direction at xBF varying between 0.46 and 1.66 D, and under the mean plane of the rotors at zBF between 0.01 and 0.7 D. Finally, results are then applied to the possible real-case scenario of a Foxtech D130 carrying a CSAT3B ultrasonic anemometer, that aims to sample wind with mean flows higher than 5 m s−1. The authors propose xBF=1.7 m and zBF=20 cm below the mean rotor plane as a feasible compromise between propeller-induced flow reduction and safety. These results will be used to improve the design of a novel drone-based atmospheric turbulence measurement system, which aims to combine accurate wind and turbulence measurements by a research-grade ultrasonic anemometer with the high mobility and flexibility of UAVs as sensor carriers.

Mapping The Agriculture Land of The Land Farmers in The South Coast of Kulon Progo

The south coast land of Kulon Progo on the beginning was sandy and infertile soil. The land then was converted into agriculture land, chilli farm based on the idea of the agriculture expert, Mr. Karman. This study aimed to map the agriculture land in Bidadara coast, Panjatan district, Kulon Progo because of the the success of the coastal farmers on producing an abundance of chilli harvest. The method used was interviews and field observation. The deviced used for mapping was DJI Mavic 2 Pro multicopter drone operated approximately for 20 minutes. The result of this study was aerial photos of drone shots with a height of 20 meters, 30 meters, and 50 meters above ground level onto the soil conditions adjacent to Bidara Beach, Panjatan, Kulon Progo. It was seen that the stretch of coastal land was planted with coconut trees and chilies. Hence, no wonder that the coastal land farmers are rich because of fantastic income from the farm. It is proven that the cultivation of this chili plant can improve the economy of the farming community on the South Coast of Kulon Progo.

Online estimation of unknown aerodynamic forces acting on AWE systems

• An EKF can be used for estimating online unknown aerodynamics forces that act on AWE systems. • The control performance of AWE systems can be improved by considering the estimated aerodynamic forces. • By using the EKF, less sensors are necessary to implement nonlinear control laws. • The EKF use increases the robustness of the AWE system in the presence of different sources of uncertainties. • The EKF allows for getting reliable estimations of the aerodynamic coefficients. Airborne Wind Energy systems (AWE) represent a promising solution to environmental challenges that has revolutionized research in the wind industry. The studied AWE system in this work is equipped with a multicopter drone in order to perform take-off and landing maneuvers and the objective consists in presenting an estimation strategy based on an Extended Kalman Filter (EKF) to obtain accurate estimation of the aerodynamic forces needed to improve the performance of the proposed control law for the considered prototype in this study. The proposed method is implemented and tested in a numerical and experimental environment. The obtained results show the effectiveness of the introduced method at estimating unknown forces that act on the system despite the presence of several sources of uncertainty: neglected nonlinearities, poorly known parameters, physical constraints, etc. Moreover, we show that the knowledge of these forces allows one to improve the robustness of the studied AWE system during its take-off and landing phases.

The Structural Design and Aerodynamics Analysis for a Hybrid VTOL Fixed-Wing Drone for Parcel Delivery Applications

A number of companies are experimenting with multicopter drones to deliver items to clients. Because electric planes have a restricted range, their flight range is usually limited. However, if propelled by gasoline, electric multicopter drones can only travel a short distance because of high power consumption and noise difficulties. Despite their lower aerodynamic efficiency than fixed-wing aircraft, multicopters' ability to perform vertical take-off and landing (VTOL) makes them an ideal delivery vehicles. A hybrid fixed-wing VTOL system with a tilting system that alters the flight mode could be an upgradeto the current design of hybrid fixed wing VTOL. The goal is to effectively manufacture a fixed-wing drone with an appropriate structural design and a functional tilting mechanism that can take off vertically. SolidWorks and SIMNET aero were the two approaches used throughout the design software. The drone's aerodynamic qualities were investigated in order to better understand its behaviour, such as range of flight at a given altitude, stall speed, and maximum lift created, in order to determine the maximum parcel weight the drone can carry. The drone was built using SolidWorks 3D-Solid modelling and SIMNET aero design software. The tilting mechanism is 3D printed with Polylactic Acid (PLA) material since it is both light and strong. The structural strength can also be altered by changing the in-fill. After the drone was manufactured,numerous test flights were made to examine the drone's actual behaviour and enhance its functionality. The drone's theoretical stall speed was determined to be 12.74 m/s with a maximum payload of 500g and 11.43 m/s at no load. The maximum glide distance was estimated to be 1.2 kilometres. The drone yaws to the left during test flights at a rate of 63.43 degrees per second and 4.879 degrees per second at 50% throttle. It slanted to the front, nose down, with a weight of 516 g while support was given at the tip of the left wing. The pitch rate was 2.5 degrees per second without a payload and 3.12 degrees per second with the 516g payload. With further design and calibration advancements, experimental findings that are comparable to theoretical outcomes might be possible.

Assessment of Unmanned Aerial Vehicle Use Opportunities in Forest Road Project (Düzce Sample)

Forest roads are important infrastructure facilities that enable forestry activities to continue without interruption. These infrastructure facilities are very important in terms of protection and maintenance of forests, safe transportation of the produced property, afforestation, recreation, and transportation to forest fires as soon as possible. Today, an advantageous environment has been created by the widespread use of Geographic Information Systems (GIS) software, the increase in its use, as well as the integration of clearer and reliable information within the framework of sensitive forestry understanding, with the acquisition of high-resolution images with Unmanned Aerial Vehicles (UAV). This study, with the help of UAV data and GIS on forest roads, which serve as the basic infrastructure in the fulfilment of forestry activities, for forest road design and excavation-filling calculations, drones etc. made to demonstrate the applicability of the technologies. The study was carried out on the 164 coded B Type Forest Road belonging to the Cumaova Forestry Directorate affiliated with the Düzce Forestry Operations Directorate. In line with the study, first of all, data were obtained with a multi-copter drone. A Digital Terrain Model (DTM) of the study area was produced with the raw data obtained. The produced DTM data was compared with the 12.5 m Digital Elevation Model (DEM) data showing the land structure before the road was built. At the last stage of the study, the height and position data obtained from the road line with ground measurements and the excavation-fill amounts were compared using the RoadEng software. In the light of the results obtained in this study, it is thought that safer and more precise data can be obtained in forest road design studies, and it can provide a practical approach to road planning studies for planners, decision-makers and practitioners.

Aeroacoustic installation effects in multi-rotorcraft: Numerical investigations of a small-size drone model

The noise associated with the growing presence of unmanned aerial vehicles such as professional drones is becoming a concern. The buzzing noise emitted by multicopter drones is particularly distracting and annoying. The root mechanisms causing this tonal noise in multicopter configurations are however poorly understood and constitute the focus of this study. We developed a hybrid methodology that couples unsteady Reynolds-Averaged Navier-Stokes simulations with a computational aeroacoustic approach based on the Finite Element Method. This has permitted quantifying propeller-propeller and propeller-airframe aerodynamic installation effects, and the airframe scattering effects. The methodology is validated by comparing the predicted tones with existing acoustic measurements in the literature. The aerodynamic simulations indicate that the dominant sound sources are due to the unsteady interactions of the blade with the other propellers and supporting struts. This necessitates simulating the entire system in order to obtain realistic fluctuations of the aerodynamic forces. Similarly, the sound directivity results indicate that the acoustic scattering by the airframe has also a significant effect, both in the geometrical near- and far-field of the drone.

Computational aeroacoustics of quadcopter drones

Multicopter drones have a complex geometry involving several rotors. Therefore, computational resources could hinder their aeroacoustics modelling and simulation. Furthermore, such simulations require solving the aerodynamics at different scales (propellers and fuselage) and the sound spectrum for observers away from the drone. This paper presents a Computational Fluid Dynamics (CFD) study of quadcopter aeroacoustics. The computational method combines CFD in the framework of Reynolds-Averaged Navier–Stokes with the Ffowcs Williams-Hawkings (FW-H) model for a multi propeller drone. Moreover, we have used the rotor’s virtual blade model (VBM) to obtain the momentum sources as a first-order approximation. We apply the above approach to a quadcopter drone for hovering and forward flight conditions and analyse the aeroacoustics footprints. The predicted Octave Band Sound Levels are in good agreement with experimental data. We demonstrate that the above approach can model multi-propeller drones accurately at a moderate computational cost.

Development of noise measurement technology using multi-copter drone

Development of noise measurement technology using multi-copter drone

Robotic Elytra: Insect-Inspired Protective Wings for Resilient and Multi-Modal Drones

Winged drones that fly in close proximity to obstacles or that are capable of aerial and terrestrial locomotion can benefit from protective systems that prevent damage to delicate aerial structures. Existing protective solutions focus on multi-copter drones and consist of adding structures, such as cages, mechanisms and instruments that add weight and drag. Here we describe a protective strategy for winged drones that mitigates the added weight and drag by means of increased lift generation and stall delay at high angles of attack. The proposed structure is inspired by the wing system found in beetles and consists of adding an additional set of retractable wings, named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">elytra</i> , which can rapidly encapsulate the main folding wings when protection is needed.

ИМИТАЦИОННОЕ МОДЕЛИРОВАНИЕ С ПОМОЩЬЮ ВИРТУАЛЬНОГО ОКРУЖЕНИЯ РЕЖИМОВ УПРАВЛЕНИЯ ЛЕТАЮЩИМИ АППАРАТАМИ НА ЛУННОЙ СТАНЦИИ ДЛЯ ИЗУЧЕНИЯ ОПЕРАТОРСКОЙ ДЕЯТЕЛЬНОСТИ В ИЗОЛЯЦИОННЫХ ЭКСПЕРИМЕНТАХ

The survey is focused on the applicability of virtual reality(VR) and 3D immersive technologies for isolation studies of the human-robot interaction during intravehicular activities (IVA) and scenarios of pilotless vehicles (PVs) operations on a lunar station. The investigation resulted in covering the prototyped multicopter drones for inspecting closed environments on Earth and future creation of appropriate VR models, and proposing off-line PVs analogous to the NASA Free-Flyers Units Astrobee, and VirSim system for use on the lunar station. The imitative VR models and suggested research tasks include the following: 1) PVs scenarios, routing and scheduling, 2) modeling autonomous navigation and control (local positioning and navigation) inside the station, 3) manual piloting, 4) virtual and real control panels, 5) comparison of displays representing PVs cameras stream, 2D-electronic maps and real-time 3D-image, 6) PVs scenarios for potential danger to the lunar station, and support of response to unexpected events. Knowledge from the isolation studies can substantiate guidelines on PVs operations aboard habitable lunar stations.

Field experiments to operationalize in situ burning as a response method in Norwegian waters

ABSTRACT NOFO (Norwegian Clean Seas Association for Operating Companies) and NCA (Norwegian Coastal Administration) are cooperating closely to operationalize in situ burning as a response method in Norwegian waters. After introductory experiments during Oil on water 2016 together with S. L. Ross and SINTEF, NOFO and NCA have conducted in situ burn experiments in fire booms during Oil on water 2018 and 2019. These experiments included use of net to capture burn residue, igniters to start the fire when dropped from a multicopter drone, use of sensor packages from multicopter drones to monitor fire gases and soot in various parts of the smoke plume, and finally personnel in work boats taking surface samples and operating sensors to identify gases that might be hazardous to people. Both crude oil and fuel oils were burned, approximately 6 m3 for each burn. To our knowledge such field experiments have not been carried out before. The presentation will focus on operational aspects including photos and video footage, but also refer some findings from sensors and samples that might be hazardous to the environment as well as personnel.

Quadcopter drones swarm aeroacoustics

Swarms of drones is an emerging field of research and technology. Multicopter drones are noisy machines, and the noise effects would increase for a swarm. It is, therefore, essential to understand what flight formation conditions would reduce noise emissions. This study concerns the noise induced by drone swarms. We developed a high-resolution computational methodology for predicting aeroacoustic footprints emitted from a swarm of multi-copter drones. We show that a V-flight formation emits less sound pressure level noise than a U-shape (or rectangular) formation. We also demonstrate that the V-shape flight formation induces reduced drag, thus saving energy. This research's impact is broad, including defence and security, public health, transportation, and surveillance, among others.

Quantifying the Effects of Vibration on Medicines in Transit Caused by Fixed-Wing and Multi-Copter Drones

The concept of transporting medical products by drone is gaining a lot of interest amongst the medical and logistics communities. Such innovation has generated several questions, a key one being the potential effects of flight on the stability of medical products. The aims of this study were to quantify the vibration present within drone flight, study its effect on the quality of the medical insulin through live flight trials, and compare the effects of vibration from drone flight with traditional road transport. Three trials took place in which insulin ampoules and mock blood stocks were transported to site and flown using industry standard packaging by a fixed-wing or a multi-copter drone. Triaxial vibration measurements were acquired, both in-flight and during road transit, from which overall levels and frequency spectra were derived. British Pharmacopeia quality tests were undertaken in which the UV spectra of the flown insulin samples were compared to controls of known turbidity. In-flight vibration levels in both the drone types exceeded road induced levels by up to a factor of three, and predominant vibration occurred at significantly higher frequencies. Flown samples gave clear insulin solutions that met the British Pharmacopoeia specification, and no aggregation of insulin was detected.

Estimating of the noise generated by multi-copter drone

Estimating of the noise generated by multi-copter drone

Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields

Adaptive Navigation (AN) control strategies allow an agent to autonomously alter its trajectory based on realtime measurements of the environment. Compared to conventional navigation methods, these techniques can reduce required time and energy to explore scalar characteristics of unknown and dynamic regions of interest (e.g., temperature, concentration level). Multiple Uncrewed Aerial Vehicle (UAV) approaches to AN can improve performance by exploiting synchronized spatially-dispersed measurements to generate realtime information regarding the structure of the local scalar field, which is then used to inform navigation decisions. This article presents initial results of a comprehensive program to develop, verify, and experimentally implement mission-level AN capabilities in three-dimensional (3D) space using our unique multilayer control architecture for groups of vehicles. Using our flexible formation control system, we build upon our prior 2D AN work and provide new contributions to 3D scalar field AN by a) demonstrating a wide range of 3D AN capabilities using a unified, multilayer control architecture, b) extending multivehicle 2D AN control primitives to navigation in 3D scalar fields, and c) introducing state-based sequencing of these primitive AN functions to execute 3D mission-level capabilities such as isosurface mapping and plume following. We verify functionality using high-fidelity simulations of multicopter drone clusters, accounting for vehicle dynamics, outdoor wind gust disturbances, position sensor inaccuracy, and scalar field sensor noise. This paper presents the multilayer architecture for multivehicle formation control, the 3D AN control primitives, the sequencing approaches for specific mission-level capabilities, and simulation results that demonstrate these functions.

Mud Volcanism at the Taman Peninsula: Multiscale Analysis of Remote Sensing and Morphometric Data

Mud volcanism is observed in many tectonically active regions worldwide. One of the typical areas of mud volcanic activity is the Taman Peninsula, Russia. In this article, we examine the possibilities of multiscale analysis of remote sensing and morphometric data of different origins, years, scales, and resolutions for studying mud volcanic landscapes. The research is exemplified by the central-northern margin of the Taman Peninsula, where mud volcanism has only been little studied. The data set included one arc-second gridded Advanced Land Observing Satellite World three-dimensional (3D) digital surface model (AW3D30 DSM); a Corona historical declassified satellite photography; high-resolution imagery from an unmanned aerial survey (UAS) conducted with a multi-copter drone DJI Phantom 4 Pro, as well as a series of 1-m gridded morphometric models, including 12 curvatures (minimal, maximal, mean, Gaussian, unsphericity, horizontal, vertical, difference, vertical excess, horizontal excess, accumulation, and ring one) derived from UAS-based images. The data analysis allowed us to clarify the conditions of neotectonic development in the central-northern margin of the Taman Peninsula, as well as to specify manifestations of the mud volcanism in this region. In particular, we were able to detect minor and weakly topographically expressed mud volcanic features (probably, inactive gryphons, and salses), which are hidden by long-term farming practice (e.g., ploughed and covered by soil).