scholarly journals Influence of Propeller Overlap on Large-Scale Tandem UAV Performance

2019 ◽  
Vol 07 (04) ◽  
pp. 245-260
Author(s):  
Adrian B. Weishäupl ◽  
Stephen D. Prior
Keyword(s):  
Carbon Fiber ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Vertical Separation ◽  
Hovering Flight ◽  
Wide Range ◽  
Aerial Vehicle

This paper investigates the interference that arises from overlapping Unmanned Aerial Vehicle (UAV) propellers during hovering flight. The tests have been conducted on [Formula: see text] ultralight carbon fiber propellers using a bespoke mount and the RCBenchmark Series 1780 dynamometer at various degrees of overlap [Formula: see text] and vertical separation [Formula: see text]. A great deal of confusion regarding the losses that are associated with mounting propellers in a co-axial configuration is reported in the literature, with a summary of historical tandem helicopters having been conducted. The results highlight a region of beneficial overlap (0–20%), which has the potential to be advantageous to a wide range of UAVs.

scholarly journals Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Forest Monitoring ◽  
Machine Learning Techniques ◽  
Planted Forests ◽  
Systematic Analysis ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Aerial Vehicle

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

scholarly journals Recent Advances in Unmanned Aerial Vehicles Forest Remote Sensing—A Systematic Review. Part II: Research Applications

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 397
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Sustainable Management ◽  
Large Scale ◽  
Spectral Signature ◽  
Accurate Information ◽  
Data Interoperability ◽  
Critical Issues ◽  
Management Context ◽  
Aerial Vehicle

Forest sustainable management aims to maintain the income of woody goods for companies, together with preserving non-productive functions as a benefit for the community. Due to the progress in platforms and sensors and the opening of the dedicated market, unmanned aerial vehicle–remote sensing (UAV–RS) is improving its key role in the forestry sector as a tool for sustainable management. The use of UAV (Unmanned Aerial Vehicle) in precision forestry has exponentially increased in recent years, as demonstrated by more than 600 references published from 2018 until mid-2020 that were found in the Web of Science database by searching for “UAV”+“forest”. This result is even more surprising when compared with similar research for “UAV”+“agriculture”, from which emerge about 470 references. This shows how UAV–RS research forestry is gaining increasing popularity. In Part II of this review, analyzing the main findings of the reviewed papers (227), numerous strengths emerge concerning research technical issues. UAV–RS is fully applicated for obtaining accurate information from practical parameters (height, diameter at breast height (DBH), and biomass). Research effectiveness and soundness demonstrate that UAV–RS is now ready to be applied in a real management context. Some critical issues and barriers in transferring research products are also evident, namely,(1) hyperspectral sensors are poorly used, and their novel applications should be based on the capability of acquiring tree spectral signature especially for pest and diseases detection, (2) automatic processes for image analysis are poorly flexible or based on proprietary software at the expense of flexible and open-source tools that can foster researcher activities and support technology transfer among all forestry stakeholders, and (3) a clear lack exist in sensors and platforms interoperability for large-scale applications and for enabling data interoperability.

Fast Data Acquisition of Aerial Images Using Unmanned Aerial Vehicle System

2014 ◽  
Vol 3 (3) ◽  
pp. 162
Author(s):  
Norhadija Darwin ◽  
Anuar Ahmad
Keyword(s):  
Data Acquisition ◽  
Root Mean Square ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Digital Camera ◽  
Aerial Images ◽  
Mean Square ◽  
Fast Data Acquisition ◽  
Vehicle System ◽  
Aerial Vehicle

The present work discusses the technique and methodology of analysing the potential of fast data acquisition of aerial images using unmanned aerial vehicle system. This study utilizes UAV system for large scale mapping by using digital camera attached to the UAV. UAV is developed from the low-altitude photogrammetric mapping to perform the accuracy of the aerial photography and the resolution of the image. The Ground Control Points (GCPs) and Check Points (CPs) are established using Rapid Static techniques through GPS observation for registration purpose in photogrammetric process. The GCPs is used in the photogrammetric processes to produce photogrammetric output while the CP is employed for accuracy assessment. A Pentax Optio W90 consumer digital camera is also used in image acquisition of the aerial photograph. Besides, this study also involves image processing and map production using Erdas Imagine 8.6 software. The accuracy of the orthophoto is determined using the equation of Root Mean Square Error (RMSE). The final result from orthophoto is compared to the ground survey using total station to show the different accuracy of DEM and planimetric survey. It is discovered that root mean square errors obtained from UAV system are ± 0.510, ± 0.564 and ± 0.622 for coordinate x, y and z respectively. Hence, it can be concluded that the accuracy obtained from UAV system is achieved in sub meter. In a nutshell, UAV system has potential use for large scale mapping in field of surveying and other diversified environmental applications especially for small area which has limited time and less man power.

The Reynolds number and flaperon deflection influence taken into account when optimizing the wing airfoil of an unmanned aerial vehicle

2020 ◽  
Author(s):  
N.I. Kochurova ◽  
Ye.S. Parkhaev ◽  
N.V. Semenchikov
Keyword(s):  
Reynolds Number ◽  
Unmanned Aerial Vehicle ◽  
Multicriteria Optimization ◽  
Lift Coefficient ◽  
Reynolds Numbers ◽  
Horizontal Flight ◽  
Wide Range ◽  
Aerial Vehicle ◽  
Zero Values ◽  
Wing Airfoil

The paper considers the solutions to the multicriteria problem of optimizing the wing airfoil of a miniature unmanned aerial vehicle (MUAV) under various constraints. The study introduces the statement of the problem of multicriteria optimization of the airfoil shape, following the condition of MUAV horizontal flight, with an additional condition associated with a change in the flight Reynolds number of the MUAV wing. This statement of the problem allows us to optimize the airfoil, taking into account the load on the wing of the designed vehicle. The wing airfoil was optimized in a wide range of lift coefficients of Cya and Reynolds numbers. The study shows that taking into account the Reynolds number makes it possible to improve the quality of the result obtained during optimization, and introduces a technique for multicriteria optimization of the wing airfoil with sealed mechanization, i.e. with flaperon. Findings of research show that for equal values of the relative thickness, the mechanized airfoil obtained as a result of optimization has a lower center line camber (by 1.5%) than the optimized airfoil without mechanization, due to which a gain in the drag coefficient is achieved at close to zero values of the lift coefficient. The study shows how profitable the use of a wing airfoil with a flaperon on MUAV wings can be, in contrast to an airfoil without mechanization.

scholarly journals Large-Scale Particle Image Velocimetry From an Unmanned Aerial Vehicle

2015 ◽  
Vol 20 (6) ◽  
pp. 3269-3275 ◽  
Author(s):  
Flavia Tauro ◽  
Christopher Pagano ◽  
Paul Phamduy ◽  
Salvatore Grimaldi ◽  
Maurizio Porfiri
Keyword(s):  
Particle Image Velocimetry ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Particle Image ◽  
Image Velocimetry ◽  
Aerial Vehicle ◽  
Scale Particle

scholarly journals Never landing drone: Autonomous soaring of a unmanned aerial vehicle in front of a moving obstacle

2021 ◽  
Vol 13 ◽  
pp. 175682932110605
Author(s):  
Chris PL de Jong ◽  
Bart DW Remes ◽  
Sunyou Hwang ◽  
Christophe De Wagter
Keyword(s):  
Wind Velocity ◽  
Unmanned Aerial Vehicle ◽  
Hovering Flight ◽  
Energy Control ◽  
Control Module ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Soaring Flight ◽  
Autonomous Soaring ◽  
Moving Obstacle

Increasing endurance is a major challenge for battery-powered aerial vehicles. A method is presented which makes use of an updraft around obstacles to decrease the power consumption of a fixed-wing unmanned aerial vehicle. A soaring flight controller has been developed that can autonomously soar while the unmanned aerial vehicle keeps its relative position to that of a moving object. Multiple simulations have been performed to analyse the limitations of the soaring controller under different conditions. The effect of a change in wind velocity and updraft has been analysed. The simulations showed that an increase in updraft decreases the energy consumption of the flight controller. An increase in wind velocity results in a higher updraft requirement, while a decrease in the wind velocity requires less updraft. The simulations achieved sustained flight at 0% throttle. The controller has been validated experimentally using the updraft generated by a moving ship. The practical, autonomous tests reduced the average throttle down to 4.5% in front of a ship. The method presented in this study achieved successful hovering flight using an energy control module for longitudinal positioning.

Minimizing the number of wireless charging PAD for unmanned aerial vehicle–based wireless rechargeable sensor networks

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110559
Author(s):  
Yingjue Chen ◽  
Yingnan Gu ◽  
Panfeng Li ◽  
Feng Lin
Keyword(s):  
Sensor Networks ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Charging ◽  
Aerial Vehicles ◽  
Wireless Rechargeable Sensor Networks ◽  
Aerial Vehicle

In wireless rechargeable sensor networks, most researchers address energy scarcity by introducing one or multiple ground mobile vehicles to recharge energy-hungry sensor nodes. The charging efficiency is limited by the moving speed of ground chargers and rough environments, especially in large-scale or challenging scenarios. To address the limitations, researchers consider replacing ground mobile chargers with lightweight unmanned aerial vehicles to support large-scale scenarios because of the unmanned aerial vehicle moving at a higher speed without geographical limitation. Moreover, multiple automatic landing wireless charging PADs are deployed to recharge unmanned aerial vehicles automatically. In this work, we investigate the problem of introducing the minimal number of PADs in unmanned aerial vehicle–based wireless rechargeable sensor networks. We propose a novel PAD deployment scheme named clustering-with-double-constraints and disks-shift-combining that can adapt to arbitrary locations of the base station, arbitrary geographic distributions of sensor nodes, and arbitrary sizes of network areas. In the proposed scheme, we first obtain an initial PAD deployment solution by clustering nodes in geographic locations. Then, we propose a center shift combining algorithm to optimize this solution by shifting the location of PADs and attempting to merge the adjacent PADs. The simulation results show that compared to existing algorithms, our scheme can charge the network with fewer PADs.

scholarly journals Early Fire Detection Based on Aerial 360-Degree Sensors, Deep Convolution Neural Networks and Exploitation of Fire Dynamic Textures

2020 ◽  
Vol 12 (19) ◽  
pp. 3177 ◽  
Author(s):  
Panagiotis Barmpoutis ◽  
Tania Stathaki ◽  
Kosmas Dimitropoulos ◽  
Nikos Grammalidis
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Forest Fires ◽  
Large Scale ◽  
Computational Cost ◽  
Fire Detection ◽  
Adaptive Method ◽  
Field Of View ◽  
Aerial Vehicle ◽  
Remote Sensing Systems ◽  
Early Fire Detection

The environmental challenges the world faces have never been greater or more complex. Global areas that are covered by forests and urban woodlands are threatened by large-scale forest fires that have increased dramatically during the last decades in Europe and worldwide, in terms of both frequency and magnitude. To this end, rapid advances in remote sensing systems including ground-based, unmanned aerial vehicle-based and satellite-based systems have been adopted for effective forest fire surveillance. In this paper, the recently introduced 360-degree sensor cameras are proposed for early fire detection, making it possible to obtain unlimited field of view captures which reduce the number of required sensors and the computational cost and make the systems more efficient. More specifically, once optical 360-degree raw data are obtained using an RGB 360-degree camera mounted on an unmanned aerial vehicle, we convert the equirectangular projection format images to stereographic images. Then, two DeepLab V3+ networks are applied to perform flame and smoke segmentation, respectively. Subsequently, a novel post-validation adaptive method is proposed exploiting the environmental appearance of each test image and reducing the false-positive rates. For evaluating the performance of the proposed system, a dataset, namely the “Fire detection 360-degree dataset”, consisting of 150 unlimited field of view images that contain both synthetic and real fire, was created. Experimental results demonstrate the great potential of the proposed system, which has achieved an F-score fire detection rate equal to 94.6%, hence reducing the number of required sensors. This indicates that the proposed method could significantly contribute to early fire detection.

High-resolution Brillouin analysis in a carbon-fiber-composite unmanned aerial vehicle model wing

2016 ◽  
Author(s):  
Yonatan Stern ◽  
Yosef London ◽  
Eyal Preter ◽  
Yair Antman ◽  
Orel Shlomi ◽  
...  
Keyword(s):  
High Resolution ◽  
Carbon Fiber ◽  
Unmanned Aerial Vehicle ◽  
Fiber Composite ◽  
Vehicle Model ◽  
Carbon Fiber Composite ◽  
Aerial Vehicle
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