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[IEEE 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC) - San Diego, CA, USA (2019.9.8-2019.9.12)] 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC) - Enabling Air-to-Air Wideband Channel Measurements between Small Unmanned Aerial Vehicles with Optical Fibers
摘要： In order to ensure safe and ef?cient operation and to prevent collisions, unmanned aerial vehicles (UAVs) need to communicate with each other with high reliability. To design respective communication systems, accurate air-to-air (A2A) channel models are needed, especially for urban environments, where the channel characteristics are hard to predict due to rich multipath propagation, diffractions and non line of sight (LOS) conditions. For these models, channel measurements in different scenarios are inevitable to model the real-world communication channel. However, small sized UAVs are very limited in carrying payload and in power supply, making it dif?cult or often impossible to use high performing channel-sounding hardware equipment. As a result, less resource demanding hardware with lower performance in the sense of clock synchronization, time resolution or dynamic range is usually applied leading to a limited propagation channel characterization. In this work, we describe a measurement setup that allows using arbitrary channel sounder hardware by exploiting analog optical links in order to enable A2A wideband channel measurements between small sized UAVs. We extend the operation of our MEDAV RUSKDLR channel sounder by guiding a 100 MHz bandwidth radio frequency (RF) signal at 5.2 GHz through two 600 m long optical ?bers attached on two hexacopters after being converted with high bandwidth converters and show the feasibility of this setup with ?rst ?ight trials in an urban scenario.
关键词： Experimental Setup,Optical Fibers,Air-to-Air,Unmanned Aerial Vehicle,Channel Measurement
更新于2025-09-23 15:21:01
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Monitoring of Strain and Temperature in an Open Pit Using Brillouin Distributed Optical Fiber Sensors
摘要： Marble quarries are quite dangerous environments in which rock falls may occur. As many workers operate in these sites, it is necessary to deal with the matter of safety at work, checking and monitoring the stability conditions of the rock mass. In this paper, some results of an innovative analysis method are shown. It is based on the combination of Distributed Optical Fiber Sensors (DOFS), digital photogrammetry through Unmanned Aerial Vehicle (UAV), topographic, and geotechnical monitoring systems. Although DOFS are currently widely used for studying infrastructures, buildings and landslides, their use in rock marble quarries represents an element of peculiarity. The complex morphologies and the intense temperature range that characterize this environment make this application original. The selected test site is the Lorano open pit which is located in the Apuan Alps (Italy); here, a monitoring system consisting of extensometers, crackmeters, clinometers and a Robotic Total Station has been operating since 2012. From DOFS measurements, strain and temperature values were obtained and validated with displacement data from topographic and geotechnical instruments. These results may provide useful fundamental indications about the rock mass stability for the safety at work and the long-term planning of mining activities.
关键词： temperature,brillouin shift frequency,geotechnical monitoring system,strain,robotic total station,marble quarry,distributed optical fiber sensors,unmanned aerial vehicle
更新于2025-09-23 15:19:57
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Analysis of Positional and Geometric Accuracy of Objects in Survey with Unmanned Aerial Vehicle (UAV)
摘要： This study aimed the analysis of the positional and geometric accuracy of objects in orthomosaics obtained through different unmanned aerial vehicle (UAV) data processing software covering an area located within Universidade do Vale do Rio dos Sinos – UNISINOS in S?o Leopoldo, RS. A total of nine ground control points (GCP) and twenty checkpoints were surveyed in order register and classify the processed orthomosaics according to the cartographic accuracy standard – Padr?o de Exatid?o Cartográfica (PEC). Four software was employed to process the UAV data: Pix4D mapper, Agisoft PhotoScan, Menci APS and Bentley Context Capture. The results obtained from each software were compared and identified the smallest distortions when processing with and without ground control points. The flight was executed at a height of 90m with 60% sidelap and 80% overlap using an ST800 UAV equipped with a Sony NEX-7 small format non-metric camera with 24 megapixels resolution. The software GeoPEC was used to classify the orthomosaics according to PEC. For data processed with ground control points all orthomosaics were classified “Class A” in 1/500 scale, however, only Menci APS did not present a trend line via t-student test. On the other hand, Menci APS presented the worst results without the ground control points. In processing with GCP, all orthomosaics obtained optimum results with an approximated error of 2,5 m2, about 0,03% of the area.
关键词： Unmanned Aerial Vehicle,Cartographic Accuracy Standard,Orthomosaic,Ground Control Points
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Epitaxial Reflector Structures for High Efficiency Quantum Well Solar Cells
摘要： This paper provides the design and implementation of an L1-optimal control of a quadrotor unmanned aerial vehicle (UAV). The quadrotor UAV is an underactuated rigid body with four propellers that generate forces along the rotor axes. These four forces are used to achieve asymptotic tracking of four outputs, namely the position of the center of mass of the UAV and the heading. With perfect knowledge of plant parameters and no measurement noise, the magnitudes of the errors are shown to exponentially converge to zero. In the case of parametric uncertainty and measurement noise, the controller yields an exponential decrease of the magnitude of the errors in an L1-optimal sense. In other words, the controller is designed so that it minimizes the L∞-gain of the plant with respect to disturbances. The performance of the controller is evaluated in experiments and compared with that of a related robust nonlinear controller in the literature. The experimental data shows that the proposed controller rejects persistent disturbances, which is quanti?ed by a very small magnitude of the mean error.
关键词： unmanned aerial vehicle,optimal control,quadrotor,Robust control,feedback linearization
更新于2025-09-19 17:13:59
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A UAV-Mounted Free Space Optical Communication: Trajectory Optimization for Flight Time
摘要： In this work, we address the trajectory optimization of a fixed-wing unmanned aerial vehicle (UAV) using free space optical communication (FSOC). Here, we focus on maximizing the flight time of the UAV by considering practical constraints for wireless UAV communication, including limited propulsion energy and required data rates. We find optimized trajectories in various atmospheric environments (e.g., moderate-fog and heavy-fog conditions), while also considering the channel characteristics of FSOC. In addition to maximizing the flight time, we consider the energy efficiency maximization and operation-time minimization problem to find the suboptimal solutions required to meet those constraints. Furthermore, we introduce a low-complexity approach to the proposed framework. In order to address the optimization problem, we conduct a bisection method and sequential programming and introduce a new feasibility check algorithm. Although our design considers suboptimal solutions owing to the nonconvexity of the problems, our simulations indicate that the proposed scheme exhibits a gain of approximately 44.12% in terms of service time when compared to the conventional scheme.
关键词： trajectory design,Free space optical communication (FSOC),wireless communications with an unmanned aerial vehicle (UAV),flight time maximization,UAV-mounted FSOC
更新于2025-09-12 10:27:22
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Cu <sub/>2</sub> O photocathodes for unassisted solar water-splitting devices enabled by noble-metal cocatalysts simultaneously as hydrogen evolution catalysts and protection layers
摘要： BACKGROUND: Unmanned aerial vehicles (UAVs) are a recently developed aerial spraying technology. However, the effect of spray volume variation on deposition and pesticide control efficacy is unknown. The effect of three UAV spray volumes (9.0, 16.8 and 28.1 L ha?1) using three different nozzle sizes on droplet deposition and wheat aphid and powdery mildew control efficacy was assessed. An electric air-pressure knapsack (EAP) sprayer was used as a comparison. RESULTS: Different spray volumes significantly influenced the deposition and control efficacy of the UAV and EAP. For the UAV, a low spray volume of 9.0 L ha?1 with a fine nozzle (nozzle LU120-01) resulted in lower deposition and control efficacy. Optimal control efficacy was achieved with coarser nozzles (nozzles LU120-02, -03) at > 16.8 L ha?1 volume with systemic insecticide, and at 28.1 L ha?1 with contact insecticide and fungicide. For EAP, a high spray volume led to run-off, and a spray volume of 225 L ha?1 achieved better deposition and control efficacy. CONCLUSION: The UAV had comparable deposition and efficacy control to the EAP at a higher spray volume (> 16.8 L ha?1) with coarse nozzles, but exhibited inferior deposition and efficacy control at a lower spray volume (<9.0 L ha?1) with fine nozzles.
关键词： electric air-pressure knapsack sprayer,unmanned aerial vehicle,wheat powdery mildew,wheat aphid,control efficacy,pesticide deposition
更新于2025-09-11 14:15:04
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NRLI-UAV: Non-rigid registration of sequential raw laser scans and images for low-cost UAV LiDAR point cloud quality improvement
摘要： Accurate registration of light detection and ranging (LiDAR) point clouds and images is a prerequisite for integrating the spectral and geometrical information collected by low-cost unmanned aerial vehicle (UAV) systems. Most registration approaches take the directly georeferenced LiDAR point cloud as a rigid body, based on the assumption that the high-precision positioning and orientation system (POS) in the LiDAR system provides sufficient precision, and that the POS errors are negligible. However, due to the large errors of the low-precision POSs commonly used in the low-cost UAV LiDAR systems (ULSs), dramatic deformation may exist in the directly georeferenced ULS point cloud, resulting in non-rigid transformation between the images and the deformed ULS point cloud. As a result, registration may fail when using a rigid transformation between the images and the directly georeferenced LiDAR point clouds. To address this problem, we proposed NRLI-UAV, which is a non-rigid registration method for registration of sequential raw laser scans and images collected by low-cost UAV systems. NRLI-UAV is a two-step registration method that exploits trajectory correction and discrepancy minimization between the depths derived from structure from motion (SfM) and the raw laser scans to achieve LiDAR point cloud quality improvement. Firstly, the coarse registration procedure utilizes global navigation satellite system (GNSS) and inertial measurement unit (IMU)-aided SfM to obtain accurate image orientation and corrects the errors of the low-precision POS. Secondly, the fine registration procedure transforms the original 2D-3D registration to 3D-3D registration. This is performed by setting the oriented images as the reference, and iteratively minimizing the discrepancy between the depth maps derived from SfM and the raw laser scans, resulting in accurate registration between the images and the LiDAR point clouds. In addition, an improved LiDAR point cloud is generated in the mapping frame. Experiments were conducted with data collected by a low-cost UAV system in three challenging scenes to evaluate NRLI-UAV. The final registration errors of the images and the LiDAR point cloud are less than one pixel in image space and less than 0.13 m in object space. The LiDAR point cloud quality was also evaluated by plane fitting, and the results show that the LiDAR point cloud quality is improved by 8.8 times from 0.45 m (root-mean-square error [RMSE] of plane fitting) to 0.05 m (RMSE of plane fitting) using NRLI-UAV, demonstrating a high level of automation, robustness, and accuracy.
关键词： Low-cost,Light detection and ranging (LiDAR),Unmanned aerial vehicle (UAV),Image sequence,Non-rigid registration
更新于2025-09-11 14:15:04
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[IEEE 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Hangzhou (2018.8.6-2018.8.9)] 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Research on Empirical Model and Gap Rate Model for Estimating Rice Leaf Area Index Based on UAV HD Digital Images
摘要： The Leaf Area Index (LAI), as an important plant characteristic parameter, is of great significance for the monitoring of vegetation growth and the estimation of surface vegetation productivity. Rice is one of the world's major food crops, timely and accurate measurement of rice LAI can provide scientific information on agriculture. The remote sensing system of UAV is characterized by its cost-effective and real-time data acquisition. The method of estimating LAI by remote sensing technology has great advantages over traditional methods and has gradually become a frontier method for agricultural research. At present, the commonly used LAI inversion methods are empirical model method and physical model method. The former is not accurate because not all of the spectral information is used. The latter cannot directly calculate the analytical solution because of the complicated model and many input parameters. The main purpose of this paper is to obtain high-definition digital images of different varieties of rice using low-altitude drones, and to analyze the feasibility of estimating the LAI of rice canopy by empirical model method and porosity model method, and analyze the difference and estimation process between them. There are problems.
关键词： Leaf Area Index(LAI),Remote sensing,Empirical model,Unmanned Aerial Vehicle(UAV),Rice,Gap rate model
更新于2025-09-11 14:15:04
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Tracking Unmanned Aerial Vehicle CTU FTS - Application of equipment
摘要： Article which is about the Tracking Unmanned Aerial Vehicle continues in the description of the project development dealing with the utilization of the UAV (unmanned aerial vehicle). Documentation of the project progresses builds on the previous article. In that article the selection of observation and transmission equipment was summarized. In the article, the reader learns about an installation of the equipment on the UAV (helicopter), about an interconnection of the equipment to create complete and functional system, about testing of the UAV, about the solutions of the problems which came into being during the equipment against testing and about protection of unfavourable effects. The unmanned vehicle was chosen after a considering of several the parameters. These parameters are preservation of functionality or an influence to the balance. To find out how the added equipment affect the centre of gravity of the UAV the tabular method of the centre of gravity calculation was used. The results of the existing work on the project are location and attaching of the equipment to the unmanned vehicle, balance of the unmanned vehicle, solutions of the problems coming into being during the testing and design of the equipment protection against unfavourable effects.
关键词： Tracking Unmanned Aerial Vehicle CTU FTS,application of equipment,UAV,observation and transmission equipment,RPAS
更新于2025-09-11 14:15:04
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Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle
摘要： Quantifying the spatial distribution of snow is crucial to predict and assess its water resource potential and understand land–atmosphere interactions. High-resolution remote sensing of snow depth has been limited to terrestrial and airborne laser scanning and more recently with application of structure from motion (SfM) techniques to airborne (manned and unmanned) imagery. In this study, photography from a small unmanned aerial vehicle (UAV) was used to generate digital surface models (DSMs) and orthomosaics for snow cover at a cultivated agricultural Canadian prairie and a sparsely vegetated Rocky Mountain alpine ridgetop site using SfM. The accuracy and repeatability of this method to quantify snow depth, changes in depth and its spatial variability was assessed for different terrain types over time. Root mean square errors in snow depth estimation from differencing snow-covered and non-snow-covered DSMs were 8.8 cm for a short prairie grain stubble surface, 13.7 cm for a tall prairie grain stubble surface and 8.5 cm for an alpine mountain surface. This technique provided useful information on maximum snow accumulation and snow-covered area depletion at all sites, while temporal changes in snow depth could also be quanti?ed at the alpine site due to the deeper snowpack and consequent higher signal-to-noise ratio. The application of SfM to UAV photographs returns meaningful information in areas with mean snow depth > 30 cm, but the direct observation of snow depth depletion of shallow snowpacks with this method is not feasible. Accuracy varied with surface characteristics, sunlight and wind speed during the ?ight, with the most consistent performance found for wind speeds < 10 m s?1, clear skies, high sun angles and surfaces with negligible vegetation cover.
关键词： mountain environments,structure from motion,unmanned aerial vehicle,snow depth estimation,prairie environments
更新于2025-09-10 09:29:36