Small unmanned aerial vehicles (micro-UAVs, drones) in plant ecology1

PubMed Central

Cruzan, Mitchell B.; Weinstein, Ben G.; Grasty, Monica R.; Kohrn, Brendan F.; Hendrickson, Elizabeth C.; Arredondo, Tina M.; Thompson, Pamela G.

2016-01-01

Premise of the study: Low-elevation surveys with small aerial drones (micro–unmanned aerial vehicles [UAVs]) may be used for a wide variety of applications in plant ecology, including mapping vegetation over small- to medium-sized regions. We provide an overview of methods and procedures for conducting surveys and illustrate some of these applications. Methods: Aerial images were obtained by flying a small drone along transects over the area of interest. Images were used to create a composite image (orthomosaic) and a digital surface model (DSM). Vegetation classification was conducted manually and using an automated routine. Coverage of an individual species was estimated from aerial images. Results: We created a vegetation map for the entire region from the orthomosaic and DSM, and mapped the density of one species. Comparison of our manual and automated habitat classification confirmed that our mapping methods were accurate. A species with high contrast to the background matrix allowed adequate estimate of its coverage. Discussion: The example surveys demonstrate that small aerial drones are capable of gathering large amounts of information on the distribution of vegetation and individual species with minimal impact to sensitive habitats. Low-elevation aerial surveys have potential for a wide range of applications in plant ecology. PMID:27672518

A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management.

PubMed

Hocraffer, Amy; Nam, Chang S

2017-01-01

A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm's level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Applications of unmanned aerial vehicles in weed science

USDA-ARS?s Scientific Manuscript database

For most producers, unmanned aerial vehicles (UAV) are a novelty that has been little employed in their agricultural operations. An UAV will not fix every problem on the farm, but there are some practical applications for which UAVs have demonstrated value. Three examples of how UAVs have been used...

Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

NASA Astrophysics Data System (ADS)

Ma, Yi; Zhang, Jie; Zhang, Jingyu

2016-01-01

The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale

Feasibility of Turing-Style Tests for Autonomous Aerial Vehicle "Intelligence"

NASA Technical Reports Server (NTRS)

Young, Larry A.

2007-01-01

A new approach is suggested to define and evaluate key metrics as to autonomous aerial vehicle performance. This approach entails the conceptual definition of a "Turing Test" for UAVs. Such a "UAV Turing test" would be conducted by means of mission simulations and/or tailored flight demonstrations of vehicles under the guidance of their autonomous system software. These autonomous vehicle mission simulations and flight demonstrations would also have to be benchmarked against missions "flown" with pilots/human-operators in the loop. In turn, scoring criteria for such testing could be based upon both quantitative mission success metrics (unique to each mission) and by turning to analog "handling quality" metrics similar to the well-known Cooper-Harper pilot ratings used for manned aircraft. Autonomous aerial vehicles would be considered to have successfully passed this "UAV Turing Test" if the aggregate mission success metrics and handling qualities for the autonomous aerial vehicle matched or exceeded the equivalent metrics for missions conducted with pilots/human-operators in the loop. Alternatively, an independent, knowledgeable observer could provide the "UAV Turing Test" ratings of whether a vehicle is autonomous or "piloted." This observer ideally would, in the more sophisticated mission simulations, also have the enhanced capability of being able to override the scripted mission scenario and instigate failure modes and change of flight profile/plans. If a majority of mission tasks are rated as "piloted" by the observer, when in reality the vehicle/simulation is fully- or semi- autonomously controlled, then the vehicle/simulation "passes" the "UAV Turing Test." In this regards, this second "UAV Turing Test" approach is more consistent with Turing s original "imitation game" proposal. The overall feasibility, and important considerations and limitations, of such an approach for judging/evaluating autonomous aerial vehicle "intelligence" will be discussed from a

Unmanned Aerial Vehicle (UAV) Data Acquisition for Archaeological Site Identification and Mapping

NASA Astrophysics Data System (ADS)

Handayani, W.; Ayuningtyas, E. A.; Candra R, F. S.; Arif S, B.; Argadyanto, B.

2017-12-01

Archaeological sites as part of human history and located around community are important to be preserved for connecting historical information from generation to generation. Mapping of archaeological sites can be done as one of preservation efforts. Yogyakarta has several archaeological sites such as Pleret Palace, the former royal palace of Mataram Islam in the 16th Century. Data limitations and the difficulty of reconstructing the site sketches into a map become obstacles in archaeological sites mapping. Unmanned Aerial Vehicle (UAV) can be an alternative of high-resolution spatial data acquisition for detail mapping, including archaeological sites mapping. This study aims to see how far the UAV acquisition results can be used for Archaeological Site mapping in Pleret Palace. Data acquisition using UAV generated to mosaic orthophoto, Digital Surface Model (DSM), and Digital Terrain Model (DTM). Archaeological sites identified using DTM and matched with site sketch made by Cultural Agency. From these data, it can be recognized some relics form, such as palace fortress, moats and canals, and also dikes of Segarayasa. This research is expected to be a reference in archaeological site mapping using detailed spatial data, especially UAV. Furthermore, it can be obtained archaeological site map close to real condition; as well as archaeological sites preservation in Indonesia.

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

NASA Astrophysics Data System (ADS)

Geis, Jack; Arnold, Jack H.

1994-09-01

Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States' Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV's whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Since the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, we have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible we modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

NASA Technical Reports Server (NTRS)

Geis, Jack; Arnold, Jack H.

1994-01-01

Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States' Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV's whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Since the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, we have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible we modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.

Unmanned Aerial Vehicle (UAV) data analysis for fertilization dose assessment

NASA Astrophysics Data System (ADS)

Kavvadias, Antonis; Psomiadis, Emmanouil; Chanioti, Maroulio; Tsitouras, Alexandros; Toulios, Leonidas; Dercas, Nicholas

2017-10-01

The growth rate monitoring of crops throughout their biological cycle is very important as it contributes to the achievement of a uniformly optimum production, a proper harvest planning, and reliable yield estimation. Fertilizer application often dramatically increases crop yields, but it is necessary to find out which is the ideal amount that has to be applied in the field. Remote sensing collects spatially dense information that may contribute to, or provide feedback about, fertilization management decisions. There is a potential goal to accurately predict the amount of fertilizer needed so as to attain an ideal crop yield without excessive use of fertilizers cause financial loss and negative environmental impacts. The comparison of the reflectance values at different wavelengths, utilizing suitable vegetation indices, is commonly used to determine plant vigor and growth. Unmanned Aerial Vehicles (UAVs) have several advantages; because they can be deployed quickly and repeatedly, they are flexible regarding flying height and timing of missions, and they can obtain very high-resolution imagery. In an experimental crop field in Eleftherio Larissa, Greece, different dose of pre-plant and in-season fertilization was applied in 27 plots. A total of 102 aerial photos in two flights were taken using an Unmanned Aerial Vehicle based on the scheduled fertilization. Α correlation of experimental fertilization with the change of vegetation indices values and with the increase of the vegetation cover rate during those days was made. The results of the analysis provide useful information regarding the vigor and crop growth rate performance of various doses of fertilization.

The remote characterization of vegetation using Unmanned Aerial Vehicle photography

USDA-ARS?s Scientific Manuscript database

Unmanned Aerial Vehicles (UAVs) can fly in place of piloted aircraft to gather remote sensing information on vegetation characteristics. The type of sensors flown depends on the instrument payload capacity available, so that, depending on the specific UAV, it is possible to obtain video, aerial phot...

Wildlife Multispecies Remote Sensing Using Visible and Thermal Infrared Imagery Acquired from AN Unmanned Aerial Vehicle (uav)

NASA Astrophysics Data System (ADS)

Chrétien, L.-P.; Théau, J.; Ménard, P.

2015-08-01

Wildlife aerial surveys require time and significant resources. Multispecies detection could reduce costs to a single census for species that coexist spatially. Traditional methods are demanding for observers in terms of concentration and are not adapted to multispecies censuses. The processing of multispectral aerial imagery acquired from an unmanned aerial vehicle (UAV) represents a potential solution for multispecies detection. The method used in this study is based on a multicriteria object-based image analysis applied on visible and thermal infrared imagery acquired from a UAV. This project aimed to detect American bison, fallow deer, gray wolves, and elks located in separate enclosures with a known number of individuals. Results showed that all bison and elks were detected without errors, while for deer and wolves, 0-2 individuals per flight line were mistaken with ground elements or undetected. This approach also detected simultaneously and separately the four targeted species even in the presence of other untargeted ones. These results confirm the potential of multispectral imagery acquired from UAV for wildlife census. Its operational application remains limited to small areas related to the current regulations and available technology. Standardization of the workflow will help to reduce time and expertise requirements for such technology.

A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery.

PubMed

Huang, Huasheng; Deng, Jizhong; Lan, Yubin; Yang, Aqing; Deng, Xiaoling; Zhang, Lei

2018-01-01

Appropriate Site Specific Weed Management (SSWM) is crucial to ensure the crop yields. Within SSWM of large-scale area, remote sensing is a key technology to provide accurate weed distribution information. Compared with satellite and piloted aircraft remote sensing, unmanned aerial vehicle (UAV) is capable of capturing high spatial resolution imagery, which will provide more detailed information for weed mapping. The objective of this paper is to generate an accurate weed cover map based on UAV imagery. The UAV RGB imagery was collected in 2017 October over the rice field located in South China. The Fully Convolutional Network (FCN) method was proposed for weed mapping of the collected imagery. Transfer learning was used to improve generalization capability, and skip architecture was applied to increase the prediction accuracy. After that, the performance of FCN architecture was compared with Patch_based CNN algorithm and Pixel_based CNN method. Experimental results showed that our FCN method outperformed others, both in terms of accuracy and efficiency. The overall accuracy of the FCN approach was up to 0.935 and the accuracy for weed recognition was 0.883, which means that this algorithm is capable of generating accurate weed cover maps for the evaluated UAV imagery.

Configuration and specifications of an Unmanned Aerial Vehicle (UAV) for early site specific weed management.

PubMed

Torres-Sánchez, Jorge; López-Granados, Francisca; De Castro, Ana Isabel; Peña-Barragán, José Manuel

2013-01-01

A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches).

Configuration and Specifications of an Unmanned Aerial Vehicle (UAV) for Early Site Specific Weed Management

PubMed Central

Torres-Sánchez, Jorge; López-Granados, Francisca; De Castro, Ana Isabel; Peña-Barragán, José Manuel

2013-01-01

A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches). PMID:23483997

Towards collaboration between unmanned aerial and ground vehicles for precision agriculture

NASA Astrophysics Data System (ADS)

Bhandari, Subodh; Raheja, Amar; Green, Robert L.; Do, Dat

2017-05-01

This paper presents the work being conducted at Cal Poly Pomona on the collaboration between unmanned aerial and ground vehicles for precision agriculture. The unmanned aerial vehicles (UAVs), equipped with multispectral/hyperspectral cameras and RGB cameras, take images of the crops while flying autonomously. The images are post processed or can be processed onboard. The processed images are used in the detection of unhealthy plants. Aerial data can be used by the UAVs and unmanned ground vehicles (UGVs) for various purposes including care of crops, harvest estimation, etc. The images can also be useful for optimized harvesting by isolating low yielding plants. These vehicles can be operated autonomously with limited or no human intervention, thereby reducing cost and limiting human exposure to agricultural chemicals. The paper discuss the autonomous UAV and UGV platforms used for the research, sensor integration, and experimental testing. Methods for ground truthing the results obtained from the UAVs will be used. The paper will also discuss equipping the UGV with a robotic arm for removing the unhealthy plants and/or weeds.

Research study concerning the 3D printing adittion (FDM-fused deposition modeling) to design UAV (UAV-unconventional aerial vehicle) structures

NASA Astrophysics Data System (ADS)

Pascu, Nicoleta Elisabeta; CǎruÅ£aşu, Nicoleta LuminiÅ£a.; Geambaşu, Gabriel George; Adîr, Victor Gabriel; Arion, Aurel Florin; Ivaşcu, Laura

2018-02-01

Aerial vehicles have become indispensable. There are in this field UAV (Unconventional Aerial vehicle) and transportation airplanes and other aerospace vehicles for spatial tourism. Today, the research and development activity in aerospace industry is focused to obtain a good and efficient design for airplanes, to solve the problem of high pollution and to reduce the noise. For these goals are necessary to realize light and resistant components. The aerospace industry products are, generally, very complex concerning geometric shapes and the costs are high, usually. Due to the progress in this field (products obtained using FDM) was possible to reduce the number of used tools, welding belts, and, of course, to eliminate a lot of machine tools. In addition, the complex shapes are easier product using this high technology, the cost is more attractive and the time is lower. This paper allows to present a few aspects about FDM technology and the obtained structures using it, as follows: computer geometric modeling (different designing softs) to design and redesign complex structures using 3D printing, for this kind of vehicles; finite element analysis to identify what is the influence of design for different structures; testing the structures.

Unmanned aerial vehicle applications for highway transportation : initial stage reference search.

DOT National Transportation Integrated Search

2013-11-01

Identification of research (2006present) focusing on autonomous micro unmanned aerial vehicles (UAVs) for transportation applications, including the examination of other industries that may also utilize micro UAVs.

Topographic data acquisition in tsunami-prone coastal area using Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

Marfai, M. A.; Sunarto; Khakim, N.; Cahyadi, A.; Rosaji, F. S. C.; Fatchurohman, H.; Wibowo, Y. A.

2018-04-01

The southern coastal area of Java Island is one of the nine seismic gaps prone to tsunamis. The entire coastline in one of the regencies, Gunungkidul, is exposed to the subduction zone in the Indian Ocean. Also, the growing tourism industries in the regency increase its vulnerability, which places most of its areas at high risk of tsunamis. The same case applies to Kukup, i.e., one of the most well-known beaches in Gunungkidul. Structurally shaped cliffs that surround it experience intensive wave erosion process, but it has very minimum access for evacuation routes. Since tsunami modeling is a very advanced analysis, it requires an accurate topographic data. Therefore, the research aimed to generate the topographic data of Kukup Beach as the baseline in tsunami risk reduction analysis and disaster management. It used aerial photograph data, which was acquired using Unmanned Aerial Vehicle (UAV). The results showed that the aerial photographs captured by drone had accurate elevation and spatial resolution. Therefore, they are applicable for tsunami modeling and disaster management.

Unmanned Aerial Vehicles unique cost estimating requirements

NASA Astrophysics Data System (ADS)

Malone, P.; Apgar, H.; Stukes, S.; Sterk, S.

Unmanned Aerial Vehicles (UAVs), also referred to as drones, are aerial platforms that fly without a human pilot onboard. UAVs are controlled autonomously by a computer in the vehicle or under the remote control of a pilot stationed at a fixed ground location. There are a wide variety of drone shapes, sizes, configurations, complexities, and characteristics. Use of these devices by the Department of Defense (DoD), NASA, civil and commercial organizations continues to grow. UAVs are commonly used for intelligence, surveillance, reconnaissance (ISR). They are also use for combat operations, and civil applications, such as firefighting, non-military security work, surveillance of infrastructure (e.g. pipelines, power lines and country borders). UAVs are often preferred for missions that require sustained persistence (over 4 hours in duration), or are “ too dangerous, dull or dirty” for manned aircraft. Moreover, they can offer significant acquisition and operations cost savings over traditional manned aircraft. Because of these unique characteristics and missions, UAV estimates require some unique estimating methods. This paper describes a framework for estimating UAV systems total ownership cost including hardware components, software design, and operations. The challenge of collecting data, testing the sensitivities of cost drivers, and creating cost estimating relationships (CERs) for each key work breakdown structure (WBS) element is discussed. The autonomous operation of UAVs is especially challenging from a software perspective.

Unmanned Aerial Vehicles (UAVs): a new tool in counterterrorism operations?

NASA Astrophysics Data System (ADS)

Dörtbudak, Mehmet F.

2015-05-01

Terrorism is not a new phenomenon to the world, yet it remains difficult to define and counter. Countering terrorism requires several measures that must be taken simultaneously; however, counterterrorism strategies of many countries mostly depend on military measures. In the aftermath of the 2001 terrorist attack on the Twin Towers of the World Trade Center, the United States (U.S.) has started and led the campaign of Global War on Terrorism. They have invaded Afghanistan and Iraq and have encountered insurgencies run by terrorist organizations, such as al-Qaeda and its affiliates. The U.S. made the utilization of Air and Space Power very intensively during these operations. In order to implement operations; Intelligence, Surveillance, and Reconnaissance (ISR) assets were used to collect the necessary information. Before the successful insertion of a small number of U.S. Special Operation Force (SOF) teams into Afghanistan, the U.S. Air Force attacked al-Qaeda and Taliban's targets such as infrastructure, airfields, ground forces, command-control facilities etc. As soon as the U.S. troops got on the ground and started to marshal to Kabul, the Air Force supported them by attacking jointly determined targets. The Air Force continued to carry out the missions and played a significant role to achieve the objective of operation during all the time. This is not the only example of utilization of Air and Space Power in counterterrorism and counterinsurgency operations. All around the world, many countries have also made the utilization of Air Power in different missions ranging from ISR to attacking. Thinking that terrorism has a psychological dimension and losing a pilot during operations may result in decreasing the population support to operations, Unmanned Aerial Vehicles (UAVs) started to be used by practitioners and took priority over other assets. Although UAVs have been on the theatre for a long time used for ISR mission in conventional conflicts, with the advent

Hardware Implementation of COTS Avionics System on Unmanned Aerial Vehicle Platforms

NASA Technical Reports Server (NTRS)

Yeh, Yoo-Hsiu; Kumar, Parth; Ishihara, Abraham; Ippolito, Corey

2010-01-01

Unmanned Aerial Vehicles (UAVs) can serve as low cost and low risk platforms for flight testing in Aeronautics research. The NASA Exploration Aerial Vehicle (EAV) and Experimental Sensor-Controlled Aerial Vehicle (X-SCAV) UAVs were developed in support of control systems research at NASA Ames Research Center. The avionics hardware for both systems has been redesigned and updated, and the structure of the EAV has been further strengthened. Preliminary tests show the avionics operate properly in the new configuration. A linear model for the EAV also was estimated from flight data, and was verified in simulation. These modifications and results prepare the EAV and X-SCAV to be used in a wide variety of flight research projects.

Data Acquisition (DAQ) system dedicated for remote sensing applications on Unmanned Aerial Vehicles (UAV)

NASA Astrophysics Data System (ADS)

Keleshis, C.; Ioannou, S.; Vrekoussis, M.; Levin, Z.; Lange, M. A.

2014-08-01

Continuous advances in unmanned aerial vehicles (UAV) and the increased complexity of their applications raise the demand for improved data acquisition systems (DAQ). These improvements may comprise low power consumption, low volume and weight, robustness, modularity and capability to interface with various sensors and peripherals while maintaining the high sampling rates and processing speeds. Such a system has been designed and developed and is currently integrated on the Autonomous Flying Platforms for Atmospheric and Earth Surface Observations (APAESO/NEA-YΠOΔOMH/NEKΠ/0308/09) however, it can be easily adapted to any UAV or any other mobile vehicle. The system consists of a single-board computer with a dual-core processor, rugged surface-mount memory and storage device, analog and digital input-output ports and many other peripherals that enhance its connectivity with various sensors, imagers and on-board devices. The system is powered by a high efficiency power supply board. Additional boards such as frame-grabbers, differential global positioning system (DGPS) satellite receivers, general packet radio service (3G-4G-GPRS) modems for communication redundancy have been interfaced to the core system and are used whenever there is a mission need. The onboard DAQ system can be preprogrammed for automatic data acquisition or it can be remotely operated during the flight from the ground control station (GCS) using a graphical user interface (GUI) which has been developed and will also be presented in this paper. The unique design of the GUI and the DAQ system enables the synchronized acquisition of a variety of scientific and UAV flight data in a single core location. The new DAQ system and the GUI have been successfully utilized in several scientific UAV missions. In conclusion, the novel DAQ system provides the UAV and the remote-sensing community with a new tool capable of reliably acquiring, processing, storing and transmitting data from any sensor integrated

Development and prospect of unmanned aerial vehicles for agricultural production management

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles have been developed and applied to support agricultural production management. Compared to piloted aircrafts, an Unmanned Aerial Vehicle (UAV) can focus on small crop fields in lower flight altitude than regular airplanes to perform site-specific management with high precisi...

Development of Unmanned Aerial Vehicles for Site-Specific Crop Production Management

USDA-ARS?s Scientific Manuscript database

Unmanned Aerial Vehicles (UAV) have been developed and applied to support the practice of precision agriculture. Compared to piloted aircrafts, an Unmanned Aerial Vehicle can focus on much smaller crop fields with much lower flight altitude than regular airplanes to perform site-specific management ...

Measurement of greenhouse gases in UAE by using Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

Abou-Elnour, Ali; Odeh, Mohamed; Abdelrhman, Mohammed; Balkis, Ahmed; Amira, Abdelraouf

2017-04-01

In the present work, a reliable and low cost system has been designed and implemented to measure greenhouse gases (GHG) in United Arab Emirates (UAE) by using unmanned aerial vehicle (UAV). A set of accurate gas, temperature, pressure, humidity sensors are integrated together with a wireless communication system on a microcontroller based platform to continuously measure the required data. The system instantaneously sends the measured data to a center monitoring unit via the wireless communication system. In addition, the proposed system has the features that all measurements are recorded directly in a storage device to allow effective monitoring in regions with weak or no wireless coverage. The obtained data will be used in all further sophisticated calculations for environmental research and monitoring purposes.

The effective use of unmanned aerial vehicles for local law enforcement

NASA Astrophysics Data System (ADS)

Gasque, Leighton

This qualitative study was done to interview local law enforcement in Murfreesboro, Tennessee to determine if unmanned aerial vehicles could increase the safety of policy officers. Many police officers face dangerous scenarios on a daily basis; however, officers must also perform non-criminal related responsibilities that could put them in hazardous situations. UAVs have multiple capabilities that can decrease the number of hazards in an emergency situation whether it is environmental, traffic related, criminal activity, or investigations. Officers were interviewed to find whether or not unmanned aerial vehicles (UAV) could be useful manpower on the police force. The study was also used to find whether or not officers foresee UAVs being used in law enforcement. The study revealed that UAVs could be used to add useful manpower to law enforcement based on the capabilities a UAV may have. Police officers cannot confirm whether or not they would be able to use a UAV until further research is conducted to examine the relation of costs to usage.

Synthesis of the unmanned aerial vehicle remote control augmentation system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tomczyk, Andrzej, E-mail: A.Tomczyk@prz.edu.pl

Medium size Unmanned Aerial Vehicle (UAV) usually flies as an autonomous aircraft including automatic take-off and landing phases. However in the case of the on-board control system failure, the remote steering is using as an emergency procedure. In this reason, remote manual control of unmanned aerial vehicle is used more often during take-of and landing phases. Depends on UAV take-off mass and speed (total energy) the potential crash can be very danger for airplane and environment. So, handling qualities of UAV is important from pilot-operator point of view. In many cases the dynamic properties of remote controlling UAV are notmore » suitable for obtaining the desired properties of the handling qualities. In this case the control augmentation system (CAS) should be applied. Because the potential failure of the on-board control system, the better solution is that the CAS algorithms are placed on the ground station computers. The method of UAV handling qualities shaping in the case of basic control system failure is presented in this paper. The main idea of this method is that UAV reaction on the operator steering signals should be similar - almost the same - as reaction of the 'ideal' remote control aircraft. The model following method was used for controller parameters calculations. The numerical example concerns the medium size MP-02A UAV applied as an aerial observer system.« less

Formation Flying for Satellites and Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Merrill, Garrick

2015-01-01

The shrinking size of satellites and unmanned aerial vehicles (UAVs) is enabling lower cost missions. As sensors and electronics continue to downsize, the next step is multiple vehicles providing different perspectives or variations for more precise measurements. While flying a single satellite or UAV autonomously is a challenge, flying multiple vehicles in a precise formation is even more challenging. The goal of this project is to develop a scalable mesh network between vehicles (satellites or UAVs) to share real-time position data and maintain formations autonomously. Newly available low-cost, commercial off-the-shelf credit card size computers will be used as the basis for this network. Mesh networking techniques will be used to provide redundant links and a flexible network. The Small Projects Rapid Integration and Test Environment Lab will be used to simulate formation flying of satellites. UAVs built by the Aero-M team will be used to demonstrate the formation flying in the West Test Area. The ability to test in flight on NASA-owned UAVs allows this technology to achieve a high Technology Readiness Level (TRL) (TRL-4 for satellites and TRL-7 for UAVs). The low cost of small UAVs and the availability of a large test range (West Test Area) dramatically reduces the expense of testing. The end goal is for this technology to be ready to use on any multiple satellite or UAV mission.

The future of structural fieldwork - UAV assisted aerial photogrammetry

NASA Astrophysics Data System (ADS)

Vollgger, Stefan; Cruden, Alexander

2015-04-01

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are opening new and low cost possibilities to acquire high-resolution aerial images and digital surface models (DSM) for applications in structural geology. UAVs can be programmed to fly autonomously along a user defined grid to systematically capture high-resolution photographs, even in difficult to access areas. The photographs are subsequently processed using software that employ SIFT (scale invariant feature transform) and SFM (structure from motion) algorithms. These photogrammetric routines allow the extraction of spatial information (3D point clouds, digital elevation models, 3D meshes, orthophotos) from 2D images. Depending on flight altitude and camera setup, sub-centimeter spatial resolutions can be achieved. By "digitally mapping" georeferenced 3D models and images, orientation data can be extracted directly and used to analyse the structural framework of the mapped object or area. We present UAV assisted aerial mapping results from a coastal platform near Cape Liptrap (Victoria, Australia), where deformed metasediments of the Palaeozoic Lachlan Fold Belt are exposed. We also show how orientation and spatial information of brittle and ductile structures extracted from the photogrammetric model can be linked to the progressive development of folds and faults in the region. Even though there are both technical and legislative limitations, which might prohibit the use of UAVs without prior commercial licensing and training, the benefits that arise from the resulting high-resolution, photorealistic models can substantially contribute to the collection of new data and insights for applications in structural geology.

Rangeland resource assessment, monitoring, and management using unmanned aerial vehicle-based remote sensing

USDA-ARS?s Scientific Manuscript database

Civilian applications of Unmanned Aerial Vehicles (UAV) have rapidly been expanding recently. Thanks to military development many civil UAVs come via the defense sector. Although numerous UAVs can perform civilian tasks, the regulations imposed by FAA in the national airspace system and military e...

A survey of hybrid Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Saeed, Adnan S.; Younes, Ahmad Bani; Cai, Chenxiao; Cai, Guowei

2018-04-01

This article presents a comprehensive overview on the recent advances of miniature hybrid Unmanned Aerial Vehicles (UAVs). For now, two conventional types, i.e., fixed-wing UAV and Vertical Takeoff and Landing (VTOL) UAV, dominate the miniature UAVs. Each type has its own inherent limitations on flexibility, payload, flight range, cruising speed, takeoff and landing requirements and endurance. Enhanced popularity and interest are recently gained by the newer type, named hybrid UAV, that integrates the beneficial features of both conventional ones. In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples. Next, the hybrid UAV's flight dynamics model and flight control strategies are explained addressing several representative modeling and control work. In addition, key observations, existing challenges and conclusive remarks based on the conducted review are discussed accordingly.

Real-time people and vehicle detection from UAV imagery

NASA Astrophysics Data System (ADS)

Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan

2011-01-01

A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.

Coastal Ecosystem Assessment, Development and Creation of a Policy Tool using Unmanned Aerial Vehicles (UAVs) for: A Case Study of Western Puerto Rico Coastal Region

NASA Astrophysics Data System (ADS)

Munoz Barreto, J.; Pillich, J.; Aponte Bermúdez, L. D.; Torres Pagan, G.

2017-12-01

This project utilizes low-cost Unmanned Aerial Vehicles (UAVs) based systems for different applications, such as low-altitude (high resolution) aerial photogrammetry for aerial analysis of vegetation, reconstruction of beach topography and mapping coastal erosion to understand, and estimated ecosystem values. As part of this work, five testbeds coastal sites, designated as the Caribbean Littoral Aerial Surveillance System (CLASS), were established. The sites are distributed along western Puerto Rico coastline where population and industry (tourism) are very much clustered and dense along the coast. Over the past year, rapid post-storm deployment of UAV surveying has been successfully integrated into the CLASS sites, specifically at Rincon (Puerto Rico), where coastal erosion has raised the public and government concern over the past decades. A case study is presented here where we collected aerial photos before and after the swells caused by Hurricane Mathew (October 2016). We merged the point cloud obtained from the UAV photogrammetric assessment with topo-bathymetric data, to get a complete beach topography. Using the rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for the pre-swell and post-swell events. Also, we used numerical modeling (X-Beach) to simulate the rate-of-change dynamics of the coastal zones and compare the model results to observed values (including multiple historic shoreline positions). In summary, our project has accomplished the first milestone which is the Development and Implementation of an Effective Shoreline Monitoring Program using UAVs. The activities of the monitoring program have enabled the collection of crucial data for coastal mapping along Puerto Rico's shorelines with emphasis on coastal erosion hot spots zones and ecosystem values. Our results highlight the potential of the synergy between UAVs, photogrammetry, and Geographic Information Systems to provide faster and low-cost reliable

Wetland Assessment Using Unmanned Aerial Vehicle (uav) Photogrammetry

NASA Astrophysics Data System (ADS)

Boon, M. A.; Greenfield, R.; Tesfamichael, S.

2016-06-01

The use of Unmanned Arial Vehicle (UAV) photogrammetry is a valuable tool to enhance our understanding of wetlands. Accurate planning derived from this technological advancement allows for more effective management and conservation of wetland areas. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool to enhance the assessment of wetland ecosystems. The UAV images were collected during a single flight within 2½ hours over a 100 ha area at the Kameelzynkraal farm, Gauteng Province, South Africa. An AKS Y-6 MKII multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. Twenty ground control points (GCPs) were surveyed using a Trimble GPS to achieve geometrical precision and georeferencing accuracy. Structure-from-Motion (SfM) computer vision techniques were used to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The geometric accuracy of the data based on the 20 GCP's were 0.018 m for the overall, 0.0025 m for the vertical root mean squared error (RMSE) and an over all root mean square reprojection error of 0.18 pixel. The UAV products were then edited and subsequently analysed, interpreted and key attributes extracted using a selection of tools/ software applications to enhance the wetland assessment. The results exceeded our expectations and provided a valuable and accurate enhancement to the wetland delineation, classification and health assessment which even with detailed field studies would have been difficult to achieve.

Numerical simulation of unmanned aerial vehicle under centrifugal load and optimization of milling and planing

NASA Astrophysics Data System (ADS)

Chen, Yunsheng; Lu, Xinghua

2018-05-01

The mechanical parts of the fuselage surface of the UAV are easily fractured by the action of the centrifugal load. In order to improve the compressive strength of UAV and guide the milling and planing of mechanical parts, a numerical simulation method of UAV fuselage compression under centrifugal load based on discrete element analysis method is proposed. The three-dimensional discrete element method is used to establish the splitting tensile force analysis model of the UAV fuselage under centrifugal loading. The micro-contact connection parameters of the UAV fuselage are calculated, and the yield tensile model of the mechanical components is established. The dynamic and static mechanical model of the aircraft fuselage milling is analyzed by the axial amplitude vibration frequency combined method. The correlation parameters of the cutting depth on the tool wear are obtained. The centrifugal load stress spectrum of the surface of the UAV is calculated. The meshing and finite element simulation of the rotor blade of the unmanned aerial vehicle is carried out to optimize the milling process. The test results show that the accuracy of the anti - compression numerical test of the UAV is higher by adopting the method, and the anti - fatigue damage capability of the unmanned aerial vehicle body is improved through the milling and processing optimization, and the mechanical strength of the unmanned aerial vehicle can be effectively improved.

Morphing unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Gomez, Juan Carlos; Garcia, Ephrahim

2011-10-01

Research on aircraft morphing has exploded in recent years. The motivation and driving force behind this has been to find new and novel ways to increase the capabilities of aircraft. Materials advancements have helped to increase possibilities with respect to actuation and, hence, a diversity of concepts and unimagined capabilities. The expanded role of unmanned aerial vehicles (UAVs) has provided an ideal platform for exploring these emergent morphing concepts since at this scale a greater amount of risk can be taken, as well as having more manageable fabrication and cost requirements. This review focuses on presenting the role UAVs have in morphing research by giving an overview of the UAV morphing concepts, designs, and technologies described in the literature. A presentation of quantitative information as well as a discussion of technical issues is given where possible to begin gaining some insight into the overall assessment and performance of these technologies.

High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology

PubMed Central

Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M.

2015-01-01

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications. PMID:26107174

High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology.

PubMed

Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M

2015-01-01

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications.

Precision wildlife monitoring using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Hodgson, Jarrod C.; Baylis, Shane M.; Mott, Rowan; Herrod, Ashley; Clarke, Rohan H.

2016-03-01

Unmanned aerial vehicles (UAVs) represent a new frontier in environmental research. Their use has the potential to revolutionise the field if they prove capable of improving data quality or the ease with which data are collected beyond traditional methods. We apply UAV technology to wildlife monitoring in tropical and polar environments and demonstrate that UAV-derived counts of colony nesting birds are an order of magnitude more precise than traditional ground counts. The increased count precision afforded by UAVs, along with their ability to survey hard-to-reach populations and places, will likely drive many wildlife monitoring projects that rely on population counts to transition from traditional methods to UAV technology. Careful consideration will be required to ensure the coherence of historic data sets with new UAV-derived data and we propose a method for determining the number of duplicated (concurrent UAV and ground counts) sampling points needed to achieve data compatibility.

Ground control station software design for micro aerial vehicles

NASA Astrophysics Data System (ADS)

Walendziuk, Wojciech; Oldziej, Daniel; Binczyk, Dawid Przemyslaw; Slowik, Maciej

2017-08-01

This article describes the process of designing the equipment part and the software of a ground control station used for configuring and operating micro unmanned aerial vehicles (UAV). All the works were conducted on a quadrocopter model being a commonly accessible commercial construction. This article contains a characteristics of the research object, the basics of operating the micro aerial vehicles (MAV) and presents components of the ground control station model. It also describes the communication standards for the purpose of building a model of the station. Further part of the work concerns the software of the product - the GIMSO application (Generally Interactive Station for Mobile Objects), which enables the user to manage the actions and communication and control processes from the UAV. The process of creating the software and the field tests of a station model are also presented in the article.

Unmanned Aerial Vehicle (UAV) Dynamic-Tracking Directional Wireless Antennas for Low Powered Applications that Require Reliable Extended Range Operations in Time Critical Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott G. Bauer; Matthew O. Anderson; James R. Hanneman

2005-10-01

The proven value of DOD Unmanned Aerial Vehicles (UAVs) will ultimately transition to National and Homeland Security missions that require real-time aerial surveillance, situation awareness, force protection, and sensor placement. Public services first responders who routinely risk personal safety to assess and report a situation for emergency actions will likely be the first to benefit from these new unmanned technologies. ‘Packable’ or ‘Portable’ small class UAVs will be particularly useful to the first responder. They require the least amount of training, no fixed infrastructure, and are capable of being launched and recovered from the point of emergency. All UAVs requiremore » wireless communication technologies for real- time applications. Typically on a small UAV, a low bandwidth telemetry link is required for command and control (C2), and systems health monitoring. If the UAV is equipped with a real-time Electro-Optical or Infrared (EO/Ir) video camera payload, a dedicated high bandwidth analog/digital link is usually required for reliable high-resolution imagery. In most cases, both the wireless telemetry and real-time video links will be integrated into the UAV with unity gain omni-directional antennas. With limited on-board power and payload capacity, a small UAV will be limited with the amount of radio-frequency (RF) energy it transmits to the users. Therefore, ‘packable’ and ‘portable’ UAVs will have limited useful operational ranges for first responders. This paper will discuss the limitations of small UAV wireless communications. The discussion will present an approach of utilizing a dynamic ground based real-time tracking high gain directional antenna to provide extend range stand-off operation, potential RF channel reuse, and assured telemetry and data communications from low-powered UAV deployed wireless assets.« less

Photogrammetric mapping using unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Graça, N.; Mitishita, E.; Gonçalves, J.

2014-11-01

Nowadays Unmanned Aerial Vehicle (UAV) technology has attracted attention for aerial photogrammetric mapping. The low cost and the feasibility to automatic flight along commanded waypoints can be considered as the main advantages of this technology in photogrammetric applications. Using GNSS/INS technologies the images are taken at the planned position of the exposure station and the exterior orientation parameters (position Xo, Yo, Zo and attitude ω, φ, χ) of images can be direct determined. However, common UAVs (off-the-shelf) do not replace the traditional aircraft platform. Overall, the main shortcomings are related to: difficulties to obtain the authorization to perform the flight in urban and rural areas, platform stability, safety flight, stability of the image block configuration, high number of the images and inaccuracies of the direct determination of the exterior orientation parameters of the images. In this paper are shown the obtained results from the project photogrammetric mapping using aerial images from the SIMEPAR UAV system. The PIPER J3 UAV Hydro aircraft was used. It has a micro pilot MP2128g. The system is fully integrated with 3-axis gyros/accelerometers, GPS, pressure altimeter, pressure airspeed sensors. A Sony Cyber-shot DSC-W300 was calibrated and used to get the image block. The flight height was close to 400 m, resulting GSD near to 0.10 m. The state of the art of the used technology, methodologies and the obtained results are shown and discussed. Finally advantages/shortcomings found in the study and main conclusions are presented

Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2003-01-01

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Implementation of AN Unmanned Aerial Vehicle System for Large Scale Mapping

NASA Astrophysics Data System (ADS)

Mah, S. B.; Cryderman, C. S.

2015-08-01

Unmanned Aerial Vehicles (UAVs), digital cameras, powerful personal computers, and software have made it possible for geomatics professionals to capture aerial photographs and generate digital terrain models and orthophotographs without using full scale aircraft or hiring mapping professionals. This has been made possible by the availability of miniaturized computers and sensors, and software which has been driven, in part, by the demand for this technology in consumer items such as smartphones. The other force that is in play is the increasing number of Do-It-Yourself (DIY) people who are building UAVs as a hobby or for professional use. Building a UAV system for mapping is an alternative to purchasing a turnkey system. This paper describes factors to be considered when building a UAV mapping system, the choices made, and the test results of a project using this completed system.

Targeted Applications of Unmanned Aerial Vehicles (Drones) in Telemedicine.

PubMed

Bhatt, Kunj; Pourmand, Ali; Sikka, Neal

2018-02-28

Advances in technology have revolutionized the medical field and changed the way healthcare is delivered. Unmanned aerial vehicles (UAVs) are the next wave of technological advancements that have the potential to make a huge splash in clinical medicine. UAVs, originally developed for military use, are making their way into the public and private sector. Because they can be flown autonomously and can reach almost any geographical location, the significance of UAVs are becoming increasingly apparent in the medical field. We conducted a comprehensive review of the English language literature via the PubMed and Google Scholar databases using search terms "unmanned aerial vehicles," "UAVs," and "drone." Preference was given to clinical trials and review articles that addressed the keywords and clinical medicine. Potential applications of UAVs in medicine are broad. Based on articles identified, we grouped UAV application in medicine into three categories: (1) Prehospital Emergency Care; (2) Expediting Laboratory Diagnostic Testing; and (3) Surveillance. Currently, UAVs have been shown to deliver vaccines, automated external defibrillators, and hematological products. In addition, they are also being studied in the identification of mosquito habitats as well as drowning victims at beaches as a public health surveillance modality. These preliminary studies shine light on the possibility that UAVs may help to increase access to healthcare for patients who may be otherwise restricted from proper care due to cost, distance, or infrastructure. As with any emerging technology and due to the highly regulated healthcare environment, the safety and effectiveness of this technology need to be thoroughly discussed. Despite the many questions that need to be answered, the application of drones in medicine appears to be promising and can both increase the quality and accessibility of healthcare.

Use of unmanned aerial vehicles for medical product transport.

PubMed

Thiels, Cornelius A; Aho, Johnathon M; Zietlow, Scott P; Jenkins, Donald H

2015-01-01

Advances in technology and decreasing costs have led to an increased use of unmanned aerial vehicles (UAVs) by the military and civilian sectors. The use of UAVs in commerce is restricted by US Federal Aviation Administration (FAA) regulations, but the FAA is drafting new regulations that are expected to expand commercial applications. Currently, the transportation of medical goods in times of critical need is limited to wheeled motor vehicles and manned aircraft, options that can be costly and slow. This article explores the demand for, feasibility of, and risks associated with the use of UAVs to deliver medical products, including blood derivatives and pharmaceuticals, to hospitals, mass casualty scenes, and offshore vessels in times of critical demand. Copyright © 2015 Air Medical Journal Associates. Published by Elsevier Inc. All rights reserved.

Unmanned aerial vehicle: A unique platform for low-altitude remote sensing for crop management

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...

A new stratospheric sounding platform based on unmanned aerial vehicle (UAV) droppable from meteorological balloon

NASA Astrophysics Data System (ADS)

Efremov, Denis; Khaykin, Sergey; Lykov, Alexey; Berezhko, Yaroslav; Lunin, Aleksey

High-resolution measurements of climate-relevant trace gases and aerosols in the upper troposphere and stratosphere (UTS) have been and remain technically challenging. The high cost of measurements onboard airborne platforms or heavy stratospheric balloons results in a lack of accurate information on vertical distribution of atmospheric constituents. Whereas light-weight instruments carried by meteorological balloons are becoming progressively available, their usage is constrained by the cost of the equipment or the recovery operations. The evolving need in cost-efficient observations for UTS process studies has led to development of small airborne platforms - unmanned aerial vehicles (UAV), capable of carrying small sensors for in-situ measurements. We present a new UAV-based stratospheric sounding platform capable of carrying scientific payload of up to 2 kg. The airborne platform comprises of a latex meteorological balloon and detachable flying wing type UAV with internal measurement controller. The UAV is launched on a balloon to stratospheric altitudes up to 20 km, where it can be automatically released by autopilot or by a remote command sent from the ground control. Having been released from the balloon the UAV glides down and returns to the launch position. Autopilot using 3-axis gyro, accelerometer, barometer, compas and GPS navigation provides flight stabilization and optimal way back trajectory. Backup manual control is provided for emergencies. During the flight the onboard measurement controller stores the data into internal memory and transmits current flight parameters to the ground station via telemetry. Precise operation of the flight control systems ensures safe landing at the launch point. A series of field tests of the detachable stratospheric UAV has been conducted. The scientific payload included the following instruments involved in different flights: a) stratospheric Lyman-alpha hygrometer (FLASH); b) backscatter sonde; c) electrochemical

Distributed Actuation and Sensing on an Uninhabited Aerial Vehicle

NASA Technical Reports Server (NTRS)

Barnwell, William Garrard

2003-01-01

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). The UAV is modified to serve as a flying, controls research, testbed. This effector/sensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

PubMed Central

Gonzalez, Luis F.; Montes, Glen A.; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J.

2016-01-01

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification. PMID:26784196

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

PubMed

Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

2016-01-14

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Unmanned aerial vehicles in construction and worker safety.

PubMed

Howard, John; Murashov, Vladimir; Branche, Christine M

2018-01-01

Applications of unmanned aerial vehicles (UAVs) for military, recreational, public, and commercial uses have expanded significantly in recent years. In the construction industry, UAVs are used primarily for monitoring of construction workflow and job site logistics, inspecting construction sites to assess structural integrity, and for maintenance assessments. As is the case with other emerging technologies, occupational safety assessments of UAVs lag behind technological advancements. UAVs may create new workplace hazards that need to be evaluated and managed to ensure their safe operation around human workers. At the same time, UAVs can perform dangerous tasks, thereby improving workplace safety. This paper describes the four major uses of UAVs, including their use in construction, the potential risks of their use to workers, approaches for risk mitigation, and the important role that safety and health professionals can play in ensuring safe approaches to the their use in the workplace. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Development of a Data Acquisition System for Unmanned Aerial Vehicle (UAV) System Identification

NASA Astrophysics Data System (ADS)

Lear, Donald Joseph

Aircraft system identification techniques are developed for fixed wing Unmanned Aerial Vehicles (UAV). The use of a designed flight experiment with measured system inputs/outputs can be used to derive aircraft stability derivatives. This project set out to develop a methodology to support an experiment to model pitch damping in the longitudinal short-period mode of a UAV. A Central Composite Response Surface Design was formed using angle of attack and power levels as factors to test for the pitching moment coefficient response induced by a multistep pitching maneuver. Selecting a high-quality data acquisition platform was critical to the success of the project. This system was designed to support fixed wing research through the addition of a custom air data vane capable of measuring angle of attack and sideslip, as well as an airspeed sensor. A Pixhawk autopilot system serves as the core and modification of the device firmware allowed for the integration of custom sensors and custom RC channels dedicated to performing system identification maneuvers. Tests were performed on all existing Pixhawk sensors to validate stated uncertainty values. The air data system was calibrated in a low speed wind tunnel and dynamic performance was verified. The assembled system was then installed in a commercially available UAV known as an Air Titan FPV in order to test the Pixhawk's automated flight maneuvers and determine the final performance of each sensor. Flight testing showed all the critical sensors produced acceptable data for further research. The Air Titan FPV airframe was found to be very flexible and did not lend itself well to accurate measurement of inertial properties. This realization prohibited the construction of the required math models for longitudinal dynamics. It is recommended that future projects using the developed methods choose an aircraft with a more rigid airframe.

Detail design of empennage of an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Sarker, Md. Samad; Panday, Shoyon; Rasel, Md; Salam, Md. Abdus; Faisal, Kh. Md.; Farabi, Tanzimul Hasan

2017-12-01

In order to maintain the operational continuity of air defense systems, unmanned autonomous or remotely controlled unmanned aerial vehicle (UAV) plays a great role as a target for the anti-aircraft weapons. The aerial vehicle must comply with the requirements of high speed, remotely controlled tracking and navigational aids, operational sustainability and sufficient loiter time. It can also be used for aerial reconnaissance, ground surveillance and other intelligence operations. This paper aims to develop a complete tail design of an unmanned aerial vehicle using Systems Engineering approach. The design fulfils the requirements of longitudinal and directional trim, stability and control provided by the horizontal and vertical tail. Tail control surfaces are designed to provide sufficient control of the aircraft in critical conditions. Design parameters obtained from wing design are utilized in the tail design process as required. Through chronological calculations and successive iterations, optimum values of 26 tail design parameters are determined.

Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery.

PubMed

Casado, Monica Rivas; Gonzalez, Rocio Ballesteros; Kriechbaumer, Thomas; Veal, Amanda

2015-11-04

European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

Measured Noise from Small Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Cabell, Randolph; McSwain, Robert; Grosveld, Ferdinand

2016-01-01

Proposed uses of small unmanned aerial vehicles (UAVs), including home package delivery, have the potential to expose large portions of communities to a new noise source. This paper discusses results of flyover noise measurements of four small UAVs, including an internal combustion-powered model airplane and three battery-powered multicopters. Basic noise characteristics of these vehicles are discussed, including spectral properties and sound level metrics such as sound pressure level, effective perceived noise level, and sound exposure level. The size and aerodynamic characteristics of the multicopters in particular make their flight path susceptible to atmospheric disturbances such as wind gusts. These gusts, coupled with a flight control system that varies rotor speed to maintain vehicle stability, create an unsteady acoustic signature. The spectral variations resulting from this unsteadiness are explored, in both hover and flyover conditions for the multicopters. The time varying noise, which differs from the relatively steady noise generated by large transport aircraft, may complicate the prediction of human annoyance using conventional sound level metrics.

Aerial vehicles collision avoidance using monocular vision

NASA Astrophysics Data System (ADS)

Balashov, Oleg; Muraviev, Vadim; Strotov, Valery

2016-10-01

In this paper image-based collision avoidance algorithm that provides detection of nearby aircraft and distance estimation is presented. The approach requires a vision system with a single moving camera and additional information about carrier's speed and orientation from onboard sensors. The main idea is to create a multi-step approach based on a preliminary detection, regions of interest (ROI) selection, contour segmentation, object matching and localization. The proposed algorithm is able to detect small targets but unlike many other approaches is designed to work with large-scale objects as well. To localize aerial vehicle position the system of equations relating object coordinates in space and observed image is solved. The system solution gives the current position and speed of the detected object in space. Using this information distance and time to collision can be estimated. Experimental research on real video sequences and modeled data is performed. Video database contained different types of aerial vehicles: aircrafts, helicopters, and UAVs. The presented algorithm is able to detect aerial vehicles from several kilometers under regular daylight conditions.

Modeling of Air-to-Air Refueling for an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Spears, Brian Raul

Air-to-air refueling is important to the military for enabling aircraft to remain in the air for long periods of time, reducing the need for forward bases, and allowing aircraft to stay on mission for longer intervals. Although this has been available for traditional military aircraft for several decades, it has not been implemented for the use of Unmanned Aerial Vehicles (UAV). This thesis uses a panel method, VSAERO, to examine the effects that a large tanker aircraft will have on a small unmanned aerial vehicle during a refueling process. The primary cause of conditions behind the tanker aircraft is the wake generated by the wingtip vortices of the aircraft. The planes used for this analysis were an Airbus A320 as the tanker, and a General Atomic MQ-9 as the receiver. The techniques used were to examine literature on aerial refueling, and analyze the aerodynamic characteristics of the UAV. The most important properties that were examined were the rolling moment, pitching moment, and lift. These characteristics were used to determine the feasibility of the UAV being able to withstand the conditions behind the A320. Through the analysis of the MQ-9's aerodynamic characteristics when in ideal conditions, along with its maximum rolling moment, and those same characteristics when flying behind the tanker, it was determined that the MQ-9 would be able to maintain position behind an A320 in order to complete the aerial refueling process.

[Small unmanned aerial vehicles for low-altitude remote sensing and its application progress in ecology.

PubMed

Sun, Zhong Yu; Chen, Yan Qiao; Yang, Long; Tang, Guang Liang; Yuan, Shao Xiong; Lin, Zhi Wen

2017-02-01

Low-altitude unmanned aerial vehicles (UAV) remote sensing system overcomes the deficiencies of space and aerial remote sensing system in resolution, revisit period, cloud cover and cost, which provides a novel method for ecological research on mesoscale. This study introduced the composition of UAV remote sensing system, reviewed its applications in species, population, community and ecosystem ecology research. Challenges and opportunities of UAV ecology were identified to direct future research. The promising research area of UAV ecology includes the establishment of species morphology and spectral characteristic data base, species automatic identification, the revelation of relationship between spectral index and plant physiological processes, three-dimension monitoring of ecosystem, and the integration of remote sensing data from multi resources and multi scales. With the development of UAV platform, data transformation and sensors, UAV remote sensing technology will have wide application in ecology research.

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

NASA Astrophysics Data System (ADS)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Modeling and Optimization of Multiple Unmanned Aerial Vehicles System Architecture Alternatives

PubMed Central

Wang, Weiping; He, Lei

2014-01-01

Unmanned aerial vehicle (UAV) systems have already been used in civilian activities, although very limitedly. Confronted different types of tasks, multi UAVs usually need to be coordinated. This can be extracted as a multi UAVs system architecture problem. Based on the general system architecture problem, a specific description of the multi UAVs system architecture problem is presented. Then the corresponding optimization problem and an efficient genetic algorithm with a refined crossover operator (GA-RX) is proposed to accomplish the architecting process iteratively in the rest of this paper. The availability and effectiveness of overall method is validated using 2 simulations based on 2 different scenarios. PMID:25140328

Small catchments DEM creation using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Gafurov, A. M.

2018-01-01

Digital elevation models (DEM) are an important source of information on the terrain, allowing researchers to evaluate various exogenous processes. The higher the accuracy of DEM the better the level of the work possible. An important source of data for the construction of DEMs are point clouds obtained with terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAV). In this paper, we present the results of constructing a DEM on small catchments using UAVs. Estimation of the UAV DEM showed comparable accuracy with the TLS if real time kinematic Global Positioning System (RTK-GPS) ground control points (GCPs) and check points (CPs) were used. In this case, the main source of errors in the construction of DEMs are the errors in the referencing of survey results.

High-Fidelity Computational Aerodynamics of Multi-Rotor Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Ventura Diaz, Patricia; Yoon, Seokkwan

2018-01-01

High-fidelity Computational Fluid Dynamics (CFD) simulations have been carried out for several multi-rotor Unmanned Aerial Vehicles (UAVs). Three vehicles have been studied: the classic quadcopter DJI Phantom 3, an unconventional quadcopter specialized for forward flight, the SUI Endurance, and an innovative concept for Urban Air Mobility (UAM), the Elytron 4S UAV. The three-dimensional unsteady Navier-Stokes equations are solved on overset grids using high-order accurate schemes, dual-time stepping, and a hybrid turbulence model. The DJI Phantom 3 is simulated with different rotors and with both a simplified airframe and the real airframe including landing gear and a camera. The effects of weather are studied for the DJI Phantom 3 quadcopter in hover. The SUI En- durance original design is compared in forward flight to a new configuration conceived by the authors, the hybrid configuration, which gives a large improvement in forward thrust. The Elytron 4S UAV is simulated in helicopter mode and in airplane mode. Understanding the complex flows in multi-rotor vehicles will help design quieter, safer, and more efficient future drones and UAM vehicles.

Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

PubMed Central

Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan

2015-01-01

Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032×778 resolution) and 150 ms outdoors (1280×720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms. PMID:26393599

Concept design of a disaster response unmanned aerial vehicle for India

NASA Astrophysics Data System (ADS)

Vashi, Y.; Jai, U.; Atluri, R.; Sunjii, M.; Kashyap, Y.; Ashok, V.; Khilari, S.; Jain, K.; Aravind Raj, S.

2017-12-01

The Indian sub-continent experiences frequent flooding, earthquakes and landslides. During the times of peril, live surveillance of the disaster zone facilitates the disaster agencies in locating and aiding the affected people. For this reason, development of a micro unmanned aerial vehicle (UAV) can be an optimal solution. This article provides a conceptualization of a UAV model that meets the need of the country. A comparison of different aircraft components and their optimization and sensitivity analyses are presented. In the end, this research produces a preliminary design of UAV that can accomplish surveillance and payload dropping missions in disaster affected areas.

Infrared search and track performance estimates for detection of commercial unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Nicholas, Robert; Driggers, Ronald; Shelton, David; Furxhi, Orges

2018-04-01

Unmanned aerial vehicles (UAVs) have become more readily available in the past 5 years and are proliferating rapidly. New aviation regulations are accelerating the use of UAVs in many applications. As a result, there are increasing concerns of potential air threats in situational environments including commercial airport security and drug trafficking. In this study, radiometric signatures of commercially available miniature UAVs is determined for long-wave infrared (LWIR) bands in both clear sky and partial cloudy conditions. Results are presented that compare LWIR performance estimates for the detection of commercial UAVs via infrared search and track (IRST) systems with two candidate sensors.

Evaluating the use of unmanned aerial vehicles for transportation purposes : [parts A-D].

DOT National Transportation Integrated Search

2015-03-01

Advances in unmanned aerial vehicle (UAV) technology have enabled these tools to become : easier to use and afford. In a budget-limited environment, these flexible remote sensing : technologies can help address transportation agency needs in operatio...

Counter-Unmanned Aerial Vehicle Warfare: Kill Authorizations for the Carrier Strike Group

DTIC Science & Technology

2016-06-10

COUNTER-UNMANNED AERIAL VEHICLE WARFARE: KILL AUTHORIZATIONS FOR THE CARRIER STRIKE GROUP A thesis presented to the Faculty...the Carrier Strike Group 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) LCDR Joshua C. Mattingly, U.S...including armed UAVs in an offensive role, but counter- UAV warfare is a new warfare area within the larger realm of air defense. Small Group 1 and 2

The left wing of NASA's Altair unmanned aerial vehicle (UAV) rests in a jig during construction at G

NASA Technical Reports Server (NTRS)

2002-01-01

The left wing of NASA's Altair unmanned aerial vehicle (UAV) rests in a jig during construction at General Atomics Aeronautical Systems, Inc., (GA-ASI) facility at Adelanto, Calif. General Atomics Aeronautical Systems, Inc., is developing the Altair version of its Predator B unmanned reconnaissance aircraft under NASA's Environmental Research Aircraft and Sensor Technology (ERAST) project. NASA plans to use the Altair as a technology demonstrator to validate a variety of command and control technologies for UAVs, as well as demonstrate the capability to perform a variety of Earth science missions. The Altair is designed to carry an 700-lb. payload of scientific instruments and imaging equipment for as long as 32 hours at up to 52,000 feet altitude. Eleven-foot extensions have been added to each wing, giving the Altair an overall wingspan of 86 feet with an aspect ratio of 23. It is powered by a 700-hp. rear-mounted TPE-331-10 turboprop engine, driving a three-blade propeller. Altair is scheduled to begin flight tests in the fourth quarter of 2002, and be acquired by NASA following successful completion of basic airworthiness tests in early 2003 for evaluation of over-the-horizon control, detect, see and avoid and other technologies required to allow UAVs to operate safely with other aircraft in the national airspace.

Delivery of Unmanned Aerial Vehicle Data

NASA Technical Reports Server (NTRS)

Ivancic, William D.; Sullivan, Donald V.

2011-01-01

To support much of NASA's Upper Atmosphere Research Program science, NASA has acquired two Global Hawk Unmanned Aerial Vehicles (UAVs). Two major missions are currently planned using the Global Hawk: the Global Hawk Pacific (GloPac) and the Genesis and Rapid Intensification Processes (GRIP) missions. This paper briefly describes GloPac and GRIP, the concept of operations and the resulting requirements and communication architectures. Also discussed are requirements for future missions that may use satellite systems and networks owned and operated by third parties.

Sensor-driven area coverage for an autonomous fixed-wing unmanned aerial vehicle.

PubMed

Paull, Liam; Thibault, Carl; Nagaty, Amr; Seto, Mae; Li, Howard

2014-09-01

Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are more appropriate for larger scale area surveying since they can cover ground more quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage a challenging task. Most previous approaches to area coverage planning are offline and assume that the UAV can follow the planned trajectory exactly. In this paper, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft is able to plan paths in situ based on sensor data and an accurate model of the on-board camera used for coverage. An information theoretic approach is used that selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept previously developed for autonomous underwater vehicles is extended to UAVs and ensures that the vehicle is able to achieve its global coverage mission. The coverage map over the workspace uses the projective camera model and compares the expected area of the target on the ground and the actual area covered on the ground by each pixel in the image. The camera is mounted on a two-axis gimbal and can either be stabilized or optimized for maximal coverage. Hardware-in-the-loop simulation results and real hardware implementation on a fixed-wing UAV show the effectiveness of the approach. By including the already developed automatic takeoff and landing capabilities, we now have a fully automated and robust platform for performing aerial imagery surveys.

Fault-Tolerant and Reconfigurable Control of Unmanned Aerial Vehicles (UAVs)

DTIC Science & Technology

2008-02-29

forces and moments are expressed as functions of angle of attack, sideslip angle, angular rates, and control surface deflection. L, M, and N are...invertible. As for matrix B, the control surfaces of the reusable launch vehicle are designed to control each axes angular rate of aircraft...literature as being invertible. As for matrix B, the control surfaces of the UAV are designed to control angular rate along each axis of the aircraft

The UAV take-off and landing system used for small areas of mobile vehicles

NASA Astrophysics Data System (ADS)

Ren, Tian-Yu; Duanmu, Qing-Duo; Wu, Bo-Qi

2018-03-01

In order to realize an UAV formation cluster system based on the current GPS and the fault and insufficiency of Beidou integrated navigation system in strong jamming environment. Due to the impact of the compass on the plane crash, navigation system error caused by the mobile area to help reduce the need for large landing sites and not in the small fast moving area to achieve the reality of the landing. By using Strapdown inertial and all-optical system to form Composite UAV flight control system, the photoelectric composite strapdown inertial coupling is realized, and through the laser and microwave telemetry link compound communication mechanism, using all-optical strapdown inertial and visual navigation system to solve the deviation of take-off and landing caused by electromagnetic interference, all-optical bidirectional data link realizes two-way position correction of landing site and aircraft, thus achieves the accurate recovery of UAV formation cluster in the mobile narrow area which the traditional navigation system can't realize. This system is a set of efficient unmanned aerial vehicle Group Take-off/descending system, which is suitable for many tasks, and not only realizes the reliable continuous navigation under the complex electromagnetic interference environment, moreover, the intelligent flight and Take-off and landing of unmanned aerial vehicles relative to the fast moving and small recovery sites in complex electromagnetic interference environment can not only improve the safe operation rate of unmanned aerial vehicle, but also guarantee the operation safety of the aircraft, and the more has important social value for the application foreground of the aircraft.

Mathematical model of unmanned aerial vehicle used for endurance autonomous monitoring

NASA Astrophysics Data System (ADS)

Chelaru, Teodor-Viorel; Chelaru, Adrian

2014-12-01

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system, based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.

Mission control of multiple unmanned aerial vehicles: a workload analysis.

PubMed

Dixon, Stephen R; Wickens, Christopher D; Chang, Dervon

2005-01-01

With unmanned aerial vehicles (UAVs), 36 licensed pilots flew both single-UAV and dual-UAV simulated military missions. Pilots were required to navigate each UAV through a series of mission legs in one of the following three conditions: a baseline condition, an auditory autoalert condition, and an autopilot condition. Pilots were responsible for (a) mission completion, (b) target search, and (c) systems monitoring. Results revealed that both the autoalert and the autopilot automation improved overall performance by reducing task interference and alleviating workload. The autoalert system benefited performance both in the automated task and mission completion task, whereas the autopilot system benefited performance in the automated task, the mission completion task, and the target search task. Practical implications for the study include the suggestion that reliable automation can help alleviate task interference and reduce workload, thereby allowing pilots to better handle concurrent tasks during single- and multiple-UAV flight control.

Using Unmanned Aerial Vehicle (UAV) for spatio-temporal monitoring of soil erosion and roughness in Chania, Crete, Greece

NASA Astrophysics Data System (ADS)

Alexakis, Dimitrios; Seiradakis, Kostas; Tsanis, Ioannis

2016-04-01

This article presents a remote sensing approach for spatio-temporal monitoring of both soil erosion and roughness using an Unmanned Aerial Vehicle (UAV). Soil erosion by water is commonly known as one of the main reasons for land degradation. Gully erosion causes considerable soil loss and soil degradation. Furthermore, quantification of soil roughness (irregularities of the soil surface due to soil texture) is important and affects surface storage and infiltration. Soil roughness is one of the most susceptible to variation in time and space characteristics and depends on different parameters such as cultivation practices and soil aggregation. A UAV equipped with a digital camera was employed to monitor soil in terms of erosion and roughness in two different study areas in Chania, Crete, Greece. The UAV followed predicted flight paths computed by the relevant flight planning software. The photogrammetric image processing enabled the development of sophisticated Digital Terrain Models (DTMs) and ortho-image mosaics with very high resolution on a sub-decimeter level. The DTMs were developed using photogrammetric processing of more than 500 images acquired with the UAV from different heights above the ground level. As the geomorphic formations can be observed from above using UAVs, shadowing effects do not generally occur and the generated point clouds have very homogeneous and high point densities. The DTMs generated from UAV were compared in terms of vertical absolute accuracies with a Global Navigation Satellite System (GNSS) survey. The developed data products were used for quantifying gully erosion and soil roughness in 3D as well as for the analysis of the surrounding areas. The significant elevation changes from multi-temporal UAV elevation data were used for estimating diachronically soil loss and sediment delivery without installing sediment traps. Concerning roughness, statistical indicators of surface elevation point measurements were estimated and various

Measuring orthometric water heights from lightweight Unmanned Aerial Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Olesen, Daniel; Jakobsen, Jakob; Reyna-Gutierrez, Jose Antonio; Bauer-Gottwein, Peter

2016-04-01

A better quantitative understanding of hydrologic processes requires better observations of hydrological variables, such as surface water area, water surface level, its slope and its temporal change. However, ground-based measurements of water heights are restricted to the in-situ measuring stations. Hence, the objective of remote sensing hydrology is to retrieve these hydraulic variables from spaceborne and airborne platforms. The forthcoming Surface Water and Ocean Topography (SWOT) satellite mission will be able to acquire water heights with an expected accuracy of 10 centimeters for rivers that are at least 100 m wide. Nevertheless, spaceborne missions will always face the limitations of: i) a low spatial resolution which makes it difficult to separate water from interfering surrounding areas and a tracking of the terrestrial water bodies not able to detect water heights in small rivers or lakes; ii) a limited temporal resolution which limits the ability to determine rapid temporal changes, especially during extremes. Unmanned Aerial Vehicles (UAVs) are one technology able to fill the gap between spaceborne and ground-based observations, ensuring 1) high spatial resolution; 2) tracking of the water bodies better than any satellite technology; 3) timing of the sampling which only depends on the operator 4) flexibility of the payload. Hence, this study focused on categorizing and testing sensors capable of measuring the range between the UAV and the water surface. The orthometric height of the water surface is then retrieved by subtracting the height above water measured by the sensors from the altitude above sea level retrieved by the onboard GPS. The following sensors were tested: a) a radar, b) a sonar c) a laser digital-camera based prototype developed at Technical University of Denmark. The tested sensors comply with the weight constraint of small UAVs (around 1.5 kg). The sensors were evaluated in terms of accuracy, maximum ranging distance and beam

An Analysis of the Influence of Flight Parameters in the Generation of Unmanned Aerial Vehicle (UAV) Orthomosaicks to Survey Archaeological Areas.

PubMed

Mesas-Carrascosa, Francisco-Javier; Notario García, María Dolores; Meroño de Larriva, Jose Emilio; García-Ferrer, Alfonso

2016-11-01

This article describes the configuration and technical specifications of a multi-rotor unmanned aerial vehicle (UAV) using a red-green-blue (RGB) sensor for the acquisition of images needed for the production of orthomosaics to be used in archaeological applications. Several flight missions were programmed as follows: flight altitudes at 30, 40, 50, 60, 70 and 80 m above ground level; two forward and side overlap settings (80%-50% and 70%-40%); and the use, or lack thereof, of ground control points. These settings were chosen to analyze their influence on the spatial quality of orthomosaicked images processed by Inpho UASMaster (Trimble, CA, USA). Changes in illumination over the study area, its impact on flight duration, and how it relates to these settings is also considered. The combined effect of these parameters on spatial quality is presented as well, defining a ratio between ground sample distance of UAV images and expected root mean square of a UAV orthomosaick. The results indicate that a balance between all the proposed parameters is useful for optimizing mission planning and image processing, altitude above ground level (AGL) being main parameter because of its influence on root mean square error (RMSE).

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle.

PubMed

Luo, Zhihao; Liu, Zhong; Shi, Jianmai

2017-05-17

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0-1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25-200 targets, 12-80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable.

Evaluation and development of unmanned aircraft (UAV) for UDOT needs.

DOT National Transportation Integrated Search

2012-05-01

This research involved the use of high-resolution aerial photography obtained from Unmanned Aerial Vehicles (UAV) to aid UDOT in monitoring and documenting State Roadway structures and associated issues. Using geo-referenced UAV high resolution aeria...

Visual signature reduction of unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Zhong, Z. W.; Ma, Z. X.; Jayawijayaningtiyas; Ngoh, J. H. H.

2016-10-01

With the emergence of unmanned aerial vehicles (UAVs) in multiple tactical defence missions, there was a need for an efficient visual signature suppression system for a more efficient stealth operation. One of our studies experimentally investigated the visual signature reduction of UAVs achieved through an active camouflage system. A prototype was constructed with newly developed operating software, Cloak, to provide active camouflage to the UAV model. The reduction of visual signature was analysed. Tests of the devices mounted on UAVs were conducted in another study. A series of experiments involved testing of the concept as well as the prototype. The experiments were conducted both in the laboratory and under normal environmental conditions. Results showed certain degrees of blending with the sky to create a camouflage effect. A mini-UAV made mostly out of transparent plastic was also designed and fabricated. Because of the transparency of the plastic material, the visibility of this UAV in the air is very small, and therefore the UAV is difficult to be detected. After re-designs and tests, eventually a practical system to reduce the visibility of UAVs viewed by human observers from the ground was developed. The system was evaluated during various outdoor tests. The scene target-to-background lightness contrast and the scene target-to-background colour contrast of the adaptive control system prototype were smaller than 10% at a stand-off viewing distance of 20-50 m.

Determination of the State of Strain of Large Floating Covers Using Unmanned Aerial Vehicle (UAV) Aided Photogrammetry

PubMed Central

Ong, Wern Hann; Chiu, Wing Kong; Kuen, Thomas; Kodikara, Jayantha

2017-01-01

Floating covers used in waste water treatment plants are one of the many structures formed with membrane materials. These structures are usually large and can spread over an area measuring 470 m × 170 m. The aim of this paper is to describe recent work to develop an innovative and effective approach for structural health monitoring (SHM) of such large membrane-like infrastructure. This paper will propose a potentially cost-effective non-contact approach for full-field strain and stress mapping using an unmanned aerial vehicle (UAV) mounted with a digital camera and a global positioning system (GPS) tracker. The aim is to use the images acquired by the UAV to define the geometry of the floating cover using photogrammetry. In this manner, any changes in the geometry of the floating cover due to forces acting beneath resulting from its deployment and usage can be determined. The time-scale for these changes is in terms of weeks and months. The change in the geometry can be implemented as input conditions to a finite element model (FEM) for stress prediction. This will facilitate the determination of the state of distress of the floating cover. This paper investigates the possibility of using data recorded from a UAV to predict the strain level and assess the health of such structures. An investigation was first conducted on a laboratory sized membrane structure instrumented with strain gauges for comparison against strains, which were computed from 3D scans of the membrane geometry. Upon validating the technique in the laboratory, it was applied to a more realistic scenario: an outdoor test membrane structure and capable UAV were constructed to see if the shape of the membrane could be computed. The membrane displacements were then used to calculate the membrane stress and strain, state demonstrating a new way to perform structural health monitoring on membrane structures. PMID:28788081

Determination of the State of Strain of Large Floating Covers Using Unmanned Aerial Vehicle (UAV) Aided Photogrammetry.

PubMed

Ong, Wern Hann; Chiu, Wing Kong; Kuen, Thomas; Kodikara, Jayantha

2017-07-28

Floating covers used in waste water treatment plants are one of the many structures formed with membrane materials. These structures are usually large and can spread over an area measuring 470 m × 170 m. The aim of this paper is to describe recent work to develop an innovative and effective approach for structural health monitoring (SHM) of such large membrane-like infrastructure. This paper will propose a potentially cost-effective non-contact approach for full-field strain and stress mapping using an unmanned aerial vehicle (UAV) mounted with a digital camera and a global positioning system (GPS) tracker. The aim is to use the images acquired by the UAV to define the geometry of the floating cover using photogrammetry. In this manner, any changes in the geometry of the floating cover due to forces acting beneath resulting from its deployment and usage can be determined. The time-scale for these changes is in terms of weeks and months. The change in the geometry can be implemented as input conditions to a finite element model (FEM) for stress prediction. This will facilitate the determination of the state of distress of the floating cover. This paper investigates the possibility of using data recorded from a UAV to predict the strain level and assess the health of such structures. An investigation was first conducted on a laboratory sized membrane structure instrumented with strain gauges for comparison against strains, which were computed from 3D scans of the membrane geometry. Upon validating the technique in the laboratory, it was applied to a more realistic scenario: an outdoor test membrane structure and capable UAV were constructed to see if the shape of the membrane could be computed. The membrane displacements were then used to calculate the membrane stress and strain, state demonstrating a new way to perform structural health monitoring on membrane structures.

Detection of unmanned aerial vehicles using a visible camera system.

PubMed

Hu, Shuowen; Goldman, Geoffrey H; Borel-Donohue, Christoph C

2017-01-20

Unmanned aerial vehicles (UAVs) flown by adversaries are an emerging asymmetric threat to homeland security and the military. To help address this threat, we developed and tested a computationally efficient UAV detection algorithm consisting of horizon finding, motion feature extraction, blob analysis, and coherence analysis. We compare the performance of this algorithm against two variants, one using the difference image intensity as the motion features and another using higher-order moments. The proposed algorithm and its variants are tested using field test data of a group 3 UAV acquired with a panoramic video camera in the visible spectrum. The performance of the algorithms was evaluated using receiver operating characteristic curves. The results show that the proposed approach had the best performance compared to the two algorithmic variants.

Vibration energy harvesting for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Anton, Steven R.; Inman, Daniel J.

2008-03-01

Unmanned aerial vehicles (UAVs) are a critical component of many military operations. Over the last few decades, the evolution of UAVs has given rise to increasingly smaller aircraft. Along with the development of smaller UAVs, termed mini UAVs, has come issues involving the endurance of the aircraft. Endurance in mini UAVs is problematic because of the limited size of the fuel systems that can be incorporated into the aircraft. A large portion of the total mass of many electric powered mini UAVs, for example, is the rechargeable battery power source. Energy harvesting is an attractive technology for mini UAVs because it offers the potential to increase their endurance without adding significant mass or the need to increase the size of the fuel system. This paper investigates the possibility of harvesting vibration and solar energy in a mini UAV. Experimentation has been carried out on a remote controlled (RC) glider aircraft with a 1.8 m wing span. This aircraft was chosen to replicate the current electric mini UAVs used by the military today. The RC glider was modified to include two piezoelectric patches placed at the roots of the wings and a cantilevered piezoelectric beam installed in the fuselage to harvest energy from wing vibrations and rigid body motions of the aircraft, as well as two thin film photovoltaic panels attached to the top of the wings to harvest energy from sunlight. Flight testing has been performed and the power output of the piezoelectric and photovoltaic devices has been examined.

Research on the Application of Rapid Surveying and Mapping for Large Scare Topographic Map by Uav Aerial Photography System

NASA Astrophysics Data System (ADS)

Gao, Z.; Song, Y.; Li, C.; Zeng, F.; Wang, F.

2017-08-01

Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.

Real time target allocation in cooperative unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kudleppanavar, Ganesh

The prolific development of Unmanned Aerial Vehicles (UAV's) in recent years has the potential to provide tremendous advantages in military, commercial and law enforcement applications. While safety and performance take precedence in the development lifecycle, autonomous operations and, in particular, cooperative missions have the ability to significantly enhance the usability of these vehicles. The success of cooperative missions relies on the optimal allocation of targets while taking into consideration the resource limitation of each vehicle. The task allocation process can be centralized or decentralized. This effort presents the development of a real time target allocation algorithm that considers available stored energy in each vehicle while minimizing the communication between each UAV. The algorithm utilizes a nearest neighbor search algorithm to locate new targets with respect to existing targets. Simulations show that this novel algorithm compares favorably to the mixed integer linear programming method, which is computationally more expensive. The implementation of this algorithm on Arduino and Xbee wireless modules shows the capability of the algorithm to execute efficiently on hardware with minimum computation complexity.

Research for new UAV capabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Canavan, G.H.; Leadabrand, R.

1996-07-01

This paper discusses research for new Unmanned Aerial Vehicles (UAV) capabilities. Findings indicate that UAV performance could be greatly enhanced by modest research. Improved sensors and communications enhance near term cost effectiveness. Improved engines, platforms, and stealth improve long term effectiveness.

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition

Unmanned aerial vehicles for surveying marine fauna: assessing detection probability.

PubMed

Hodgson, Amanda; Peel, David; Kelly, Natalie

2017-06-01

Aerial surveys are conducted for various fauna to assess abundance, distribution, and habitat use over large spatial scales. They are traditionally conducted using light aircraft with observers recording sightings in real time. Unmanned Aerial Vehicles (UAVs) offer an alternative with many potential advantages, including eliminating human risk. To be effective, this emerging platform needs to provide detection rates of animals comparable to traditional methods. UAVs can also acquire new types of information, and this new data requires a reevaluation of traditional analyses used in aerial surveys; including estimating the probability of detecting animals. We conducted 17 replicate UAV surveys of humpback whales (Megaptera novaeangliae) while simultaneously obtaining a 'census' of the population from land-based observations, to assess UAV detection probability. The ScanEagle UAV, carrying a digital SLR camera, continuously captured images (with 75% overlap) along transects covering the visual range of land-based observers. We also used ScanEagle to conduct focal follows of whale pods (n = 12, mean duration = 40 min), to assess a new method of estimating availability. A comparison of the whale detections from the UAV to the land-based census provided an estimated UAV detection probability of 0.33 (CV = 0.25; incorporating both availability and perception biases), which was not affected by environmental covariates (Beaufort sea state, glare, and cloud cover). According to our focal follows, the mean availability was 0.63 (CV = 0.37), with pods including mother/calf pairs having a higher availability (0.86, CV = 0.20) than those without (0.59, CV = 0.38). The follows also revealed (and provided a potential correction for) a downward bias in group size estimates from the UAV surveys, which resulted from asynchronous diving within whale pods, and a relatively short observation window of 9 s. We have shown that UAVs are an effective alternative to

Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

2003-01-01

This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

Putting Technology to Work in Science - How to Select Unmanned Aerial Vehicles (UAV) and their Instrumentation for Atmospheric and Earth Surface Observations

NASA Astrophysics Data System (ADS)

Teller, Amit; Lange, Manfred; Ioannou, Stelios; Keleshis, Christos

2010-05-01

The Autonomous Flying Platforms for Atmospheric and Earth Surface Observations project (APAESO) of the Energy, Environment and Water Research Center (EEWRC) at the Cyprus Institute is aimed at the dual purpose of carrying out atmospheric and earth-surface observations in the Mediterranean. The APAESO platforms will offer the unique potential to determine physical, chemical and radiative atmospheric properties, aerosol and dust concentrations, atmospheric dynamics, surface morphology, vegetation and land use patterns as well as ocean surface properties (biology, waves, currents) and to carry out archaeological site reconnaissance and contaminant detection at high spatial resolution. The first phase of APAESO was dedicated to the preliminary design and the selection of an Unmanned Aerial Vehicle (UAV) as the backbone of the APAESO infrastructure. Selection of a UAV suitable for the many research objectives as outlined above is challenging because the UAV technology is new and rapidly evolving. This notwithstanding, a very large number of systems, mostly utilized for defense purposes, are currently available. The major challenge in the selection process lies in considering the trade-off between different platform characteristics (e.g. payload weight, endurance, max. altitude for operation and price) and in optimizing the potential performance of the UAV. Based on the required characteristics for the UAV platform, a survey of possible UAVs and suitable sensors was prepared based on various data sources. We used an elimination process in order to consider only a few models for the final selection process out of about 1000 commercially available UAV models that were initially investigated. The presentation will discuss the main scientific objectives that determine the specification of the UAV platform, major considerations in selecting best available technology for our needs and will briefly describe the next phases of the project.

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind.

PubMed

Luo, He; Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided.

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind

PubMed Central

Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided. PMID:29561888

UAV using the open-source flight-control-system in the application of aerial survey

NASA Astrophysics Data System (ADS)

Huang, Ji-chen; Ru, Chen

2015-12-01

The aerial survey as one of the branches of the Space Information Technology system, has an important application in data acquisition of the earth's surface. In recent years, the trend of UVA (unmanned aerial vehicle) to replace traditional survey aircraft has become increasingly obvious with the progress of science and technology. At present, the price of the commercial UAV Flight Control System is higher, limiting the application of UVA. This paper mainly discusses the possibility that the open-source's flight-control-system take the place of the commercial one. Result is that the costs of UVA are reduced, and make the application more widely.

Unmanned Aerial Vehicles Produce High-Resolution Seasonally-Relevant Imagery for Classifying Wetland Vegetation

NASA Astrophysics Data System (ADS)

Marcaccio, J. V.; Markle, C. E.; Chow-Fraser, P.

2015-08-01

With recent advances in technology, personal aerial imagery acquired with unmanned aerial vehicles (UAVs) has transformed the way ecologists can map seasonal changes in wetland habitat. Here, we use a multi-rotor (consumer quad-copter, the DJI Phantom 2 Vision+) UAV to acquire a high-resolution (< 8 cm) composite photo of a coastal wetland in summer 2014. Using validation data collected in the field, we determine if a UAV image and SWOOP (Southwestern Ontario Orthoimagery Project) image (collected in spring 2010) differ in their classification of type of dominant vegetation type and percent cover of three plant classes: submerged aquatic vegetation, floating aquatic vegetation, and emergent vegetation. The UAV imagery was more accurate than available SWOOP imagery for mapping percent cover of submergent and floating vegetation categories, but both were able to accurately determine the dominant vegetation type and percent cover of emergent vegetation. Our results underscore the value and potential for affordable UAVs (complete quad-copter system < 3,000 CAD) to revolutionize the way ecologists obtain imagery and conduct field research. In Canada, new UAV regulations make this an easy and affordable way to obtain multiple high-resolution images of small (< 1.0 km2) wetlands, or portions of larger wetlands throughout a year.

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle

PubMed Central

Luo, Zhihao; Liu, Zhong; Shi, Jianmai

2017-01-01

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0–1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25–200 targets, 12–80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable. PMID:28513552

Fault detection and multiclassifier fusion for unmanned aerial vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Yan, Weizhong

2001-03-01

UAVs demand more accurate fault accommodation for their mission manager and vehicle control system in order to achieve a reliability level that is comparable to that of a pilot aircraft. This paper attempts to apply multi-classifier fusion techniques to achieve the necessary performance of the fault detection function for the Lockheed Martin Skunk Works (LMSW) UAV Mission Manager. Three different classifiers that meet the design requirements of the fault detection of the UAAV are employed. The binary decision outputs from the classifiers are then aggregated using three different classifier fusion schemes, namely, majority vote, weighted majority vote, and Naieve Bayes combination. All of the three schemes are simple and need no retraining. The three fusion schemes (except the majority vote that gives an average performance of the three classifiers) show the classification performance that is better than or equal to that of the best individual. The unavoidable correlation between the classifiers with binary outputs is observed in this study. We conclude that it is the correlation between the classifiers that limits the fusion schemes to achieve an even better performance.

Unmanned aerial vehicles (drones) to prevent drowning.

PubMed

Seguin, Celia; Blaquière, Gilles; Loundou, Anderson; Michelet, Pierre; Markarian, Thibaut

2018-06-01

Drowning literature have highlighted the submersion time as the most powerful predictor in assessing the prognosis. Reducing the time taken to provide a flotation device and prevent submersion appears of paramount importance. Unmanned aerial vehicles (UAVs) can provide the location of the swimmer and a flotation device. The objective of this simulation study was to evaluate the efficiency of a UAV in providing a flotation device in different sea conditions, and to compare the times taken by rescue operations with and without a UAV (standard vs UAV intervention). Several comparisons were made using professional lifeguards acting as simulated victims. A specifically-shaped UAV was used to allow us to drop an inflatable life buoy into the water. During the summer of 2017, 28 tests were performed. UAV use was associated with a reduction of time it took to provide a flotation device to the simulated victim compared with standard rescue operations (p < 0.001 for all measurements) and the time was reduced even further in moderate (81 ± 39 vs 179 ± 78 s; p < 0.001) and rough sea conditions (99 ± 34 vs 198 ± 130 s; p < 0.001). The times taken for UAV to locate the simulated victim, identify them and drop the life buoy were not altered by the weather conditions. UAV can deliver a flotation device to a swimmer safely and quickly. The addition of a UAV in rescue operations could improve the quality and speed of first aid while keeping lifeguards away from dangerous sea conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

An Analysis of the Influence of Flight Parameters in the Generation of Unmanned Aerial Vehicle (UAV) Orthomosaicks to Survey Archaeological Areas

PubMed Central

Mesas-Carrascosa, Francisco-Javier; Notario García, María Dolores; Meroño de Larriva, Jose Emilio; García-Ferrer, Alfonso

2016-01-01

This article describes the configuration and technical specifications of a multi-rotor unmanned aerial vehicle (UAV) using a red–green–blue (RGB) sensor for the acquisition of images needed for the production of orthomosaics to be used in archaeological applications. Several flight missions were programmed as follows: flight altitudes at 30, 40, 50, 60, 70 and 80 m above ground level; two forward and side overlap settings (80%–50% and 70%–40%); and the use, or lack thereof, of ground control points. These settings were chosen to analyze their influence on the spatial quality of orthomosaicked images processed by Inpho UASMaster (Trimble, CA, USA). Changes in illumination over the study area, its impact on flight duration, and how it relates to these settings is also considered. The combined effect of these parameters on spatial quality is presented as well, defining a ratio between ground sample distance of UAV images and expected root mean square of a UAV orthomosaick. The results indicate that a balance between all the proposed parameters is useful for optimizing mission planning and image processing, altitude above ground level (AGL) being main parameter because of its influence on root mean square error (RMSE). PMID:27809293

Bird's-Eye View of Sampling Sites: Using Unmanned Aerial Vehicles to Make Chemistry Fieldwork Videos

ERIC Educational Resources Information Center

Fung, Fun Man; Watts, Simon Francis

2017-01-01

Drones, unmanned aerial vehicles (UAVs), usually helicopters or airplanes, are commonly used for warfare, aerial surveillance, and recreation. In recent years, drones have become more accessible to the public as a platform for photography. In this report, we explore the use of drones as a new technological filming tool to enhance student learning…

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

PubMed

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-08-19

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Meteorological and Remote Sensing Applications of High Altitude Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Schoenung, S. M.; Wegener, S. S.

1999-01-01

Unmanned aerial vehicles (UAVs) are maturing in performance and becoming available for routine use in environmental applications including weather reconnaissance and remote sensing. This paper presents a discussion of UAV characteristics and unique features compared with other measurement platforms. A summary of potential remote sensing applications is provided, along with details for four types of tropical cyclone missions. Capabilities of platforms developed under NASA's Environmental Research Aircraft and Sensor Technology (ERAST) program are reviewed, including the Altus, Perseus, and solar- powered Pathfinder, all of which have flown to over 57,000 ft (17 km). In many scientific missions, the science objectives drive the experimental design, thus defining the sensor payload, aircraft performance, and operational requirements. Some examples of science missions and the requisite UAV / payload system are given. A discussion of technology developments needed to fully mature UAV systems for routine operational use is included, along with remarks on future science and commercial UAV business opportunities.

Tracking with a Cooperatively Controlled Swarm of GMTI Equipped UAVS

DTIC Science & Technology

2008-12-02

with Ground Optimal Placement of GMTI UAVs for ground target tracking Abhijit Sinha°, Thia. Kirubarajana and Yaakov Bar-Shalom6 " Electrical and...Storrs, CT 06269, USA Abstract—With the recent advent of moderate-cost unmanned (or uninhabited) aerial vehicles (UAV) and their success in...the sensor platforms are mobile one has to decide the optimal placement of sensors. With the recent advent of af- fordable unmanned aerial vehicles

The Proliferation of Unmanned Aerial Vehicles: Terrorist Use, Capability, and Strategic Implications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ball, Ryan Jokl

There has been unparalleled proliferation and technological advancement of consumer unmanned aerial vehicles (UAVs) across the globe in the past several years. As witnessed over the course of insurgency tactics, it is difficult to restrict terrorists from using widely available technology they perceive as advantageous to their overall strategy. Through a review of the characteristics, consumer market landscape, tactics, and countertactics, as well as operational use of consumer-grade UAVs, this open-source report seeks to provide an introductory understanding of the terrorist-UAV landscape, as well as insights into present and future capabilities. The caveat is evaluating a developing technology haphazardly usedmore » by terrorists in asymmetric conflicts.« less

Small unmanned aerial vehicles for aeromagnetic surveys and their flights in the South Shetland Islands, Antarctica

NASA Astrophysics Data System (ADS)

Funaki, Minoru; Higashino, Shin-Ichiro; Sakanaka, Shinya; Iwata, Naoyoshi; Nakamura, Norihiro; Hirasawa, Naohiko; Obara, Noriaki; Kuwabara, Mikio

2014-12-01

We developed small computer-controlled unmanned aerial vehicles (UAVs, Ant-Plane) using parts and technology designed for model airplanes. These UAVs have a maximum flight range of 300-500 km. We planned aeromagnetic and aerial photographic surveys using the UAVs around Bransfield Basin, Antarctica, beginning from King George Island. However, we were unable to complete these flights due to unsuitable weather conditions and flight restrictions. Successful flights were subsequently conducted from Livingston Island to Deception Island in December 2011. This flight covered 302.4 km in 3:07:08, providing aeromagnetic and aerial photographic data from an altitude of 780 m over an area of 9 × 18 km around the northern region of Deception Island. The resulting magnetic anomaly map of Deception Island displayed higher resolution than the marine anomaly maps published already. The flight to South Bay in Livingston Island successfully captured aerial photographs that could be used for assessment of glacial and sea-ice conditions. It is unclear whether the cost-effectiveness of the airborne survey by UAV is superior to that of manned flight. Nonetheless, Ant-Plane 6-3 proved to be highly cost-effective for the Deception Island flight, considering the long downtime of the airplane in the Antarctic storm zone.

The payload bay in the nose of NASA's Altair unmanned aerial vehicle (UAV) will be able to carry up

NASA Technical Reports Server (NTRS)

2002-01-01

The payload bay in the nose of NASA's Altair unmanned aerial vehicle (UAV), shown here during final construction at General Atomics Aeronautical Systems, Inc., (GA-ASI) facility at Adelanto, Calif., will be able to carry up to 700 lbs. of sensors, imaging equipment and other instruments for Earth science missions. General Atomics Aeronautical Systems, Inc., is developing the Altair version of its Predator B unmanned reconnaissance aircraft under NASA's Environmental Research Aircraft and Sensor Technology (ERAST) project. NASA plans to use the Altair as a technology demonstrator to validate a variety of command and control technologies for UAVs, as well as demonstrate the capability to perform a variety of Earth science missions. The Altair is designed to carry an 700-lb. payload of scientific instruments and imaging equipment for as long as 32 hours at up to 52,000 feet altitude. Eleven-foot extensions have been added to each wing, giving the Altair an overall wingspan of 86 feet with an aspect ratio of 23. It is powered by a 700-hp. rear-mounted TPE-331-10 turboprop engine, driving a three-blade propeller. Altair is scheduled to begin flight tests in the fourth quarter of 2002, and be acquired by NASA following successful completion of basic airworthiness tests in early 2003 for evaluation of over-the-horizon control, detect, see and avoid and other technologies required to allow UAVs to operate safely with other aircraft in the national airspace.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

PubMed Central

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-01-01

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

[Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

PubMed

Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

2015-05-01

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

Small UAV Research and Evolution in Long Endurance Electric Powered Vehicles

NASA Technical Reports Server (NTRS)

Logan, Michael J.; Chu, Julio; Motter, Mark A.; Carter, Dennis L.; Ol, Michael; Zeune, Cale

2007-01-01

This paper describes recent research into the advancement of small, electric powered unmanned aerial vehicle (UAV) capabilities. Specifically, topics include the improvements made in battery technology, design methodologies, avionics architectures and algorithms, materials and structural concepts, propulsion system performance prediction, and others. The results of prototype vehicle designs and flight tests are discussed in the context of their usefulness in defining and validating progress in the various technology areas. Further areas of research need are also identified. These include the need for more robust operating regimes (wind, gust, etc.), and continued improvement in payload fraction vs. endurance.

Application of high resolution images from unmanned aerial vehicles for hydrology and range science

USDA-ARS?s Scientific Manuscript database

A common problem in many natural resource disciplines is the lack of high-enough spatial resolution images that can be used for monitoring and modeling purposes. Advances have been made in the utilization of Unmanned Aerial Vehicles (UAVs) in hydrology and rangeland science. By utilizing low fligh...

Auditory decision aiding in supervisory control of multiple unmanned aerial vehicles.

PubMed

Donmez, Birsen; Cummings, M L; Graham, Hudson D

2009-10-01

This article is an investigation of the effectiveness of sonifications, which are continuous auditory alerts mapped to the state of a monitored task, in supporting unmanned aerial vehicle (UAV) supervisory control. UAV supervisory control requires monitoring a UAV across multiple tasks (e.g., course maintenance) via a predominantly visual display, which currently is supported with discrete auditory alerts. Sonification has been shown to enhance monitoring performance in domains such as anesthesiology by allowing an operator to immediately determine an entity's (e.g., patient) current and projected states, and is a promising alternative to discrete alerts in UAV control. However, minimal research compares sonification to discrete alerts, and no research assesses the effectiveness of sonification for monitoring multiple entities (e.g., multiple UAVs). The authors conducted an experiment with 39 military personnel, using a simulated setup. Participants controlled single and multiple UAVs and received sonifications or discrete alerts based on UAV course deviations and late target arrivals. Regardless of the number of UAVs supervised, the course deviation sonification resulted in reactions to course deviations that were 1.9 s faster, a 19% enhancement, compared with discrete alerts. However, course deviation sonifications interfered with the effectiveness of discrete late arrival alerts in general and with operator responses to late arrivals when supervising multiple vehicles. Sonifications can outperform discrete alerts when designed to aid operators to predict future states of monitored tasks. However, sonifications may mask other auditory alerts and interfere with other monitoring tasks that require divided attention. This research has implications for supervisory control display design.

Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions

NASA Astrophysics Data System (ADS)

Zargarzadeh, H.; Nodland, David; Thotla, V.; Jagannathan, S.; Agarwal, S.

2012-06-01

Unmanned Aerial Vehicles (UAVs) are versatile aircraft with many applications, including the potential for use to detect unintended electromagnetic emissions from electronic devices. A particular area of recent interest has been helicopter unmanned aerial vehicles. Because of the nature of these helicopters' dynamics, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via output feedback control for trajectory tracking of a helicopter UAV using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic, virtual, and dynamic controllers and an observer. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The controller positions the helicopter, which is equipped with an antenna, such that the antenna can detect unintended emissions. The overall closed-loop system stability with the proposed controller is demonstrated by using Lyapunov analysis. Finally, results are provided to demonstrate the effectiveness of the proposed control design for positioning the helicopter for unintended emissions detection.

Flight dynamic investigations of flying wing with winglet configured unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Ro, Kapseong

2006-05-01

A swept wing tailless vehicle platform is well known in the radio control (RC) and sailing aircraft community for excellent spiral stability during soaring or thermaling, while exhibiting no Dutch roll behavior at high speed. When an unmanned aerial vehicle (UAV) is subjected to fly a mission in a rugged mountainous terrain where air current or thermal up-drift is frequently present, this is great aerodynamic benefit over the conventional cross-tailed aircraft which requires careful balance between lateral and directional stability. Such dynamic characteristics can be studied through vehicle dynamic modeling and simulation, but it requires configuration aerodynamic data through wind tunnel experiments. Obtaining such data is very costly and time consuming, and it is not feasible especially for low cost and dispensable UAVs. On the other hand, the vehicle autonomy is quite demanding which requires substantial understanding of aircraft dynamic characteristics. In this study, flight dynamics of an UAV platform based on flying wing with a large winglet was investigated through analytical modeling and numerical simulation. Flight dynamic modeling software and experimental formulae were used to obtain essential configuration aerodynamic characteristics, and linear flight dynamic analysis was carried out to understand the effect of wing sweep angle and winglet size on the vehicle dynamic characteristics.

Sitting in the Pilot's Seat; Optimizing Human-Systems Interfaces for Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Queen, Steven M.; Sanner, Kurt Gregory

2011-01-01

One of the pilot-machine interfaces (the forward viewing camera display) for an Unmanned Aerial Vehicle called the DROID (Dryden Remotely Operated Integrated Drone) will be analyzed for optimization. The goal is to create a visual display for the pilot that as closely resembles an out-the-window view as possible. There are currently no standard guidelines for designing pilot-machine interfaces for UAVs. Typically, UAV camera views have a narrow field, which limits the situational awareness (SA) of the pilot. Also, at this time, pilot-UAV interfaces often use displays that have a diagonal length of around 20". Using a small display may result in a distorted and disproportional view for UAV pilots. Making use of a larger display and a camera lens with a wider field of view may minimize the occurrences of pilot error associated with the inability to see "out the window" as in a manned airplane. It is predicted that the pilot will have a less distorted view of the DROID s surroundings, quicker response times and more stable vehicle control. If the experimental results validate this concept, other UAV pilot-machine interfaces will be improved with this design methodology.

Monitoring beach evolution using low-altitude aerial photogrammetry and UAV drones

NASA Astrophysics Data System (ADS)

Rovere, Alessio; Casella, Elisa; Vacchi, Matteo; Mucerino, Luigi; Pedroncini, Andrea; Ferrari, Marco; Firpo, Marco

2014-05-01

Beach monitoring is essential in order to understand the mechanisms of evolution of soft coasts, and the rates of erosion. Traditional beach monitoring techniques involve topographic and bathymetric surveys of the beach, and/or aerial photos repeated in time and compared through geographical information systems. A major problem of this kind of approach is the high economic cost. This often leads to increase the time lag between successive monitoring campaigns to reduce survey costs, with the consequence of fragmenting the information available for coastal zone management. MIRAMar is a project funded by Regione Liguria through the PO CRO European Social Fund, and has two main objectives: i) to study and develop an innovative technique, relatively low-cost, to monitor the evolution of the shoreline using low-altitude Unmanned Aerial Vehicle (UAV) photogrammetry; ii) to study the impact of different type of storm events on a vulnerable coastal tract subject to coastal erosion using also the data collected by the UAV instrument. To achieve these aims we use a drone with its hardware and software suit, traditional survey techniques (bathymetric surveys, topographic GPS surveys and GIS techniques) and we implement a numerical modeling chain (coupling hydrodynamic, wave and sand transport modules) in order to study the impact of different type of storm events on a vulnerable coastal tract subject to coastal erosion.

Solar-powered unmanned aerial vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reinhardt, K.C.; Lamp, T.R.; Geis, J.W.

1996-12-31

An analysis was performed to determine the impact of various power system components and mission requirements on the size of solar-powered high altitude long endurance (HALE)-type aircraft. The HALE unmanned aerial vehicle (UAV) has good potential for use in many military and civil applications. The primary power system components considered in this study were photovoltaic (PV) modules for power generation and regenerative fuel cells for energy storage. The impact of relevant component performance on UAV size and capability were considered; including PV module efficiency and mass, power electronics efficiency, and fuel cell specific energy. Mission parameters such as time ofmore » year, flight altitude, flight latitude, and payload mass and power were also varied to determine impact on UAV size. The aircraft analysis method used determines the required aircraft wing aspect ratio, wing area, and total mass based on maximum endurance or minimum required power calculations. The results indicate that the capacity of the energy storage system employed, fuel cells in this analysis, greatly impacts aircraft size, whereas the impact of PV module efficiency and mass is much less important. It was concluded that an energy storage specific energy (total system) of 250--500 Whr/kg is required to enable most useful missions, and that PV cells with efficiencies greater than {approximately} 12% are suitable for use.« less

Moving object detection using dynamic motion modelling from UAV aerial images.

PubMed

Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

2014-01-01

Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

Quantifying efficacy and limits of unmanned aerial vehicle (UAV) technology for weed seedling detection as affected by sensor resolution.

PubMed

Peña, José M; Torres-Sánchez, Jorge; Serrano-Pérez, Angélica; de Castro, Ana I; López-Granados, Francisca

2015-03-06

In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV) for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera), spatial (flight altitude) and temporal (the date of the study) resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2), when plants had 5-6 true leaves, had the highest weed detection accuracy (up to 91%). At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing) because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations.

Quantifying Efficacy and Limits of Unmanned Aerial Vehicle (UAV) Technology for Weed Seedling Detection as Affected by Sensor Resolution

PubMed Central

Peña, José M.; Torres-Sánchez, Jorge; Serrano-Pérez, Angélica; de Castro, Ana I.; López-Granados, Francisca

2015-01-01

In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV) for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera), spatial (flight altitude) and temporal (the date of the study) resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2), when plants had 5–6 true leaves, had the highest weed detection accuracy (up to 91%). At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing) because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations. PMID:25756867

System identification of a small low-cost unmanned aerial vehicle using flight data from low-cost sensors

NASA Astrophysics Data System (ADS)

Hoffer, Nathan Von

Remote sensing has traditionally been done with satellites and manned aircraft. While. these methods can yield useful scientificc data, satellites and manned aircraft have limitations in data frequency, process time, and real time re-tasking. Small low-cost unmanned aerial vehicles (UAVs) provide greater possibilities for personal scientic research than traditional remote sensing platforms. Precision aerial data requires an accurate vehicle dynamics model for controller development, robust flight characteristics, and fault tolerance. One method of developing a model is system identification (system ID). In this thesis system ID of a small low-cost fixed-wing T-tail UAV is conducted. The linerized longitudinal equations of motion are derived from first principles. Foundations of Recursive Least Squares (RLS) are presented along with RLS with an Error Filtering Online Learning scheme (EFOL). Sensors, data collection, data consistency checking, and data processing are described. Batch least squares (BLS) and BLS with EFOL are used to identify aerodynamic coecoefficients of the UAV. Results of these two methods with flight data are discussed.

Fault tolerant attitude sensing and force feedback control for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Jagadish, Chirag

Two aspects of an unmanned aerial vehicle are studied in this work. One is fault tolerant attitude determination and the other is to provide force feedback to the joy-stick of the UAV so as to prevent faulty inputs from the pilot. Determination of attitude plays an important role in control of aerial vehicles. One way of defining the attitude is through Euler angles. These angles can be determined based on the measurements of the projections of the gravity and earth magnetic fields on the three body axes of the vehicle. Attitude determination in unmanned aerial vehicles poses additional challenges due to limitations of space, payload, power and cost. Therefore it provides for almost no room for any bulky sensors or extra sensor hardware for backup and as such leaves no room for sensor fault issues either. In the face of these limitations, this study proposes a fault tolerant computing of Euler angles by utilizing multiple different computation methods, with each method utilizing a different subset of the available sensor measurement data. Twenty-five such methods have been presented in this document. The capability of computing the Euler angles in multiple ways provides a diversified redundancy required for fault tolerance. The proposed approach can identify certain sets of sensor failures and even separate the reference fields from the disturbances. A bank-to-turn maneuver of the NASA GTM UAV is used to demonstrate the fault tolerance provided by the proposed method as well as to demonstrate the method of determining the correct Euler angles despite interferences by inertial acceleration disturbances. Attitude computation is essential for stability. But as of today most UAVs are commanded remotely by human pilots. While basic stability control is entrusted to machine or the on-board automatic controller, overall guidance is usually with humans. It is therefore the pilot who sets the command/references through a joy-stick. While this is a good compromise between

Aerial Images from AN Uav System: 3d Modeling and Tree Species Classification in a Park Area

NASA Astrophysics Data System (ADS)

Gini, R.; Passoni, D.; Pinto, L.; Sona, G.

2012-07-01

The use of aerial imagery acquired by Unmanned Aerial Vehicles (UAVs) is scheduled within the FoGLIE project (Fruition of Goods Landscape in Interactive Environment): it starts from the need to enhance the natural, artistic and cultural heritage, to produce a better usability of it by employing audiovisual movable systems of 3D reconstruction and to improve monitoring procedures, by using new media for integrating the fruition phase with the preservation ones. The pilot project focus on a test area, Parco Adda Nord, which encloses various goods' types (small buildings, agricultural fields and different tree species and bushes). Multispectral high resolution images were taken by two digital compact cameras: a Pentax Optio A40 for RGB photos and a Sigma DP1 modified to acquire the NIR band. Then, some tests were performed in order to analyze the UAV images' quality with both photogrammetric and photo-interpretation purposes, to validate the vector-sensor system, the image block geometry and to study the feasibility of tree species classification. Many pre-signalized Control Points were surveyed through GPS to allow accuracy analysis. Aerial Triangulations (ATs) were carried out with photogrammetric commercial software, Leica Photogrammetry Suite (LPS) and PhotoModeler, with manual or automatic selection of Tie Points, to pick out pros and cons of each package in managing non conventional aerial imagery as well as the differences in the modeling approach. Further analysis were done on the differences between the EO parameters and the corresponding data coming from the on board UAV navigation system.

Development of Open source-based automatic shooting and processing UAV imagery for Orthoimage Using Smart Camera UAV

NASA Astrophysics Data System (ADS)

Park, J. W.; Jeong, H. H.; Kim, J. S.; Choi, C. U.

2016-06-01

Recently, aerial photography with unmanned aerial vehicle (UAV) system uses UAV and remote controls through connections of ground control system using bandwidth of about 430 MHz radio Frequency (RF) modem. However, as mentioned earlier, existing method of using RF modem has limitations in long distance communication. The Smart Camera equipments's LTE (long-term evolution), Bluetooth, and Wi-Fi to implement UAV that uses developed UAV communication module system carried out the close aerial photogrammetry with the automatic shooting. Automatic shooting system is an image capturing device for the drones in the area's that needs image capturing and software for loading a smart camera and managing it. This system is composed of automatic shooting using the sensor of smart camera and shooting catalog management which manages filmed images and information. Processing UAV imagery module used Open Drone Map. This study examined the feasibility of using the Smart Camera as the payload for a photogrammetric UAV system. The open soure tools used for generating Android, OpenCV (Open Computer Vision), RTKLIB, Open Drone Map.

A Water Vapor Differential Absorption LIDAR Design for Unpiloted Aerial Vehicles

NASA Technical Reports Server (NTRS)

DeYoung, Russell J.; Mead, Patricia F.

2004-01-01

This system study proposes the deployment of a water vapor Differential Absorption LIDAR (DIAL) system on an Altair unmanned aerial vehicle (UAV) platform. The Altair offers improved payload weight and volume performance, and longer total flight time as compared to other commercial UAV's. This study has generated a preliminary design for an Altair based water vapor DIAL system. The design includes a proposed DIAL schematic, a review of mechanical challenges such as temperature and humidity stresses on UAV deployed DIAL systems, an assessment of the available capacity for additional instrumentation (based on the proposed design), and an overview of possible weight and volume improvements associated with the use of customized electronic and computer hardware, and through the integration of advanced fiber-optic and laser products. The results of the study show that less than 17% of the available weight, less than 19% of the volume capacity, and approximately 11% of the electrical capacity is utilized by the proposed water vapor DIAL system on the Altair UAV.

Configuration and Specifications of AN Unmanned Aerial Vehicle for Precision Agriculture

NASA Astrophysics Data System (ADS)

Erena, M.; Montesinos, S.; Portillo, D.; Alvarez, J.; Marin, C.; Fernandez, L.; Henarejos, J. M.; Ruiz, L. A.

2016-06-01

Unmanned Aerial Vehicles (UAVs) with multispectral sensors are increasingly attractive in geosciences for data capture and map updating at high spatial and temporal resolutions. These autonomously-flying systems can be equipped with different sensors, such as a six-band multispectral camera (Tetracam mini-MCA-6), GPS Ublox M8N, and MEMS gyroscopes, and miniaturized sensor systems for navigation, positioning, and mapping purposes. These systems can be used for data collection in precision viticulture. In this study, the efficiency of a light UAV system for data collection, processing, and map updating in small areas is evaluated, generating correlations between classification maps derived from remote sensing and production maps. Based on the comparison of the indices derived from UAVs incorporating infrared sensors with those obtained by satellites (Sentinel 2A and Landsat 8), UAVs show promise for the characterization of vineyard plots with high spatial variability, despite the low vegetative coverage of these crops. Consequently, a procedure for zoning map production based on UAV/UV images could provide important information for farmers.

Earthbound Unmanned Autonomous Vehicles (UAVS) As Planetary Science Testbeds

NASA Astrophysics Data System (ADS)

Pieri, D. C.; Bland, G.; Diaz, J. A.; Fladeland, M. M.

2014-12-01

Recent advances in the technology of unmanned vehicles have greatly expanded the range of contemplated terrestrial operational environments for their use, including aerial, surface, and submarine. The advances have been most pronounced in the areas of autonomy, miniaturization, durability, standardization, and ease of operation, most notably (especially in the popular press) for airborne vehicles. Of course, for a wide range of planetary venues, autonomy at high cost of both money and risk, has always been a requirement. Most recently, missions to Mars have also featured an unprecedented degree of mobility. Combining the traditional planetary surface deployment operational and science imperatives with emerging, very accessible, and relatively economical small UAV platforms on Earth can provide flexible, rugged, self-directed, test-bed platforms for landed instruments and strategies that will ultimately be directed elsewhere, and, in the process, provide valuable earth science data. While the most direct transfer of technology from terrestrial to planetary venues is perhaps for bodies with atmospheres (and oceans), with appropriate technology and strategy accommodations, single and networked UAVs can be designed to operate on even airless bodies, under a variety of gravities. In this presentation, we present and use results and lessons learned from our recent earth-bound UAV volcano deployments, as well as our future plans for such, to conceptualize a range of planetary and small-body missions. We gratefully acknowledge the assistance of students and colleagues at our home institutions, and the government of Costa Rica, without which our UAV deployments would not have been possible. This work was carried out, in part, at the Jet Propulsion Laboratory of the California Institute of Technology under contract to NASA.

Optimal Path Planning and Control of Quadrotor Unmanned Aerial Vehicle for Area Coverage

NASA Astrophysics Data System (ADS)

Fan, Jiankun

An Unmanned Aerial Vehicle (UAV) is an aircraft without a human pilot on board. Its flight is controlled either autonomously by computers onboard the vehicle, or remotely by a pilot on the ground, or by another vehicle. In recent years, UAVs have been used more commonly than prior years. The example includes areo-camera where a high speed camera was attached to a UAV which can be used as an airborne camera to obtain aerial video. It also could be used for detecting events on ground for tasks such as surveillance and monitoring which is a common task during wars. Similarly UAVs can be used for relaying communication signal during scenarios when regular communication infrastructure is destroyed. The objective of this thesis is motivated from such civilian operations such as search and rescue or wildfire detection and monitoring. One scenario is that of search and rescue where UAV's objective is to geo-locate a person in a given area. The task is carried out with the help of a camera whose live feed is provided to search and rescue personnel. For this objective, the UAV needs to carry out scanning of the entire area in the shortest time. The aim of this thesis to develop algorithms to enable a UAV to scan an area in optimal time, a problem referred to as "Coverage Control" in literature. The thesis focuses on a special kind of UAVs called "quadrotor" that is propelled with the help of four rotors. The overall objective of this thesis is achieved via solving two problems. The first problem is to develop a dynamic control model of quadrtor. In this thesis, a proportional-integral-derivative controller (PID) based feedback control system is developed and implemented on MATLAB's Simulink. The PID controller helps track any given trajectory. The second problem is to design a trajectory that will fulfill the mission. The planed trajectory should make sure the quadrotor will scan the whole area without missing any part to make sure that the quadrotor will find the lost

On parallel hybrid-electric propulsion system for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Hung, J. Y.; Gonzalez, L. F.

2012-05-01

This paper presents a review of existing and current developments and the analysis of Hybrid-Electric Propulsion Systems (HEPS) for small fixed-wing Unmanned Aerial Vehicles (UAVs). Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. One technology with potential in this area is with the use of HEPS. In this paper, information on the state-of-art technology in this field of research is provided. A description and simulation of a parallel HEPS for a small fixed-wing UAV by incorporating an Ideal Operating Line (IOL) control strategy is described. Simulation models of the components in a HEPS were designed in the MATLAB Simulink environment. An IOL analysis of an UAV piston engine was used to determine the most efficient points of operation for this engine. The results show that an UAV equipped with this HEPS configuration is capable of achieving a fuel saving of 6.5%, compared to the engine-only configuration.

Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) from an Unmanned Aerial Vehicle (UAV): Results from the 2014 AROMAT campaign

NASA Astrophysics Data System (ADS)

Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Fayt, Caroline; Maes, Jeroen; Mingireanu, Florin; Mocanu, Ionut; Georgescu, Lucian; Van Roozendael, Michel

2015-04-01

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is an instrument dedicated to atmospheric trace gas retrieval from an Unmanned Aerial Vehicle (UAV). The payload is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27x12x12 cm3, and 6 W. The custom-built 2.5 m flying wing UAV is electrically powered, has a typical airspeed of 100 km/h, and can operate at a maximum altitude of 3 km. Both the payload and the UAV were developed in the framework of a collaboration between the Belgian Institute for Space Aeronomy (BIRA-IASB) and the Dunarea de Jos University of Galati, Romania. We present here SWING-UAV test flights dedicated to NO2 measurements and performed in Romania on 10 and 11 September 2014, during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign. The UAV performed 5 flights in the vicinity of the large thermal power station of Turceni (44.67° N, 23.4° E). The UAV was operated in visual range during the campaign, up to 900 m AGL , downwind of the plant and crossing its exhaust plume. The spectra recorded on flight are analyzed with the Differential Optical Absorption Spectroscopy (DOAS) method. The retrieved NO2 Differential Slant Column Densities (DSCDs) are up to 1.5e17 molec/cm2 and reveal the horizontal gradients around the plant. The DSCDs are converted to vertical columns and compared with coincident car-based DOAS measurements. We also present the near-future perspective of the SWING-UAV observation system, which includes flights in 2015 above the Black Sea to quantify ship emissions, the addition of SO2 as a target species, and autopilot flights at higher altitudes to cover a typical satellite pixel extent (10x10 km2).

Development and evaluation of unmanned aerial vehicle (UAV) magnetometry systems

NASA Astrophysics Data System (ADS)

Parvar, Kiyavash

In this thesis, the procedure of conducting magnetic surveys from a UAV platform is investigated. In the process of evaluating UAVs for such surveys, magnetic sensors capable of operating on a UAV platform were tested using a terrestrial survey, as well as on a UAV-platform. Results were then compared to a model of the area generated using a proton precession magnetometer. Magnetic signature of the UAVs are discussed and impact values are calculated. For a better understanding of the magnetic fields around UAVs some micro-surveys were conducted with the help of a fluxgate magnetometer around two UAVs. Results of such surveys were used to determine a location to mount the magnetometer during the survey. A test survey over a known anomaly (a visible chromite outcrop in Oman) is conducted in order to determine the feasibility of using UAV-based magnetometry for chromite exploration. Observations were taken at two different elevations in order to generate a 3-D model of the magnetic field. Later, after applying upward continuation filters and comparing the calculated results to the real values, the reliability and uncertainty levels of such filters were investigated. Results show that magnetometery on UAV platforms is feasible. Unwanted signals can be noticeable and produce fake anomalies by the end of each line because of the swinging effect of the suspended magnetometer below the UAV. This should be reduced by hardware and software modifications i.e. applying non-linear filters and mounting the sensor on a rigid rod. Also, it was derived that the error level associated with upward continuation filters exceeds 45% and thus, using such filters instead of actual observations is not suggested in gradiometry. Moreover, 3-D magnetic gradient surveys can be beneficial for future inversion problems.

UAV Trajectory Modeling Using Neural Networks

NASA Technical Reports Server (NTRS)

Xue, Min

2017-01-01

Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural

An arm wearable haptic interface for impact sensing on unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Choi, Yunshil; Hong, Seung-Chan; Lee, Jung-Ryul

2017-04-01

In this paper, an impact monitoring system using fiber Bragg grating (FBG) sensors and vibro-haptic actuators has been introduced. The system is suggested for structural health monitoring (SHM) for unmanned aerial vehicles (UAVs), by making a decision with human-robot interaction. The system is composed with two major subsystems; an on-board system equipped on UAV and an arm-wearable interface for ground pilot. The on-board system acquires impact-induced wavelength changes and performs localization process, which was developed based on arrival time calculation. The arm-wearable interface helps ground pilots to make decision about impact location themselves by stimulating their tactile-sense with motor vibration.

Uav Photgrammetric Workflows: a best Practice Guideline

NASA Astrophysics Data System (ADS)

Federman, A.; Santana Quintero, M.; Kretz, S.; Gregg, J.; Lengies, M.; Ouimet, C.; Laliberte, J.

2017-08-01

The increasing commercialization of unmanned aerial vehicles (UAVs) has opened the possibility of performing low-cost aerial image acquisition for the documentation of cultural heritage sites through UAV photogrammetry. The flying of UAVs in Canada is regulated through Transport Canada and requires a Special Flight Operations Certificate (SFOC) in order to fly. Various image acquisition techniques have been explored in this review, as well as well software used to register the data. A general workflow procedure has been formulated based off of the literature reviewed. A case study example of using UAV photogrammetry at Prince of Wales Fort is discussed, specifically in relation to the data acquisition and processing. Some gaps in the literature reviewed highlight the need for streamlining the SFOC application process, and incorporating UAVs into cultural heritage documentation courses.

Long-term monitoring of a large landslide by using an Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

Lindner, Gerald; Schraml, Klaus; Mansberger, Reinfried; Hübl, Johannes

2015-04-01

Currently UAVs become more and more important in various scientific areas, including forestry, precision farming, archaeology and hydrology. Using these drones in natural hazards research enables a completely new level of data acquisition being flexible of site, invariant in time, cost-efficient and enabling arbitrary spatial resolution. In this study, a rotary-wing Mini-UAV carrying a DSLR camera was used to acquire time series of overlapping aerial images. These photographs were taken as input to extract Digital Surface Models (DSM) as well as orthophotos in the area of interest. The "Pechgraben" area in Upper Austria has a catchment area of approximately 2 km². Geology is mainly dominated by limestone and sandstone. Caused by heavy rainfalls in the late spring of 2013, an area of about 70 ha began to move towards the village in the valley. In addition to the urgent measures, the slow-moving landslide was monitored approximately every month over a time period of more than 18 months. A detailed documentation of the change process was the result. Moving velocities and height differences were quantified and validated using a dense network of Ground Control Points (GCP). For further analysis, 14 image flights with a total amount of 10.000 photographs were performed to create multi-temporal geodata in in sub-decimeter-resolution for two depicted areas of the landslide. Using a UAV for this application proved to be an excellent choice, as it allows short repetition times, low flying heights and high spatial resolution. Furthermore, the UAV acts almost weather independently as well as highly autonomously. High-quality results can be expected within a few hours after the photo flight. The UAV system performs very well in an alpine environment. Time series of the assessed geodata detect changes in topography and provide a long-term documentation of the measures taken in order to stop the landslide and to prevent infrastructure from damage.

Using unmanned aerial vehicle-borne magnetic sensors to detect and locate improvised explosive devices and unexploded ordnance

NASA Astrophysics Data System (ADS)

Trammell, Hoke S., III; Perry, Alexander R.; Kumar, Sankaran; Czipott, Peter V.; Whitecotton, Brian R.; McManus, Tobin J.; Walsh, David O.

2005-05-01

Magnetic sensors configured as a tensor magnetic gradiometer not only detect magnetic targets, but also determine their location and their magnetic moment. Magnetic moment information can be used to characterize and classify objects. Unexploded ordnance (UXO) and thus many types of improvised explosive device (IED) contain steel, and thus can be detected magnetically. Suitable unmanned aerial vehicle (UAV) platforms, both gliders and powered craft, can enable coverage of a search area much more rapidly than surveys using, for instance, total-field magnetometers. We present data from gradiometer passes over different shells using a gradiometer mounted on a moving cart. We also provide detection range and speed estimates for aerial detection by a UAV.

Actions, Observations, and Decision-Making: Biologically Inspired Strategies for Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Pisanich, Greg; Ippolito, Corey; Plice, Laura; Young, Larry A.; Lau, Benton

2003-01-01

This paper details the development and demonstration of an autonomous aerial vehicle embodying search and find mission planning and execution srrategies inspired by foraging behaviors found in biology. It begins by describing key characteristics required by an aeria! explorer to support science and planetary exploration goals, and illustrates these through a hypothetical mission profile. It next outlines a conceptual bio- inspired search and find autonomy architecture that implements observations, decisions, and actions through an "ecology" of producer, consumer, and decomposer agents. Moving from concepts to development activities, it then presents the results of mission representative UAV aerial surveys at a Mars analog site. It next describes hardware and software enhancements made to a commercial small fixed-wing UAV system, which inc!nde a ncw dpvelopnent architecture that also provides hardware in the loop simulation capability. After presenting the results of simulated and actual flights of bioinspired flight algorithms, it concludes with a discussion of future development to include an expansion of system capabilities and field science support.

Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors.

PubMed

Ramon Soria, Pablo; Bevec, Robert; Arrue, Begoña C; Ude, Aleš; Ollero, Aníbal

2016-05-14

Giving unmanned aerial vehicles (UAVs) the possibility to manipulate objects vastly extends the range of possible applications. This applies to rotary wing UAVs in particular, where their capability of hovering enables a suitable position for in-flight manipulation. Their manipulation skills must be suitable for primarily natural, partially known environments, where UAVs mostly operate. We have developed an on-board object extraction method that calculates information necessary for autonomous grasping of objects, without the need to provide the model of the object's shape. A local map of the work-zone is generated using depth information, where object candidates are extracted by detecting areas different to our floor model. Their image projections are then evaluated using support vector machine (SVM) classification to recognize specific objects or reject bad candidates. Our method builds a sparse cloud representation of each object and calculates the object's centroid and the dominant axis. This information is then passed to a grasping module. Our method works under the assumption that objects are static and not clustered, have visual features and the floor shape of the work-zone area is known. We used low cost cameras for creating depth information that cause noisy point clouds, but our method has proved robust enough to process this data and return accurate results.

A Flight Control System for Small Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Tunik, A. A.; Nadsadnaya, O. I.

2018-03-01

The program adaptation of the controller for the flight control system (FCS) of an unmanned aerial vehicle (UAV) is considered. Linearized flight dynamic models depend mainly on the true airspeed of the UAV, which is measured by the onboard air data system. This enables its use for program adaptation of the FCS over the full range of altitudes and velocities, which define the flight operating range. FCS with program adaptation, based on static feedback (SF), is selected. The SF parameters for every sub-range of the true airspeed are determined using the linear matrix inequality approach in the case of discrete systems for synthesis of a suboptimal robust H ∞-controller. The use of the Lagrange interpolation between true airspeed sub-ranges provides continuous adaptation. The efficiency of the proposed approach is shown against an example of the heading stabilization system.

Aerial monitoring in active mud volcano by UAV technique

NASA Astrophysics Data System (ADS)

Pisciotta, Antonino; Capasso, Giorgio; Madonia, Paolo

2016-04-01

UAV photogrammetry opens various new applications in the close range domain, combining aerial and terrestrial photogrammetry, but also introduces low-cost alternatives to the classical manned aerial photogrammetry. Between 2014 and 2015 tree aerial surveys have been carried out. Using a quadrotor drone, equipped with a compact camera, it was possible to generate high resolution elevation models and orthoimages of The "Salinelle", an active mud volcanoes area, located in territory of Paternò (South Italy). The main risks are related to the damages produced by paroxysmal events. Mud volcanoes show different cyclic phases of activity, including catastrophic events and periods of relative quiescence characterized by moderate activity. Ejected materials often are a mud slurry of fine solids suspended in liquids which may include water and hydrocarbon fluids, the bulk of released gases are carbon dioxide, with some methane and nitrogen, usually pond-shaped of variable dimension (from centimeters to meters in diameter). The scope of the presented work is the performance evaluation of a UAV system that was built to rapidly and autonomously acquire mobile three-dimensional (3D) mapping data in a volcanic monitoring scenario.

Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

PubMed Central

Yoon, Hyungchul; Hoskere, Vedhus; Park, Jong-Woong; Spencer, Billie F.

2017-01-01

Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc.) are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs) to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1) estimation of an appropriate scale factor; and (2) compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach. PMID:28891985

Unmanned aerial vehicle-based structure from motion biomass inventory estimates

NASA Astrophysics Data System (ADS)

Bedell, Emily; Leslie, Monique; Fankhauser, Katie; Burnett, Jonathan; Wing, Michael G.; Thomas, Evan A.

2017-04-01

Riparian vegetation restoration efforts require cost-effective, accurate, and replicable impact assessments. We present a method to use an unmanned aerial vehicle (UAV) equipped with a GoPro digital camera to collect photogrammetric data of a 0.8-ha riparian restoration. A three-dimensional point cloud was created from the photos using "structure from motion" techniques. The point cloud was analyzed and compared to traditional, ground-based monitoring techniques. Ground-truth data were collected on 6.3% of the study site and averaged across the entire site to report stem heights in stems/ha in three height classes. The project site was divided into four analysis sections, one for derivation of parameters used in the UAV data analysis and the remaining three sections reserved for method validation. Comparing the ground-truth data to the UAV generated data produced an overall error of 21.6% and indicated an R2 value of 0.98. A Bland-Altman analysis indicated a 95% probability that the UAV stems/section result will be within 61 stems/section of the ground-truth data. The ground-truth data are reported with an 80% confidence interval of ±1032 stems/ha thus, the UAV was able to estimate stems well within this confidence interval.

Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses

PubMed Central

Corniglia, Matteo; Gaetani, Monica; Grossi, Nicola; Magni, Simone; Migliazzi, Mauro; Angelini, Luciana; Mazzoncini, Marco; Silvestri, Nicola; Fontanelli, Marco; Raffaelli, Michele; Peruzzi, Andrea; Volterrani, Marco

2016-01-01

Spectral reflectance data originating from Unmanned Aerial Vehicle (UAV) imagery is a valuable tool to monitor plant nutrition, reduce nitrogen (N) application to real needs, thus producing both economic and environmental benefits. The objectives of the trial were i) to compare the spectral reflectance of 3 turfgrasses acquired via UAV and by a ground-based instrument; ii) to test the sensitivity of the 2 data acquisition sources in detecting induced variation in N levels. N application gradients from 0 to 250 kg ha-1 were created on 3 different turfgrass species: Cynodon dactylon x transvaalensis (Cdxt) ‘Patriot’, Zoysia matrella (Zm) ‘Zeon’ and Paspalum vaginatum (Pv) ‘Salam’. Proximity and remote-sensed reflectance measurements were acquired using a GreenSeeker handheld crop sensor and a UAV with onboard a multispectral sensor, to determine Normalized Difference Vegetation Index (NDVI). Proximity-sensed NDVI is highly correlated with data acquired from UAV with r values ranging from 0.83 (Zm) to 0.97 (Cdxt). Relating NDVI-UAV with clippings N, the highest r is for Cdxt (0.95). The most reactive species to N fertilization is Cdxt with a clippings N% ranging from 1.2% to 4.1%. UAV imagery can adequately assess the N status of turfgrasses and its spatial variability within a species, so for large areas, such as golf courses, sod farms or race courses, UAV acquired data can optimize turf management. For relatively small green areas, a hand-held crop sensor can be a less expensive and more practical option. PMID:27341674

Unmanned aerial vehicle (UAV) application to the structural health assessment of large civil engineering structures

NASA Astrophysics Data System (ADS)

Castiglioni, Carlo A.; Rabuffetti, Angelo S.; Chiarelli, Gian P.; Brambilla, Giovanni; Georgi, Julia

2017-09-01

This paper summarizes the experience gained in the structural assessment of an existing Thermal Power Plant (TPP) located near Pristina, focusing on the cooling tower and the flue gas stack, which are the main structures of the TPP. Scope of the work was the evaluation of the actual conditions of the structures and to identify the eventual repair measures in order to guarantee a safe and reliable operation of the TPP in view of the extension of its operational lifetime for the next 30 years. With this aim, a sequence of different activities was performed, like: a topographic survey to compare the actual geometrical configuration with the design one, an investigation of the material properties, an in depth visual inspection in order to detect any visible existing damage. Due to the very high elevations of the constructions and to the lack of appropriate structures aimed to their inspections and maintenance, this activity could not be performed without using Unmanned Aerial Vehicle (UAV). This resulted the safest, most economical and less time-consuming solution identified to map the surface damage in the reinforced concrete elements of these large structures including zones that could not be inspected because out of reach by other means.

Relative position control design of receiver UAV in flying-boom aerial refueling phase.

PubMed

An, Shuai; Yuan, Suozhong

2018-02-01

This paper proposes the design of the relative position-keeping control of the receiver unmanned aerial vehicle (UAV) with the time-varying mass in the refueling phase utilizing an inner-outer loop structure. Firstly, the model of the receiver in the refueling phase is established. And then tank model is set up to analyze the influence of fuel transfer on the receiver. Subsequently, double power reaching law based sliding mode controller is designed to control receiver translational motion relative to tanker aircraft in the outer loop while active disturbance rejection control technique is applied to the inner loop to stabilize the receiver. In addition, the closed-loop stabilities of the subsystems are established, respectively. Finally, an aerial refueling model under various refueling strategies is utilized. Simulations and comparative analysis demonstrate the effectiveness and robustness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear Landing Control for Quadrotor UAVs

NASA Astrophysics Data System (ADS)

Voos, Holger

Quadrotor UAVs are one of the most preferred type of small unmanned aerial vehicles because of the very simple mechanical construction and propulsion principle. However, the nonlinear dynamic behavior requires a more advanced stabilizing control and guidance of these vehicles. In addition, the small payload reduces the amount of batteries that can be carried and thus also limits the operating range of the UAV. One possible solution for a range extension is the application of a mobile base station for recharging purpose even during operation. However, landing on a moving base station requires autonomous tracking and landing control of the UAV. In this paper, a nonlinear autopilot for quadrotor UAVs is extended with a tracking and landing controller to fulfill the required task.

Fuzzy distributed cooperative tracking for a swarm of unmanned aerial vehicles with heterogeneous goals

NASA Astrophysics Data System (ADS)

Kladis, Georgios P.; Menon, Prathyush P.; Edwards, Christopher

2016-12-01

This article proposes a systematic analysis for a tracking problem which ensures cooperation amongst a swarm of unmanned aerial vehicles (UAVs), modelled as nonlinear systems with linear and angular velocity constraints, in order to achieve different goals. A distributed Takagi-Sugeno (TS) framework design is adopted for the representation of the nonlinear model of the dynamics of the UAVs. The distributed control law which is introduced is composed of both node and network level information. Firstly, feedback gains are synthesised using a parallel distributed compensation (PDC) control law structure, for a collection of isolated UAVs; ignoring communications among the swarm. Then secondly, based on an alternation-like procedure, the resulting feedback gains are used to determine Lyapunov matrices which are utilised at network level to incorporate into the control law, the relative differences in the states of the vehicles, and to induce cooperative behaviour. Eventually stability is guaranteed for the entire swarm. The control synthesis is performed using tools from linear control theory: in particular the design criteria are posed as linear matrix inequalities (LMIs). An example based on a UAV tracking scenario is included to outline the efficacy of the approach.

Mini-Uav LIDAR for Power Line Inspection

NASA Astrophysics Data System (ADS)

Teng, G. E.; Zhou, M.; Li, C. R.; Wu, H. H.; Li, W.; Meng, F. R.; Zhou, C. C.; Ma, L.

2017-09-01

Light detection and ranging (LIDAR) system based on unmanned aerial vehicles (UAVs) recently are in rapid advancement, meanwhile portable and flexible mini-UAV-borne laser scanners have been a hot research field, especially for the complex terrain survey in the mountains and other areas. This study proposes a power line inspection system solution based on mini-UAV-borne LIDAR system-AOEagle, developed by Academy of Opto-Electronics, Chinese Academy of Sciences, which mounted on a Multi-rotor unmanned aerial vehicle for complex terrain survey according to real test. Furthermore, the point cloud data was explored to validate its applicability for power line inspection, in terms of corridor and line laser point clouds; deformation detection of power towers, etc. The feasibility and advantages of AOEagle have been demonstrated by the promising results based on the real-measured data in the field of power line inspection.

Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

PubMed Central

Kok, Kai Yit; Rajendran, Parvathy

2016-01-01

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630

Autonomous unmanned air vehicles (UAV) techniques

NASA Astrophysics Data System (ADS)

Hsu, Ming-Kai; Lee, Ting N.

2007-04-01

The UAVs (Unmanned Air Vehicles) have great potentials in different civilian applications, such as oil pipeline surveillance, precision farming, forest fire fighting (yearly), search and rescue, boarder patrol, etc. The related industries of UAVs can create billions of dollars for each year. However, the road block of adopting UAVs is that it is against FAA (Federal Aviation Administration) and ATC (Air Traffic Control) regulations. In this paper, we have reviewed the latest technologies and researches on UAV navigation and obstacle avoidance. We have purposed a system design of Jittering Mosaic Image Processing (JMIP) with stereo vision and optical flow to fulfill the functionalities of autonomous UAVs.

Use of an unmanned aerial vehicle-mounted video camera to assess feeding behavior of Raramuri Criollo cows

USDA-ARS?s Scientific Manuscript database

We determined the feasibility of using unmanned aerial vehicle (UAV) video monitoring to predict intake of discrete food items of rangeland-raised Raramuri Criollo non-nursing beef cows. Thirty-five cows were released into a 405-m2 rectangular dry lot, either in pairs (pilot tests) or individually (...

Uav Borne Low Altitude Photogrammetry System

NASA Astrophysics Data System (ADS)

Lin, Z.; Su, G.; Xie, F.

2012-07-01

In this paper，the aforementioned three major aspects related to the Unmanned Aerial Vehicles (UAV) system for low altitude aerial photogrammetry, i.e., flying platform, imaging sensor system and data processing software, are discussed. First of all, according to the technical requirements about the least cruising speed, the shortest taxiing distance, the level of the flight control and the performance of turbulence flying, the performance and suitability of the available UAV platforms (e.g., fixed wing UAVs, the unmanned helicopters and the unmanned airships) are compared and analyzed. Secondly, considering the restrictions on the load weight of a platform and the resolution pertaining to a sensor, together with the exposure equation and the theory of optical information, the principles of designing self-calibration and self-stabilizing combined wide-angle digital cameras (e.g., double-combined camera and four-combined camera) are placed more emphasis on. Finally, a software named MAP-AT, considering the specialty of UAV platforms and sensors, is developed and introduced. Apart from the common functions of aerial image processing, MAP-AT puts more effort on automatic extraction, automatic checking and artificial aided adding of the tie points for images with big tilt angles. Based on the recommended process for low altitude photogrammetry with UAVs in this paper, more than ten aerial photogrammetry missions have been accomplished, the accuracies of Aerial Triangulation, Digital orthophotos(DOM)and Digital Line Graphs(DLG) of which meet the standard requirement of 1:2000, 1:1000 and 1:500 mapping.

Construction of an unmanned aerial vehicle remote sensing system for crop monitoring

NASA Astrophysics Data System (ADS)

Jeong, Seungtaek; Ko, Jonghan; Kim, Mijeong; Kim, Jongkwon

2016-04-01

We constructed a lightweight unmanned aerial vehicle (UAV) remote sensing system and determined the ideal method for equipment setup, image acquisition, and image processing. Fields of rice paddy (Oryza sativa cv. Unkwang) grown under three different nitrogen (N) treatments of 0, 50, or 115 kg/ha were monitored at Chonnam National University, Gwangju, Republic of Korea, in 2013. A multispectral camera was used to acquire UAV images from the study site. Atmospheric correction of these images was completed using the empirical line method, and three-point (black, gray, and white) calibration boards were used as pseudo references. Evaluation of our corrected UAV-based remote sensing data revealed that correction efficiency and root mean square errors ranged from 0.77 to 0.95 and 0.01 to 0.05, respectively. The time series maps of simulated normalized difference vegetation index (NDVI) produced using the UAV images reproduced field variations of NDVI reasonably well, both within and between the different N treatments. We concluded that the UAV-based remote sensing technology utilized in this study is potentially an easy and simple way to quantitatively obtain reliable two-dimensional remote sensing information on crop growth.

Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images

PubMed Central

Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

2013-01-01

The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r2=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance. PMID:24146963

Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images.

PubMed

Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

2013-01-01

The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r(2)=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.

Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.

PubMed

Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

2015-08-12

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.

Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping

PubMed Central

Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

2015-01-01

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights. PMID:26274960

Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors

PubMed Central

Ramon Soria, Pablo; Bevec, Robert; Arrue, Begoña C.; Ude, Aleš; Ollero, Aníbal

2016-01-01

Giving unmanned aerial vehicles (UAVs) the possibility to manipulate objects vastly extends the range of possible applications. This applies to rotary wing UAVs in particular, where their capability of hovering enables a suitable position for in-flight manipulation. Their manipulation skills must be suitable for primarily natural, partially known environments, where UAVs mostly operate. We have developed an on-board object extraction method that calculates information necessary for autonomous grasping of objects, without the need to provide the model of the object’s shape. A local map of the work-zone is generated using depth information, where object candidates are extracted by detecting areas different to our floor model. Their image projections are then evaluated using support vector machine (SVM) classification to recognize specific objects or reject bad candidates. Our method builds a sparse cloud representation of each object and calculates the object’s centroid and the dominant axis. This information is then passed to a grasping module. Our method works under the assumption that objects are static and not clustered, have visual features and the floor shape of the work-zone area is known. We used low cost cameras for creating depth information that cause noisy point clouds, but our method has proved robust enough to process this data and return accurate results. PMID:27187413

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles

PubMed Central

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-01-01

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions. PMID:28029145

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles.

PubMed

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-12-25

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions.

The use of unmanned aerial vehicle imagery in intertidal monitoring

NASA Astrophysics Data System (ADS)

Konar, Brenda; Iken, Katrin

2018-01-01

Intertidal monitoring projects are often limited in their practicality because traditional methods such as visual surveys or removal of biota are often limited in the spatial extent for which data can be collected. Here, we used imagery from a small unmanned aerial vehicle (sUAV) to test their potential use in rocky intertidal and intertidal seagrass surveys in the northern Gulf of Alaska. Images captured by the sUAV in the high, mid and low intertidal strata on a rocky beach and within a seagrass bed were compared to data derived concurrently from observer visual surveys and to images taken by observers on the ground. Observer visual data always resulted in the highest taxon richness, but when observer data were aggregated to the lower taxonomic resolution obtained by the sUAV images, overall community composition was mostly similar between the two methods. Ground camera images and sUAV images yielded mostly comparable community composition despite the typically higher taxonomic resolution obtained by the ground camera. We conclude that monitoring goals or research questions that can be answered on a relatively coarse taxonomic level can benefit from an sUAV-based approach because it allows much larger spatial coverage within the time constraints of a low tide interval than is possible by observers on the ground. We demonstrated this large-scale applicability by using sUAV images to develop maps that show the distribution patterns and patchiness of seagrass.

The combined use of Building Information Modelling (BIM) and Unmanned Aerial Vehicle (UAV) technologies for the 3D illustration of the progress of works in infrastructure construction projects

NASA Astrophysics Data System (ADS)

Vacanas, Yiannis; Themistocleous, Kyriacos; Agapiou, Athos; Hadjimitsis, Diofantos

2016-08-01

Building Information Modelling (BIM) technology is already part of the construction industry and is considered by professionals as a very useful tool for all phases of a construction project. BIM technology, with the particularly useful 3D illustrations which it provides, can be used to illustrate and monitor the progress of works effectively through the entire lifetime of the project. Unmanned Aerial Vehicles (UAVs) have undergone significant advances in equipment capabilities and now have the capacity to acquire high resolution imagery from different angles in a cost effective and efficient manner. By using photogrammetry, characteristics such as distances, areas, volumes, elevations, object sizes, and object shape can be determined within overlapping areas. This paper explores the combined use of BIM and UAV technologies in order to achieve efficient and accurate as-built data collection and 3D illustrations of the works progress during an infrastructure construction project.

The impacts of environmental variables on water reflectance measured using a lightweight unmanned aerial vehicle (UAV)-based spectrometer system

NASA Astrophysics Data System (ADS)

Zeng, Chuiqing; Richardson, Murray; King, Douglas J.

2017-08-01

Remote sensing methods to study spatial and temporal changes in water quality using satellite or aerial imagery are limited by the inherently low reflectance signal of water across the visible and near infrared spectrum, as well as environmental variables such as surface scattering effects (sun glint), substrate and aquatic vegetation reflectance, and atmospheric effects. This study exploits the low altitude, high-resolution remote sensing capabilities of unmanned aerial vehicle (UAV) platforms to examine the major environmental variables that affect water reflectance acquisition, without the confounding influence of atmospheric effects typical of higher-altitude platforms. After observation and analysis, we found: (1) multiple water spectra measured at the same location had a standard deviation of 10.4%; (2) water spectra changes associated with increasing altitude from 20 m to 100 m were negligible; (3) the difference between mean reflectance at three off-shore locations in an urban water body reached 29.9%; (4) water bottom visibility increased water reflectance by 20.1% in near shore areas compared to deep water spectra in a clear water lake; (5) emergent plants caused the water spectra to shift towards a shape that is characteristic of vegetation, whereas submerged vegetation showed limited effect on water spectra in the studied lake; (6) cloud and sun glint had major effects and caused water spectra to change abruptly; while glint and shadow effects on spectra may balance each other under certain conditions, the water reflectance can also be unpredictable at times due to wave effects and their effects on lines-of-site to calm water; (7) water spectra collected under a variety of different conditions (e.g. multiple locations, waves) resulted in weaker regression models compared to spectra collected under ideal conditions (e.g. single location, no wave), although the resulting model coefficients were relatively stable. The methods and results from this study

Near Real-Time Georeference of Umanned Aerial Vehicle Images for Post-Earthquake Response

NASA Astrophysics Data System (ADS)

Wang, S.; Wang, X.; Dou, A.; Yuan, X.; Ding, L.; Ding, X.

2018-04-01

The rapid collection of Unmanned Aerial Vehicle (UAV) remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we will spend much more time to select the images and the find images do not have spatial reference. Therefore, a near-real-time rapid georeference method for UAV remote sensing disaster data is proposed in this paper. The UAV images are achieved georeference combined with the position and attitude data collected by UAV flight control system, and the georeferenced data is organized by means of world file which is developed by ESRI. The C # language is adopted to compile the UAV images rapid georeference software, combined with Geospatial Data Abstraction Library (GDAL). The result shows that it can realize rapid georeference of remote sensing disaster images for up to one thousand UAV images within one minute, and meets the demand of rapid disaster response, which is of great value in disaster emergency application.

UAV State Estimation Modeling Techniques in AHRS

NASA Astrophysics Data System (ADS)

Razali, Shikin; Zhahir, Amzari

2017-11-01

Autonomous unmanned aerial vehicle (UAV) system is depending on state estimation feedback to control flight operation. Estimation on the correct state improves navigation accuracy and achieves flight mission safely. One of the sensors configuration used in UAV state is Attitude Heading and Reference System (AHRS) with application of Extended Kalman Filter (EKF) or feedback controller. The results of these two different techniques in estimating UAV states in AHRS configuration are displayed through position and attitude graphs.

Absolute High-Precision Localisation of an Unmanned Ground Vehicle by Using Real-Time Aerial Video Imagery for Geo-referenced Orthophoto Registration

NASA Astrophysics Data System (ADS)

Kuhnert, Lars; Ax, Markus; Langer, Matthias; Nguyen van, Duong; Kuhnert, Klaus-Dieter

This paper describes an absolute localisation method for an unmanned ground vehicle (UGV) if GPS is unavailable for the vehicle. The basic idea is to combine an unmanned aerial vehicle (UAV) to the ground vehicle and use it as an external sensor platform to achieve an absolute localisation of the robotic team. Beside the discussion of the rather naive method directly using the GPS position of the aerial robot to deduce the ground robot's position the main focus of this paper lies on the indirect usage of the telemetry data of the aerial robot combined with live video images of an onboard camera to realise a registration of local video images with apriori registered orthophotos. This yields to a precise driftless absolute localisation of the unmanned ground vehicle. Experiments with our robotic team (AMOR and PSYCHE) successfully verify this approach.

Observing changes at Santiaguito Volcano, Guatemala with an Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

De Angelis, S.; von Aulock, F.; Lavallée, Y.; Hornby, A. J.; Kennedy, B.; Lamb, O. D.; Kendrick, J. E.

2016-12-01

Santiaguito Volcano (Guatemala) is one of the most active volcanoes in Central America, producing several ash venting explosions per day for almost 100 years. Lahars, lava flows and dome and flank collapses that produce major pyroclastic density currents also present a major hazard to nearby farms and communities. Optical observations of both the vent as well as the lava flow fronts can provide scientists and local monitoring staff with important information on the current state of volcanic activity and hazard. Due to the strong activity, and difficult terrain, unmanned aerial vehicles can help to provide valuable data on the activities of the volcano at a safe distance. We collected a series of images and video footage of the active vent of Caliente and the flow front of the active lava flow and its associated lahar channels, both in May 2015 and in December 2015- January 2016. Images of the crater and the lava flows were used for the reconstruction of 3D terrain models using structure-from-motion. These models can be used to constrain topographical changes and distribution of ballistics via cloud comparisons. The preliminary data of aerial images and videos of the summit crater (during two separate ash venting episodes) and the lava flow fronts indicate the following differences in activity during those two field campaigns: - A recorded explosive event in December 2015 initiates at subparallel linear faults near the centre of the dome, with a later, separate, and more ash-laden burst occurring from an off-centre fracture. - A comparison of the point clouds before and after a degassing explosion shows minor subsidence of the dome surface and the formation of several small craters at the main venting locations. - The lava flow fronts did not advance more than a few meters between May and December 2015. - Damming of river valleys by the lava flows has established new stream channels that have modified established pathways for the recurring lahars, one of the major

ARM Unmanned Aerial Systems Implementation Plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmid, Beat; Ivey, Mark

Recent advances in Unmanned Aerial Systems (UAS) coupled with changes in the regulatory environment for operations of UAS in the National Airspace increase the potential value of UAS to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility. UAS include unmanned aerial vehicles (UAV) and tethered balloon systems (TBS). The roles UAVs and TBSs could play within the ARM Facility, particularly science questions they could help address, have been discussed in several workshops, reports, and vision documents, including: This document describes the implementation of a robust and vigorous program for use of UAV and TBS formore » the science missions ARM supports.« less

Preservation potential of subtle glacial landforms based on detailed mapping of recently exposed proglacial areas: application of unmanned aerial vehicle (UAV) and structure-from-motion (SfM)

NASA Astrophysics Data System (ADS)

Ewertowski, Marek; Evans, David; Roberts, David; Tomczyk, Aleksandra; Ewertowski, Wojciech

2016-04-01

Ongoing glacier retreat results in the continuous exposure of proglacial areas. Such areas contain invaluable information about glacial process-form relationships manifest in specific landform assemblages. However, preservation potential of freshly exposed glacial landforms is very low, as proglacial terrains are one of the most dynamic parts of the landscape. Therefore, rapid mapping and geomorphological characterisation of such areas is important from a glaciological and geomorphological point of view for proper understanding and reconstruction of glacier-landform dynamics and chronology of glacial events. Annual patterns of recession and relatively small areas exposed every year, mean that the performing of regular aerial or satellite survey is expensive and therefore impractical. Recent advances in technology enables the development of low-cost alternatives for traditional aerial surveys. Small unmanned aerial vehicles (UAV) can be used to acquire high-resolution (several cm) low-altitude photographs. The UAV-based photographs can be subsequently processed through the structure-from-motion process to generate detailed orthophotomaps and digital elevation models. In this study we present case studies from the forelands of various glaciers on Iceland and Svalbard representing different types of proglacial landscapes: Fláajökull (annual push moraines); Hofellsjökul (bedrock bedforms and push moraines); Fjallsjökull (marginal drainage network); Rieperbreen (crevasse squeeze ridges and longitudinal debris stripes); Ayerbreen (transverse debris ridges); Foxfonna (longitudinal debris stripes);Hørbyebreen (geometric ridge network); Nordenskiöldbreen (fluted till surface); Ebbabreen (controlled moraine complex). UAV campaigns were conducted using a low-cost quadcopter platform. Resultant orthophotos and DEMs enabled mapping and assessment of recent glacial landscape development in different types of glacial landsystems. Results of our study indicate that

Detecting lost persons using the k-mean method applied to aerial photographs taken by unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Stec, Magdalena; Wieczorek, Malgorzata; Slopek, Jacek; Jurecka, Miroslawa

2016-04-01

The objective of this work is to discuss the usefulness of the k-mean method in the process of detecting persons on oblique aerial photographs acquired by unmanned aerial vehicles (UAVs). The detection based on the k-mean procedure belongs to one of the modules of a larger Search and Rescue (SAR) system which is being developed at the University of Wroclaw, Poland (research project no. IP2014 032773 financed by the Ministry of Science and Higher Education of Poland). The module automatically processes individual geotagged visual-light UAV-taken photographs or their orthorectified versions. Firstly, we separate red (R), green (G) and blue (B) channels, express raster data as numeric matrices and acquire coordinates of centres of images using the exchangeable image file format (EXIF). Subsequently, we divide the matrices into matrices of smaller dimensions, the latter being associated with the size of spatial window which is suitable for discriminating between human and terrain. Each triplet of the smaller matrices (R, G and B) serves as input spatial data for the k-mean classification. We found that, in several configurations of the k-mean parameters, it is possible to distinguish a separate class which characterizes a person. We compare the skills of this approach by performing two experiments, based on UAV-taken RGB photographs and their orthorectified versions. This allows us to verify the hypothesis that the two exercises lead to similar classifications. In addition, we discuss the performance of the approach for dissimilar spatial windows, hence various dimensions of the above-mentioned matrices, and we do so in order to find the one which offers the most adequate classification. The numerical experiment is carried out using the data acquired during a dedicated observational UAV campaign carried out in the Izerskie Mountains (SW Poland).

Experimental Study of Multispectral Characteristics of an Unmanned Aerial Vehicle at Different Observation Angles

PubMed Central

Zheng, Haijing; Bai, Tingzhu; Wang, Quanxi; Cao, Fengmei; Shao, Long; Sun, Zhaotian

2018-01-01

This study investigates multispectral characteristics of an unmanned aerial vehicle (UAV) at different observation angles by experiment. The UAV and its engine are tested on the ground in the cruise state. Spectral radiation intensities at different observation angles are obtained in the infrared band of 0.9–15 μm by a spectral radiometer. Meanwhile, infrared images are captured separately by long-wavelength infrared (LWIR), mid-wavelength infrared (MWIR), and short-wavelength infrared (SWIR) cameras. Additionally, orientation maps of the radiation area and radiance are obtained. The results suggest that the spectral radiation intensity of the UAV is determined by its exhaust plume and that the main infrared emission bands occur at 2.7 μm and 4.3 μm. At observation angles in the range of 0°–90°, the radiation area of the UAV in MWIR band is greatest; however, at angles greater than 90°, the radiation area in the SWIR band is greatest. In addition, the radiance of the UAV at an angle of 0° is strongest. These conclusions can guide IR stealth technique development for UAVs. PMID:29389880

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) and its operations from an unmanned aerial vehicle (UAV) during the AROMAT campaign

NASA Astrophysics Data System (ADS)

Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Georgescu, Lucian; Maes, Jeroen; Fayt, Caroline; Mingireanu, Florin; Schuettemeyer, Dirk; Meier, Andreas Carlos; Schönardt, Anja; Ruhtz, Thomas; Bellegante, Livio; Nicolae, Doina; Den Hoed, Mirjam; Allaart, Marc; Van Roozendael, Michel

2018-01-01

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is a compact remote sensing instrument dedicated to mapping trace gases from an unmanned aerial vehicle (UAV). SWING is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27 cm × 12 cm × 8 cm, and 6 W. SWING was developed in parallel with a 2.5 m flying-wing UAV. This unmanned aircraft is electrically powered, has a typical airspeed of 100 km h-1, and can operate at a maximum altitude of 3 km. We present SWING-UAV experiments performed in Romania on 11 September 2014 during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign, which was dedicated to test newly developed instruments in the context of air quality satellite validation. The UAV was operated up to 700 m above ground, in the vicinity of the large power plant of Turceni (44.67° N, 23.41° E; 116 m a. s. l. ). These SWING-UAV flights were coincident with another airborne experiment using the Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP), and with ground-based DOAS, lidar, and balloon-borne in situ observations. The spectra recorded during the SWING-UAV flights are analysed with the DOAS technique. This analysis reveals NO2 differential slant column densities (DSCDs) up to 13±0.6×1016 molec cm-2. These NO2 DSCDs are converted to vertical column densities (VCDs) by estimating air mass factors. The resulting NO2 VCDs are up to 4.7±0.4×1016 molec cm-2. The water vapour DSCD measurements, up to 8±0.15×1022 molec cm-2, are used to estimate a volume mixing ratio of water vapour in the boundary layer of 0.013±0.002 mol mol-1. These geophysical quantities are validated with the coincident measurements.

Dryden's David Bushman explains the capabilities of the Altus UAV to NASA Langley's Charles Hudgins

NASA Image and Video Library

2003-05-27

David Bushman, unmanned aerial vehicle (UAV) mission manager in NASA Dryden's Airborne Science Program, explains the capabilities of the Altus UAV to Charles Hudgins of NASA Langley's Chemistry and Dynamics Branch.

Delayed Monocular SLAM Approach Applied to Unmanned Aerial Vehicles.

PubMed

Munguia, Rodrigo; Urzua, Sarquis; Grau, Antoni

2016-01-01

In recent years, many researchers have addressed the issue of making Unmanned Aerial Vehicles (UAVs) more and more autonomous. In this context, the state estimation of the vehicle position is a fundamental necessity for any application involving autonomy. However, the problem of position estimation could not be solved in some scenarios, even when a GPS signal is available, for instance, an application requiring performing precision manoeuvres in a complex environment. Therefore, some additional sensory information should be integrated into the system in order to improve accuracy and robustness. In this work, a novel vision-based simultaneous localization and mapping (SLAM) method with application to unmanned aerial vehicles is proposed. One of the contributions of this work is to design and develop a novel technique for estimating features depth which is based on a stochastic technique of triangulation. In the proposed method the camera is mounted over a servo-controlled gimbal that counteracts the changes in attitude of the quadcopter. Due to the above assumption, the overall problem is simplified and it is focused on the position estimation of the aerial vehicle. Also, the tracking process of visual features is made easier due to the stabilized video. Another contribution of this work is to demonstrate that the integration of very noisy GPS measurements into the system for an initial short period of time is enough to initialize the metric scale. The performance of this proposed method is validated by means of experiments with real data carried out in unstructured outdoor environments. A comparative study shows that, when compared with related methods, the proposed approach performs better in terms of accuracy and computational time.

A Discussion of Aerodynamic Control Effectors (ACEs) for Unmanned Air Vehicles (UAVs)

NASA Technical Reports Server (NTRS)

Wood, Richard M.

2002-01-01

A Reynolds number based, unmanned air vehicle classification structure has been developed which identifies four classes of unmanned air vehicle concepts. The four unmanned air vehicle (UAV) classes are; Micro UAV, Meso UAV, Macro UAV, and Mega UAV. In a similar fashion a labeling scheme for aerodynamic control effectors (ACE) was developed and eleven types of ACE concepts were identified. These eleven types of ACEs were laid out in a five (5) layer scheme. The final section of the paper correlated the various ACE concepts to the four UAV classes and ACE recommendations are offered for future design activities.

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

PubMed Central

Shi, Yeyin; Thomasson, J. Alex; Murray, Seth C.; Pugh, N. Ace; Rooney, William L.; Shafian, Sanaz; Rajan, Nithya; Rouze, Gregory; Morgan, Cristine L. S.; Neely, Haly L.; Rana, Aman; Bagavathiannan, Muthu V.; Henrickson, James; Bowden, Ezekiel; Valasek, John; Olsenholler, Jeff; Bishop, Michael P.; Sheridan, Ryan; Putman, Eric B.; Popescu, Sorin; Burks, Travis; Cope, Dale; Ibrahim, Amir; McCutchen, Billy F.; Baltensperger, David D.; Avant, Robert V.; Vidrine, Misty; Yang, Chenghai

2016-01-01

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first

Experimental and rendering-based investigation of laser radar cross sections of small unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Laurenzis, Martin; Bacher, Emmanuel; Christnacher, Frank

2017-12-01

Laser imaging systems are prominent candidates for detection and tracking of small unmanned aerial vehicles (UAVs) in current and future security scenarios. Laser reflection characteristics for laser imaging (e.g., laser gated viewing) of small UAVs are investigated to determine their laser radar cross section (LRCS) by analyzing the intensity distribution of laser reflection in high resolution images. For the first time, LRCSs are determined in a combined experimental and computational approaches by high resolution laser gated viewing and three-dimensional rendering. An optimized simple surface model is calculated taking into account diffuse and specular reflectance properties based on the Oren-Nayar and the Cook-Torrance reflectance models, respectively.

UAV Research, Operations, and Flight Test at the NASA Dryden Flight Research Center

NASA Technical Reports Server (NTRS)

Cosentino, Gary B.

2009-01-01

This slide presentation reviews some of the projects that have extended NASA Dryden's capabilities in designing, testing, and using Unmanned Aerial Vehicles (UAV's). Some of the UAV's have been for Science and experimental applications, some have been for flight research and demonstration purposes, and some have been small UAV's for other customers.

Fuel Cells: A Real Option for Unmanned Aerial Vehicles Propulsion

PubMed Central

2014-01-01

The possibility of implementing fuel cell technology in Unmanned Aerial Vehicle (UAV) propulsion systems is considered. Potential advantages of the Proton Exchange Membrane or Polymer Electrolyte Membrane (PEMFC) and Direct Methanol Fuel Cells (DMFC), their fuels (hydrogen and methanol), and their storage systems are revised from technical and environmental standpoints. Some operating commercial applications are described. Main constraints for these kinds of fuel cells are analyzed in order to elucidate the viability of future developments. Since the low power density is the main problem of fuel cells, hybridization with electric batteries, necessary in most cases, is also explored. PMID:24600326

Autonomous soaring and surveillance in wind fields with an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Gao, Chen

Small unmanned aerial vehicles (UAVs) play an active role in developing a low-cost, low-altitude autonomous aerial surveillance platform. The success of the applications needs to address the challenge of limited on-board power plant that limits the endurance performance in surveillance mission. This thesis studies the mechanics of soaring flight, observed in nature where birds utilize various wind patterns to stay airborne without flapping their wings, and investigates its application to small UAVs in their surveillance missions. In a proposed integrated framework of soaring and surveillance, a bird-mimicking soaring maneuver extracts energy from surrounding wind environment that improves surveillance performance in terms of flight endurance, while the surveillance task not only covers the target area, but also detects energy sources within the area to allow for potential soaring flight. The interaction of soaring and surveillance further enables novel energy based, coverage optimal path planning. Two soaring and associated surveillance strategies are explored. In a so-called static soaring surveillance, the UAV identifies spatially-distributed thermal updrafts for soaring, while incremental surveillance is achieved through gliding flight to visit concentric expanding regions. A Gaussian-process-regression-based algorithm is developed to achieve computationally-efficient and smooth updraft estimation. In a so-called dynamic soaring surveillance, the UAV performs one cycle of dynamic soaring to harvest energy from the horizontal wind gradient to complete one surveillance task by visiting from one target to the next one. A Dubins-path-based trajectory planning approach is proposed to maximize wind energy extraction and ensure smooth transition between surveillance tasks. Finally, a nonlinear trajectory tracking controller is designed for a full six-degree-of-freedom nonlinear UAV dynamics model and extensive simulations are carried to demonstrate the effectiveness of

A method for using unmanned aerial vehicles for emergency investigation of single geo-hazards and sample applications of this method

NASA Astrophysics Data System (ADS)

Huang, Haifeng; Long, Jingjing; Yi, Wu; Yi, Qinglin; Zhang, Guodong; Lei, Bangjun

2017-11-01

In recent years, unmanned aerial vehicles (UAVs) have become widely used in emergency investigations of major natural hazards over large areas; however, UAVs are less commonly employed to investigate single geo-hazards. Based on a number of successful investigations in the Three Gorges Reservoir area, China, a complete UAV-based method for performing emergency investigations of single geo-hazards is described. First, a customized UAV system that consists of a multi-rotor UAV subsystem, an aerial photography subsystem, a ground control subsystem and a ground surveillance subsystem is described in detail. The implementation process, which includes four steps, i.e., indoor preparation, site investigation, on-site fast processing and application, and indoor comprehensive processing and application, is then elaborated, and two investigation schemes, automatic and manual, that are used in the site investigation step are put forward. Moreover, some key techniques and methods - e.g., the layout and measurement of ground control points (GCPs), route planning, flight control and image collection, and the Structure from Motion (SfM) photogrammetry processing - are explained. Finally, three applications are given. Experience has shown that using UAVs for emergency investigation of single geo-hazards greatly reduces the time, intensity and risks associated with on-site work and provides valuable, high-accuracy, high-resolution information that supports emergency responses.

3D Modelling of Inaccessible Areas using UAV-based Aerial Photography and Structure from Motion

NASA Astrophysics Data System (ADS)

Obanawa, Hiroyuki; Hayakawa, Yuichi; Gomez, Christopher

2014-05-01

In hardly accessible areas, the collection of 3D point-clouds using TLS (Terrestrial Laser Scanner) can be very challenging, while airborne equivalent would not give a correct account of subvertical features and concave geometries like caves. To solve such problem, the authors have experimented an aerial photography based SfM (Structure from Motion) technique on a 'peninsular-rock' surrounded on three sides by the sea at a Pacific coast in eastern Japan. The research was carried out using UAS (Unmanned Aerial System) combined with a commercial small UAV (Unmanned Aerial Vehicle) carrying a compact camera. The UAV is a DJI PHANTOM: the UAV has four rotors (quadcopter), it has a weight of 1000 g, a payload of 400 g and a maximum flight time of 15 minutes. The camera is a GoPro 'HERO3 Black Edition': resolution 12 million pixels; weight 74 g; and 0.5 sec. interval-shot. The 3D model has been constructed by digital photogrammetry using a commercial SfM software, Agisoft PhotoScan Professional®, which can generate sparse and dense point-clouds, from which polygonal models and orthophotographs can be calculated. Using the 'flight-log' and/or GCPs (Ground Control Points), the software can generate digital surface model. As a result, high-resolution aerial orthophotographs and a 3D model were obtained. The results have shown that it was possible to survey the sea cliff and the wave cut-bench, which are unobservable from land side. In details, we could observe the complexity of the sea cliff that is nearly vertical as a whole while slightly overhanging over the thinner base. The wave cut bench is nearly flat and develops extensively at the base of the cliff. Although there are some evidences of small rockfalls at the upper part of the cliff, there is no evidence of very recent activity, because no fallen rock exists on the wave cut bench. This system has several merits: firstly lower cost than the existing measuring methods such as manned-flight survey and aerial laser

High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

NASA Astrophysics Data System (ADS)

Cruden, A. R.; Vollgger, S.

2016-12-01

The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution < 10 mm per pixel, and cm-scale location accuracy. Orientation data of brittle and ductile structures were semi-automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Measuring laser reflection cross-sections of small unmanned aerial vehicles for laser detection, ranging and tracking

NASA Astrophysics Data System (ADS)

Laurenzis, Martin; Bacher, Emmanuel; Christnacher, Frank

2017-05-01

An increasing number of incidents are reported where small unmanned aerial vehicles (UAV) are involved flying at low altitude. Thus UAVs are becoming more and more a serious threat in civilian and military scenarios leading to serious danger to safety or privacy issues. In this context, the detection and tracking of small UAV flying at low altitude in urban environment or near background structures is a challenge for state of the art detection technologies. In this paper, we focus on detection, tracking and identification by laser sensing technologies that are Laser Gated Viewing and scanning LiDAR. The laser reflection cross-sections (LRCS) has direct impact on the probability to detection and capability for range measurement. Here, we present methods to determine the laser reflection cross-sections by experimental and computational approaches.

Crack identification for rigid pavements using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bahaddin Ersoz, Ahmet; Pekcan, Onur; Teke, Turker

2017-09-01

Pavement condition assessment is an essential piece of modern pavement management systems as rehabilitation strategies are planned based upon its outcomes. For proper evaluation of existing pavements, they must be continuously and effectively monitored using practical means. Conventionally, truck-based pavement monitoring systems have been in-use in assessing the remaining life of in-service pavements. Although such systems produce accurate results, their use can be expensive and data processing can be time consuming, which make them infeasible considering the demand for quick pavement evaluation. To overcome such problems, Unmanned Aerial Vehicles (UAVs) can be used as an alternative as they are relatively cheaper and easier-to-use. In this study, we propose a UAV based pavement crack identification system for monitoring rigid pavements’ existing conditions. The system consists of recently introduced image processing algorithms used together with conventional machine learning techniques, both of which are used to perform detection of cracks on rigid pavements’ surface and their classification. Through image processing, the distinct features of labelled crack bodies are first obtained from the UAV based images and then used for training of a Support Vector Machine (SVM) model. The performance of the developed SVM model was assessed with a field study performed along a rigid pavement exposed to low traffic and serious temperature changes. Available cracks were classified using the UAV based system and obtained results indicate it ensures a good alternative solution for pavement monitoring applications.

Artificial guide stars for adaptive optics using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Basden, A. G.; Brown, Anthony M.; Chadwick, P. M.; Clark, P.; Massey, R.

2018-06-01

Astronomical adaptive optics (AO) systems are used to increase effective telescope resolution. However, they cannot be used to observe the whole sky since one or more natural guide stars of sufficient brightness must be found within the telescope field of view for the AO system to work. Even when laser guide stars are used, natural guide stars are still required to provide a constant position reference. Here, we introduce a technique to overcome this problem by using rotary unmanned aerial vehicles (UAVs) as a platform from which to produce artificial guide stars. We describe the concept that relies on the UAV being able to measure its precise relative position. We investigate the AO performance improvements that can be achieved, which in the cases presented here can improve the Strehl ratio by a factor of at least 2 for a 8 m class telescope. We also discuss improvements to this technique, which is relevant to both astronomical and solar AO systems.

Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study.

PubMed

Eker, Remzi; Aydın, Abdurrahim; Hübl, Johannes

2017-12-19

In the present study, UAV-based monitoring of the Gallenzerkogel landslide (Ybbs, Lower Austria) was carried out by three flight missions. High-resolution digital elevation models (DEMs), orthophotos, and density point clouds were generated from UAV-based aerial photos via structure-from-motion (SfM). According to ground control points (GCPs), an average of 4 cm root mean square error (RMSE) was found for all models. In addition, light detection and ranging (LIDAR) data from 2009, representing the prefailure topography, was utilized as a digital terrain model (DTM) and digital surface model (DSM). First, the DEM of difference (DoD) between the first UAV flight data and the LIDAR-DTM was determined and according to the generated DoD deformation map, an elevation difference of between - 6.6 and 2 m was found. Over the landslide area, a total of 4380.1 m 3 of slope material had been eroded, while 297.4 m 3 of the material had accumulated within the most active part of the slope. In addition, 688.3 m 3 of the total eroded material had belonged to the road destroyed by the landslide. Because of the vegetation surrounding the landslide area, the Multiscale Model-to-Model Cloud Comparison (M3C2) algorithm was then applied to compare the first and second UAV flight data. After eliminating both the distance uncertainty values of higher than 15 cm and the nonsignificant changes, the M3C2 distance obtained was between - 2.5 and 2.5 m. Moreover, the high-resolution orthophoto generated by the third flight allowed visual monitoring of the ongoing control/stabilization work in the area.

Multi-sensor field trials for detection and tracking of multiple small unmanned aerial vehicles flying at low altitude

NASA Astrophysics Data System (ADS)

Laurenzis, Martin; Hengy, Sebastien; Hommes, Alexander; Kloeppel, Frank; Shoykhetbrod, Alex; Geibig, Thomas; Johannes, Winfried; Naz, Pierre; Christnacher, Frank

2017-05-01

Small unmanned aerial vehicles (UAV) flying at low altitude are becoming more and more a serious threat in civilian and military scenarios. In recent past, numerous incidents have been reported where small UAV were flying in security areas leading to serious danger to public safety or privacy. The detection and tracking of small UAV is a widely discussed topic. Especially, small UAV flying at low altitude in urban environment or near background structures and the detection of multiple UAV at the same time is challenging. Field trials were carried out to investigate the detection and tracking of multiple UAV flying at low altitude with state of the art detection technologies. Here, we present results which were achieved using a heterogeneous sensor network consisting of acoustic antennas, small frequency modulated continuous wave (FMCW) RADAR systems and optical sensors. While acoustics, RADAR and LiDAR were applied to monitor a wide azimuthal area (360°) and to simultaneously track multiple UAV, optical sensors were used for sequential identification with a very narrow field of view.

Challenges in Unmanned Aerial Vehicle Photogrammetry for Archaeological Mapping at High Elevations

NASA Astrophysics Data System (ADS)

Adams, J. A.; Wernke, S.

2015-12-01

Unmanned Aerial Vehicles (UAVs), especially multi-rotor vehicles, are becoming ubiquitous and their appeal for generating photogrammetry-based maps has grown. The options are many and costs have plummeted in last five years; however, many challenges persist with their deployment. We mapped the archaeological site Maw­chu Llacta, a settlement in the southern highlands of Peru (Figure 1). Mawchu Llacta is a planned colonial town built over a major Inka-era center in the high-elevation grasslands at ~4,000m asl. The "general resettlement of Indians" was a massive forced resettlement program, for which very little local-level documentation exists. Mawachu Llacta's excellently preserved architecture includes >500 buildings and hundreds of walls spread across ~13h posed significant mapping challenges. Many environmental factors impact UAV deployment. The air pressure at 4,100 m asl is dramatically lower than at sea level. The dry season diurnal temperature differentials can vary from 7°C to 22°C daily. High and hot conditions frequently occur from late morning to early afternoon. Reaching Mawchu Llacta requires hiking 4km with 400m of vertical gain over steep and rocky terrain. There is also no on-site power or secure storage. Thus, the UAV must be packable. FAA regulations govern US UAV deployments, but regulations were less stringent in Peru. However, ITAR exemptions and Peruvian customs requirements were required. The Peruvian government has established an importation and approval process that entails leaving the UAV at customs, while obtaining the necessary government approvals, both of which can be problematic. We have deployed the Aurora Flight Sciences Skate fixed wing ßUAV, an in-house fixed wing UAV based on the Skywalker X-5 flying wing, and a tethered 9 m3 capacity latex meteorological weather balloon. Development of an autonomous blimp/balloon has been ruled-out. A 3DR Solo is being assessed for excavation mapping.

Commercial UAV operations in civil airspace

NASA Astrophysics Data System (ADS)

Newcome, Laurence R.

2000-11-01

The Federal Aviation Administration is often portrayed as the major impediment to unmanned aerial vehicle expansion into civil government and commercial markets. This paper describes one company's record for successfully negotiating the FAA regulations and obtaining authorizations for several types of UAVs to fly commercial reconnaissance missions in civil airspace. The process and criteria for obtaining such authorizations are described. The mishap records of the Pioneer, Predator and Hunter UAVs are examined in regard to their impact on FAA rule making. The paper concludes with a discussion of the true impediments to UAV penetration of commercial markets to date.

Evaluation of unmanned aerial vehicle shape, flight path and camera type for waterfowl surveys: disturbance effects and species recognition.

PubMed

McEvoy, John F; Hall, Graham P; McDonald, Paul G

2016-01-01

The use of unmanned aerial vehicles (UAVs) for ecological research has grown rapidly in recent years, but few studies have assessed the disturbance impacts of these tools on focal subjects, particularly when observing easily disturbed species such as waterfowl. In this study we assessed the level of disturbance that a range of UAV shapes and sizes had on free-living, non-breeding waterfowl surveyed in two sites in eastern Australia between March and May 2015, as well as the capability of airborne digital imaging systems to provide adequate resolution for unambiguous species identification of these taxa. We found little or no obvious disturbance effects on wild, mixed-species flocks of waterfowl when UAVs were flown at least 60m above the water level (fixed wing models) or 40m above individuals (multirotor models). Disturbance in the form of swimming away from the UAV through to leaving the water surface and flying away from the UAV was visible at lower altitudes and when fixed-wing UAVs either approached subjects directly or rapidly changed altitude and/or direction near animals. Using tangential approach flight paths that did not cause disturbance, commercially available onboard optical equipment was able to capture images of sufficient quality to identify waterfowl and even much smaller taxa such as swallows. Our results show that with proper planning of take-off and landing sites, flight paths and careful UAV model selection, UAVs can provide an excellent tool for accurately surveying wild waterfowl populations and provide archival data with fewer logistical issues than traditional methods such as manned aerial surveys.

Evaluation of unmanned aerial vehicle shape, flight path and camera type for waterfowl surveys: disturbance effects and species recognition

PubMed Central

Hall, Graham P.; McDonald, Paul G.

2016-01-01

The use of unmanned aerial vehicles (UAVs) for ecological research has grown rapidly in recent years, but few studies have assessed the disturbance impacts of these tools on focal subjects, particularly when observing easily disturbed species such as waterfowl. In this study we assessed the level of disturbance that a range of UAV shapes and sizes had on free-living, non-breeding waterfowl surveyed in two sites in eastern Australia between March and May 2015, as well as the capability of airborne digital imaging systems to provide adequate resolution for unambiguous species identification of these taxa. We found little or no obvious disturbance effects on wild, mixed-species flocks of waterfowl when UAVs were flown at least 60m above the water level (fixed wing models) or 40m above individuals (multirotor models). Disturbance in the form of swimming away from the UAV through to leaving the water surface and flying away from the UAV was visible at lower altitudes and when fixed-wing UAVs either approached subjects directly or rapidly changed altitude and/or direction near animals. Using tangential approach flight paths that did not cause disturbance, commercially available onboard optical equipment was able to capture images of sufficient quality to identify waterfowl and even much smaller taxa such as swallows. Our results show that with proper planning of take-off and landing sites, flight paths and careful UAV model selection, UAVs can provide an excellent tool for accurately surveying wild waterfowl populations and provide archival data with fewer logistical issues than traditional methods such as manned aerial surveys. PMID:27020132

Performance Evaluation of 3d Modeling Software for Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Yanagi, H.; Chikatsu, H.

2016-06-01

UAV (Unmanned Aerial Vehicle) photogrammetry, which combines UAV and freely available internet-based 3D modeling software, is widely used as a low-cost and user-friendly photogrammetry technique in the fields such as remote sensing and geosciences. In UAV photogrammetry, only the platform used in conventional aerial photogrammetry is changed. Consequently, 3D modeling software contributes significantly to its expansion. However, the algorithms of the 3D modelling software are black box algorithms. As a result, only a few studies have been able to evaluate their accuracy using 3D coordinate check points. With this motive, Smart3DCapture and Pix4Dmapper were downloaded from the Internet and commercial software PhotoScan was also employed; investigations were performed in this paper using check points and images obtained from UAV.

Energy-Efficient Systems Eliminate Icing Danger for UAVs

NASA Technical Reports Server (NTRS)

2010-01-01

Ames Research Center engineer Leonard Haslim invented an anti-icing t echnology called an electroexpulsive separation system, which uses m echanical force to shatter potentially dangerous ice buildup on an ai rcraft surface. Temecula, California-based Ice Management Systems (no w known as IMS-ESS) licensed the technology from Ames and has discov ered a niche market for the lightweight, energy-efficient technology: unmanned aerial vehicles (UAVs). IMS-ESS systems now prevent damagi ng ice accumulation on military UAVs, allowing the vehicles to carry out crucial missions year round.

Orthorectification, mosaicking, and analysis of sub-decimeter resolution UAV imagery for rangeland monitoring

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) offer an attractive platform for acquiring imagery for rangeland monitoring. UAVs can be deployed quickly and repeatedly, and they can obtain sub-decimeter resolution imagery at lower image acquisition costs than with piloted aircraft. Low flying heights result in ima...

Design of a GaAs/Ge Solar Array for Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Scheiman, David A.; Brinker, David J.; Bents, David J.; Colozza, Anthony J.

1995-01-01

Unmanned Aerial Vehicles (UAV) are being proposed for many applications including surveillance, mapping and atmospheric studies. These applications require a lightweight, low speed, medium to long duration airplane. Due to the weight, speed, and altitude constraints imposed on such aircraft, solar array generated electric power is a viable alternative to air-breathing engines. Development of such aircraft is currently being funded under the Environmental Research Aircraft and Sensor Technology (ERAST) program. NASA Lewis Research Center (LeRC) is currently building a Solar Electric Airplane to demonstrate UAV technology. This aircraft utilizes high efficiency Applied Solar Energy Corporation (ASEC) GaAs/Ge space solar cells. The cells have been provided by the Air Force through the ManTech Office. Expected completion of the plane is early 1995, with the airplane currently undergoing flight testing using battery power.

Design of a GaAs/Ge solar array for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Scheiman, David A.; Brinker, David J.; Bents, David J.; Colozza, Anthony J.

1995-03-01

Unmanned Aerial Vehicles (UAV) are being proposed for many applications including surveillance, mapping and atmospheric studies. These applications require a lightweight, low speed, medium to long duration airplane. Due to the weight, speed, and altitude constraints imposed on such aircraft, solar array generated electric power is a viable alternative to air-breathing engines. Development of such aircraft is currently being funded under the Environmental Research Aircraft and Sensor Technology (ERAST) program. NASA Lewis Research Center (LeRC) is currently building a Solar Electric Airplane to demonstrate UAV technology. This aircraft utilizes high efficiency Applied Solar Energy Corporation (ASEC) GaAs/Ge space solar cells. The cells have been provided by the Air Force through the ManTech Office. Expected completion of the plane is early 1995, with the airplane currently undergoing flight testing using battery power.

Three-Dimensional Digital Documentation of Heritage Sites Using Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry

NASA Astrophysics Data System (ADS)

Jo, Y. H.; Kim, J. Y.

2017-08-01

Three-dimensional digital documentation is an important technique for the maintenance and monitoring of cultural heritage sites. This study focuses on the three-dimensional digital documentation of the Magoksa Temple, Republic of Korea, using a combination of terrestrial laser scanning and unmanned aerial vehicle (UAV) photogrammetry. Terrestrial laser scanning mostly acquired the vertical geometry of the buildings. In addition, the digital orthoimage produced by UAV photogrammetry had higher horizontal data acquisition rate than that produced by terrestrial laser scanning. Thus, the scanning and UAV photogrammetry were merged by matching 20 corresponding points and an absolute coordinate system was established using seven ground control points. The final, complete threedimensional shape had perfect horizontal and vertical geometries. This study demonstrates the potential of integrating terrestrial laser scanning and UAV photogrammetry for three-dimensional digital documentation. This new technique is expected to contribute to the three-dimensional digital documentation and spatial analysis of cultural heritage sites.

Quantifying the morphodynamics of river restoration schemes using Unmanned Aerial Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Williams, Richard; Byrne, Patrick; Gilles, Eric; Hart, John; Hoey, Trevor; Maniatis, George; Moir, Hamish; Reid, Helen; Ves, Nikolas

2017-04-01

River restoration schemes are particularly sensitive to morphological adjustment during the first set of high-flow events that they are subjected to. Quantifying elevation change associated with morphological adjustment can contribute to improved adaptive decision making to ensure river restoration scheme objectives are achieved. To date the relatively high cost, technical demands and challenging logistics associated with acquiring repeat, high-resolution topographic surveys has resulted in a significant barrier to monitoring the three-dimensional morphodynamics of river restoration schemes. The availability of low-cost, consumer grade Unmanned Aerial Vehicles that are capable of acquiring imagery for processing using Structure-from-Motion Multi-View Stereo (SfM MVS) photogrammetry has the potential to transform the survey the morphodynamics of river restoration schemes. Application guidance does, however, need to be developed to fully exploit the advances of UAV technology and SfM MVS processing techniques. In particular, there is a need to quantify the effect of the number and spatial distribution of ground targets on vertical error. This is particularly significant because vertical errors propagate when mapping morphological change, and thus determine the evidence that is available for decision making. This presentation presents results from a study that investigated how the number and spatial distribution of targets influenced vertical error, and then used the findings to determine survey protocols for a monitoring campaign that has quantified morphological change across a number of restoration schemes. At the Swindale river restoration scheme, Cumbria, England, 31 targets were distributed across a 700 m long reach and the centre of each target was surveyed using RTK-GPS. Using the targets as General Control Points (GCPs) or checkpoints, they were divided into three different spatial patterns (centre, edge and random) and used for processing images acquired

Yellow River Icicle Hazard Dynamic Monitoring Using UAV Aerial Remote Sensing Technology

NASA Astrophysics Data System (ADS)

Wang, H. B.; Wang, G. H.; Tang, X. M.; Li, C. H.

2014-02-01

Monitoring the response of Yellow River icicle hazard change requires accurate and repeatable topographic surveys. A new method based on unmanned aerial vehicle (UAV) aerial remote sensing technology is proposed for real-time data processing in Yellow River icicle hazard dynamic monitoring. The monitoring area is located in the Yellow River ice intensive care area in southern BaoTou of Inner Mongolia autonomous region. Monitoring time is from the 20th February to 30th March in 2013. Using the proposed video data processing method, automatic extraction covering area of 7.8 km2 of video key frame image 1832 frames took 34.786 seconds. The stitching and correcting time was 122.34 seconds and the accuracy was better than 0.5 m. Through the comparison of precise processing of sequence video stitching image, the method determines the change of the Yellow River ice and locates accurate positioning of ice bar, improving the traditional visual method by more than 100 times. The results provide accurate aid decision information for the Yellow River ice prevention headquarters. Finally, the effect of dam break is repeatedly monitored and ice break five meter accuracy is calculated through accurate monitoring and evaluation analysis.

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

2018-04-01

Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

Health monitoring of unmanned aerial vehicle based on optical fiber sensor array

NASA Astrophysics Data System (ADS)

Luo, Yuxiang; Shen, Jingshi; Shao, Fei; Guo, Chunhui; Yang, Ning; Zhang, Jiande

2017-10-01

The unmanned aerial vehicle (UAV) in flight needs to face the complicated environment, especially to withstand harsh weather conditions, such as the temperature and pressure. Compared with conventional sensors, fiber Bragg grating (FBG) sensor has the advantages of small size, light weight, high reliability, high precision, anti-electromagnetic interference, long lift-span, moistureproof and good resistance to causticity. It's easy to be embedded in composite structural components of UAVs. In the paper, over 1000 FBG sensors distribute regularly on a wide range of UAVs body, combining wavelength division multiplexing (WDM), time division multiplexing (TDM) and multichannel parallel architecture. WDM has the advantage of high spatial resolution. TDM has the advantage of large capacity and wide range. It is worthful to constitute a sensor network by different technologies. For the signal demodulation of FBG sensor array, WDM works by means of wavelength scanning light sources and F-P etalon. TDM adopts the technology of optical time-domain reflectometry. In order to demodulate efficiently, the most proper sensor multiplex number with some reflectivity is given by the curves fitting. Due to the regular array arrangement of FBG sensors on the UAVs, we can acquire the health state of UAVs in the form of 3D visualization. It is helpful to master the information of health status rapidly and give a real-time health evaluation.

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

Object Based Building Extraction and Building Period Estimation from Unmanned Aerial Vehicle Data

NASA Astrophysics Data System (ADS)

Comert, Resul; Kaplan, Onur

2018-04-01

The aim of this study is to examine whether it is possible to estimate the building periods with respect to the building heights in the urban scale seismic performance assessment studies by using the building height retrieved from the unmanned aerial vehicle (UAV) data. For this purpose, a small area, which includes eight residential reinforced concrete buildings, was selected in Eskisehir (Turkey) city center. In this paper, the possibilities of obtaining the building heights that are used in the estimation of building periods from UAV based data, have been investigated. The investigations were carried out in 3 stages; (i) Building boundary extraction with Object Based Image Analysis (OBIA), (ii) height calculation for buildings of interest from nDSM and accuracy assessment with the terrestrial survey. (iii) Estimation of building period using height information. The average difference between the periods estimated according to the heights obtained from field measurements and from the UAV data is 2.86 % and the maximum difference is 13.2 %. Results of this study have shown that the building heights retrieved from the UAV data can be used in the building period estimation in the urban scale vulnerability assessments.

Positional quality assessment of orthophotos obtained from sensors onboard multi-rotor UAV platforms.

PubMed

Mesas-Carrascosa, Francisco Javier; Rumbao, Inmaculada Clavero; Berrocal, Juan Alberto Barrera; Porras, Alfonso García-Ferrer

2014-11-26

In this study we explored the positional quality of orthophotos obtained by an unmanned aerial vehicle (UAV). A multi-rotor UAV was used to obtain images using a vertically mounted digital camera. The flight was processed taking into account the photogrammetry workflow: perform the aerial triangulation, generate a digital surface model, orthorectify individual images and finally obtain a mosaic image or final orthophoto. The UAV orthophotos were assessed with various spatial quality tests used by national mapping agencies (NMAs). Results showed that the orthophotos satisfactorily passed the spatial quality tests and are therefore a useful tool for NMAs in their production flowchart.

An Analysis of Fuel Cell Options for an All-electric Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Kohout, Lisa L.; Schmitz, Paul C.

2007-01-01

A study was conducted to assess the performance characteristics of both PEM and SOFC-based fuel cell systems for an all-electric high altitude, long endurance Unmanned Aerial Vehicle (UAV). Primary and hybrid systems were considered. Fuel options include methane, hydrogen, and jet fuel. Excel-based models were used to calculate component mass as a function of power level and mission duration. Total system mass and stored volume as a function of mission duration for an aircraft operating at 65 kft altitude were determined and compared.

The application of unmanned aerial vehicle remote sensing for monitoring secondary geological disasters after earthquakes

NASA Astrophysics Data System (ADS)

Lei, Tianjie; Zhang, Yazhen; Wang, Xingyong; Fu, Jun'e.; Li, Lin; Pang, Zhiguo; Zhang, Xiaolei; Kan, Guangyuan

2017-07-01

Remote sensing system fitted on Unmanned Aerial Vehicle (UAV) can obtain clear images and high-resolution aerial photographs. It has advantages of strong real-time, flexibility and convenience, free from influence of external environment, low cost, low-flying under clouds and ability to work full-time. When an earthquake happened, it could go deep into the places safely and reliably which human staff can hardly approach, such as secondary geological disasters hit areas. The system can be timely precise in response to secondary geological disasters monitoring by a way of obtaining first-hand information as quickly as possible, producing a unique emergency response capacity to provide a scientific basis for overall decision-making processes. It can greatly enhance the capability of on-site disaster emergency working team in data collection and transmission. The great advantages of UAV remote sensing system played an irreplaceable role in monitoring secondary geological disaster dynamics and influences. Taking the landslides and barrier lakes for example, the paper explored the basic application and process of UAV remote sensing in the disaster emergency relief. UAV high-resolution remote sensing images had been exploited to estimate the situation of disaster-hit areas and monitor secondary geological disasters rapidly, systematically and continuously. Furthermore, a rapid quantitative assessment on the distribution and size of landslides and barrier lakes was carried out. Monitoring results could support relevant government departments and rescue teams, providing detailed and reliable scientific evidence for disaster relief and decision-making.

Comparative Study of Wing Lift Distribution Analysis for High Altitude Long Endurance (HALE) Unmaned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Silitonga, Faber Y.; Agoes Moelyadi, M.

2018-04-01

The development of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicle (UAV) has been emerged for both civil and military purposes. Its ability of operating in high altitude with long endurance is important in supporting maritime applications.Preliminary analysis of HALE UAV lift distribution of the wing presented to give decisive consideration for its early development. Ensuring that the generated lift is enough to compensate its own weight. Therotical approach using Pradtl’s non-linear lifting line theory will be compared with modern numerical approach using Computational Fluid Dynamics (CFD). Results of wing lift distribution calculated from both methods will be compared to study the reliability of it. HALE UAV ITB has high aspect ratio wing and will be analyze at cruise flight condition. The result indicates difference between Non-linear Lifting Line and CFD method.

Design and test of a situation-augmented display for an unmanned aerial vehicle monitoring task.

PubMed

Lu, Jen-Li; Horng, Ruey-Yun; Chao, Chin-Jung

2013-08-01

In this study, a situation-augmented display for unmanned aerial vehicle (UAV) monitoring was designed, and its effects on operator performance and mental workload were examined. The display design was augmented with the knowledge that there is an invariant flight trajectory (formed by the relationship between altitude and velocity) for every flight, from takeoff to landing. 56 participants were randomly assigned to the situation-augmented display or a conventional display condition to work on 4 (number of abnormalities) x 2 (noise level) UAV monitoring tasks three times. Results showed that the effects of situation-augmented display on flight completion time and time to detect abnormalities were robust under various workload conditions, but error rate and perceived mental workload were unaffected by the display type. Results suggest that the UAV monitoring task is extremely difficult, and that display devices providing high-level situation-awareness may improve operator monitoring performance.

Terrain mapping and control of unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Yeonsik

In this thesis, methods for terrain mapping and control of unmanned aerial vehicles (UAVs) are proposed. First, robust obstacle detection and tracking algorithm are introduced to eliminate the clutter noise uncorrelated with the real obstacle. This is an important problem since most types of sensor measurements are vulnerable to noise. In order to eliminate such noise, a Kalman filter-based interacting multiple model (IMM) algorithm is employed to effectively detect obstacles and estimate their positions precisely. Using the outcome of the IMM-based obstacle detection algorithm, a new method of building a probabilistic occupancy grid map is proposed based on Bayes rule in probability theory. Since the proposed map update law uses the outputs of the IMM-based obstacle detection algorithm, simultaneous tracking of moving targets and mapping of stationary obstacles are possible. This can be helpful especially in a noisy outdoor environment where different types of obstacles exist. Another feature of the algorithm is its capability to eliminate clutter noise as well as measurement noise. The proposed algorithm is simulated in Matlab using realistic sensor models. The results show close agreement with the layout of real obstacles. An efficient method called "quadtree" is used to process massive geographical information in a convenient manner. The algorithm is evaluated in a realistic simulation environment called RIPTIDE, which the NASA Ames Research Center developed to access the performance of complicated software for UAVs. Supposing that a UAV is equipped with abovementioned obstacle detection and mapping algorithm, the control problem of a small fixed-wing UAV is studied. A Nonlinear Model Predictive Control (NMPC is designed as a high level controller for the fixed-wing UAV using a kinematic model of the UAV. The kinematic model is employed because of the assumption that there exist low level controls on the UAV. The UAV dynamics are nonlinear with input

Human factors considerations for the integration of unmanned aerial vehicles in the National Airspace System : an analysis of reports submitted to the Aviation Safety Reporting System (ASRS)

DOT National Transportation Integrated Search

2017-06-06

Successful integration of Unmanned Aerial Vehicle (UAV) operations into the National Airspace System requires the identification and mitigation of operational risks. This report reviews human factors issues that have been identified in operational as...

Current development of UAV sense and avoid system

NASA Astrophysics Data System (ADS)

Zhahir, A.; Razali, A.; Mohd Ajir, M. R.

2016-10-01

As unmanned aerial vehicles (UAVs) are now gaining high interests from civil and commercialised market, the automatic sense and avoid (SAA) system is currently one of the essential features in research spotlight of UAV. Several sensor types employed in current SAA research and technology of sensor fusion that offers a great opportunity in improving detection and tracking system are presented here. The purpose of this paper is to provide an overview of SAA system development in general, as well as the current challenges facing UAV researchers and designers.

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Hamledari, Hesam

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.

Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Keeryun

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. The flight test evaluations were extended to the benchmark tests for 3D avoidance

Formation control of VTOL UAV vehicles under switching-directed interaction topologies with disturbance rejection

NASA Astrophysics Data System (ADS)

Kabiri, Meisam; Atrianfar, Hajar; Menhaj, Mohammad B.

2018-01-01

This paper addresses the adaptive formation control of a group of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAV) with switching-directed interaction topologies. In addition, to tackle the adverse effect of disturbances, a couple of smooth bounded estimators are involved in the procedure design. Exploiting an extraction algorithm, we take advantage of the fully actuated rotational dynamics, to control the translational dynamics of each vehicle. We propose a distributed control scheme such that all vehicles track a desired reference velocity signal while keeping a desired prespecified formation. In this framework, the underlying topology of the agents may switch among several directed graphs, each having a spanning tree. The stability of the overall closed-loop system is proved through Lyapunov function. Finally, simulation results are given to better highlight the effectiveness of the proposed control scheme.

The Role of Unmanned Aerial Systems-Sensors in Air Quality Research

EPA Science Inventory

The use of unmanned aerial systems (UASs) and miniaturized sensors for a variety of scientific and security purposes has rapidly increased. UASs include aerostats (tethered balloons) and remotely controlled, unmanned aerial vehicles (UAVs) including lighter-than-air vessels, fix...

Drones at the Beach - Surf Zone Monitoring Using Rotary Wing Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Rynne, P.; Brouwer, R.; de Schipper, M. A.; Graham, F.; Reniers, A.; MacMahan, J. H.

2014-12-01

We investigate the potential of rotary wing Unmanned Aerial Vehicles (UAVs) to monitor the surf zone. In recent years, the arrival of lightweight, high-capacity batteries, low-power electronics and compact high-definition cameras has driven the development of commercially available UAVs for hobbyists. Moreover, the low operation costs have increased their potential for scientific research as these UAVs are extremely flexible surveying platforms. The UAVs can fly for ~12 min with a mean loiter radius of 1 - 3.5 m and a mean loiter error of 0.75 - 4.5 m, depending on the environmental conditions, flying style, battery type and vehicle type. Our experiments using multiple, alternating UAVs show that it is possible to have near continuous imagery data with similar Fields Of View. The images obtained from the UAVs (Fig. 1a), and in combination with surveyed Ground Control Points (GCPs) (Fig. 1b, red squares and white circles), can be geo-rectified (Fig. 1c) to pixel resolution between 0.01 - 1 m and a reprojection error, i.e. the difference between the surveyed GPS location of a GCP and the location of the GCP obtained from the geo-rectified image, of O(1 m). These geo-rectified images provide data on a variety of coastal aspects, such as beach width (Wb(x,t)), surf zone width (Wsf(x,t)), wave breaking location (rectangle B), beach usage (circle C) and location of dune vegegation (rectangle D), amongst others. Additionally, the possibility to have consecutive, high frequency (up to 2 Hz) rectified images makes the UAVs a great data instrument for spatially and temporally variable systems, such as the surf zone. Our first observations with the UAVs reveal the potential to quickly obtain surf zone and beach characteristics in response to storms or for day to day beach information, as well as the scientific pursuits of surf zone kinematics on different spatial and temporal scales, and dispersion and advection estimates of pollutants/dye. A selection of findings from

Uncertainty management for aerial vehicles: Coordination, deconfliction, and disturbance rejection

NASA Astrophysics Data System (ADS)

Panyakeow, Prachya

The presented dissertation aims to develop control algorithms that deal with three types of uncertainties managements. First, we examine the situation when unmanned aerial vehicles (UAVs) fly through uncertain environments that contain both stationary and moving obstacles. Moreover, a guarantee of collision avoidance is necessary when UAVs operate in close proximity of each other. Second, we look at the communication uncertainty among the network of cooperative UAVs and the efforts to establish and maintain the connectivity throughout their entire missions. Third, we explore the scenario when the aircraft flies through wind gust. The introduction of an appropriate control scheme to actively alleviate the gust loads can result into weight reduction and consequently lower the fuel cost. In the first part of this dissertation, we develop a deconfliction algorithm that guarantees collision avoidance between a pair of constant speed unicycle-type UAVs as well as convergence to the desired destination for each UAV in presence of static obstacles. We use a combination of navigation and swirling functions to direct the unicycle vehicles along the planned trajectories while avoiding inter-vehicle collisions. The main feature of our contribution is proposing means of designing a deconfliction algorithm for unicycle vehicles that more closely capture the dynamics of constant speed UAVs as opposed to double integrator models. Specifically, we consider the issue of UAV turn-rate constraints and proceed to explore the selection of key algorithmic parameters in order to minimize undesirable trajectories and overshoots induced by the avoidance algorithm. The avoidance and convergence analysis of the proposed algorithm is then performed for two cooperative UAVs and simulation results are provided to support the viability of the proposed framework for more general mission scenarios. For the uncertainty of the UAV network, we provides two approaches to establish connectivity among a

Vision-Based SLAM System for Unmanned Aerial Vehicles

PubMed Central

Munguía, Rodrigo; Urzua, Sarquis; Bolea, Yolanda; Grau, Antoni

2016-01-01

The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i) an orientation sensor (AHRS); (ii) a position sensor (GPS); and (iii) a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy. PMID:26999131

Neural network control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Harmon, Frederick G.

2005-11-01

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster-monitoring missions. The benefits, due to the hybrid and electric-only modes, include increased time-on-station and greater range as compared to electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. This dissertation contributes to the research fields of small unmanned aerial vehicles, hybrid-electric propulsion system control, and intelligent control. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system is provided. The UAV is intended for intelligence, surveillance, and reconnaissance (ISR) missions. A conceptual design reveals the trade-offs that must be considered to take advantage of the hybrid-electric propulsion system. The resulting hybrid-electric propulsion system is a two-point design that includes an engine primarily sized for cruise speed and an electric motor and battery pack that are primarily sized for a slower endurance speed. The electric motor provides additional power for take-off, climbing, and acceleration and also serves as a generator during charge-sustaining operation or regeneration. The intelligent control of the hybrid-electric propulsion system is based on an instantaneous optimization algorithm that generates a hyper-plane from the nonlinear efficiency maps for the internal combustion engine, electric motor, and lithium-ion battery pack. The hyper-plane incorporates charge-depletion and charge-sustaining strategies. The optimization algorithm is flexible and allows the operator/user to assign relative importance between the use of gasoline, electricity, and recharging depending on the intended mission. A MATLAB/Simulink model was developed to test the control algorithms. The Cerebellar Model Arithmetic Computer (CMAC) associative memory neural network is applied to the control of the UAVs parallel hybrid

Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation.

PubMed

Wen, Tingxi; Zhang, Zhongnan; Wong, Kelvin K L

2016-01-01

Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood's temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

The Role of Unmanned Aerial Systems/Sensors in Air Quality Research

EPA Science Inventory

The use of unmanned aerial systems (UASs) for a variety of scientific and security purposes has rapidly increased. UASs include aerostats (tethered balloons) and remotely controlled, unmanned aerial vehicles (UAVs) including lighter-than-air vessels, fixed wing airplanes, and he...

A Multi-Purpose Simulation Environment for UAV Research

DTIC Science & Technology

2003-05-01

Maximum 200 Words) Unmanned aerial vehicles (UAVs) are playing an important role in today’s military initiatives. UAVs have proven to be invaluable in...battlefield commanders. Integration of new technologies necessitates simulation prior to fielding new systems in order to avoid costly er- rors. The unique...collection ofinformation if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD

Deep convolutional neural network for classifying Fusarium wilt of radish from unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Ha, Jin Gwan; Moon, Hyeonjoon; Kwak, Jin Tae; Hassan, Syed Ibrahim; Dang, Minh; Lee, O. New; Park, Han Yong

2017-10-01

Recently, unmanned aerial vehicles (UAVs) have gained much attention. In particular, there is a growing interest in utilizing UAVs for agricultural applications such as crop monitoring and management. We propose a computerized system that is capable of detecting Fusarium wilt of radish with high accuracy. The system adopts computer vision and machine learning techniques, including deep learning, to process the images captured by UAVs at low altitudes and to identify the infected radish. The whole radish field is first segmented into three distinctive regions (radish, bare ground, and mulching film) via a softmax classifier and K-means clustering. Then, the identified radish regions are further classified into healthy radish and Fusarium wilt of radish using a deep convolutional neural network (CNN). In identifying radish, bare ground, and mulching film from a radish field, we achieved an accuracy of ≥97.4%. In detecting Fusarium wilt of radish, the CNN obtained an accuracy of 93.3%. It also outperformed the standard machine learning algorithm, obtaining 82.9% accuracy. Therefore, UAVs equipped with computational techniques are promising tools for improving the quality and efficiency of agriculture today.

Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Plice, Laura; Pisanich, Greg

2003-01-01

The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

A Technology Analysis to Support Acquisition of UAVs for Gulf Coalition Forces Operations

DTIC Science & Technology

2017-06-01

their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non ...being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and...aerial vehicles to support detection operations. We use Map Aware Non - Uniform Automata, an agent-based simulation software platform, for the

Positional Quality Assessment of Orthophotos Obtained from Sensors Onboard Multi-Rotor UAV Platforms

PubMed Central

Mesas-Carrascosa, Francisco Javier; Rumbao, Inmaculada Clavero; Berrocal, Juan Alberto Barrera; Porras, Alfonso García-Ferrer

2014-01-01

In this study we explored the positional quality of orthophotos obtained by an unmanned aerial vehicle (UAV). A multi-rotor UAV was used to obtain images using a vertically mounted digital camera. The flight was processed taking into account the photogrammetry workflow: perform the aerial triangulation, generate a digital surface model, orthorectify individual images and finally obtain a mosaic image or final orthophoto. The UAV orthophotos were assessed with various spatial quality tests used by national mapping agencies (NMAs). Results showed that the orthophotos satisfactorily passed the spatial quality tests and are therefore a useful tool for NMAs in their production flowchart. PMID:25587877

A workflow for extracting plot-level biophysical indicators from aerially acquired multispectral imagery

USDA-ARS?s Scientific Manuscript database

Advances in technologies associated with unmanned aerial vehicles (UAVs) has allowed for researchers, farmers and agribusinesses to incorporate UAVs coupled with various imaging systems into data collection activities and aid expert systems for making decisions. Multispectral imageries allow for a q...

Embedded, real-time UAV control for improved, image-based 3D scene reconstruction

Treesearch

Jean Liénard; Andre Vogs; Demetrios Gatziolis; Nikolay Strigul

2016-01-01

Unmanned Aerial Vehicles (UAVs) are already broadly employed for 3D modeling of large objects such as trees and monuments via photogrammetry. The usual workflow includes two distinct steps: image acquisition with UAV and computationally demanding postflight image processing. Insufficient feature overlaps across images is a common shortcoming in post-flight image...

Lessons Learned from NASA UAV Science Demonstration Program Missions

NASA Technical Reports Server (NTRS)

Wegener, Steven S.; Schoenung, Susan M.

2003-01-01

During the summer of 2002, two airborne missions were flown as part of a NASA Earth Science Enterprise program to demonstrate the use of uninhabited aerial vehicles (UAVs) to perform earth science. One mission, the Altus Cumulus Electrification Study (ACES), successfully measured lightning storms in the vicinity of Key West, Florida, during storm season using a high-altitude Altus(TM) UAV. In the other, a solar-powered UAV, the Pathfinder Plus, flew a high-resolution imaging mission over coffee fields in Kauai, Hawaii, to help guide the harvest.

Design of a reconfigurable liquid hydrogen fuel tank for use in the Genii unmanned aerial vehicle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adam, Patrick; Leachman, Jacob

2014-01-29

Long endurance flight, on the order of days, is a leading flight performance characteristic for Unmanned Aerial Vehicles (UAVs). Liquid hydrogen (LH2) is well suited to providing multi-day flight times with a specific energy 2.8 times that of conventional kerosene based fuels. However, no such system of LH2 storage, delivery, and use is currently available for commercial UAVs. In this paper, we develop a light weight LH2 dewar for integration and testing in the proton exchange membrane (PEM) fuel cell powered, student designed and constructed, Genii UAV. The fuel tank design is general for scaling to suit various UAV platforms.more » A cylindrical vacuum-jacketed design with removable end caps was chosen to incorporate various fuel level gauging, pressurizing, and slosh mitigation systems. Heat and mechanical loadings were modeled to compare with experimental results. Mass performance of the fuel tank is characterized by the fraction of liquid hydrogen to full tank mass, and the insulation performance was characterized by effective thermal conductivity and boil-off rate.« less

Design of a reconfigurable liquid hydrogen fuel tank for use in the Genii unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Adam, Patrick; Leachman, Jacob

2014-01-01

Long endurance flight, on the order of days, is a leading flight performance characteristic for Unmanned Aerial Vehicles (UAVs). Liquid hydrogen (LH2) is well suited to providing multi-day flight times with a specific energy 2.8 times that of conventional kerosene based fuels. However, no such system of LH2 storage, delivery, and use is currently available for commercial UAVs. In this paper, we develop a light weight LH2 dewar for integration and testing in the proton exchange membrane (PEM) fuel cell powered, student designed and constructed, Genii UAV. The fuel tank design is general for scaling to suit various UAV platforms. A cylindrical vacuum-jacketed design with removable end caps was chosen to incorporate various fuel level gauging, pressurizing, and slosh mitigation systems. Heat and mechanical loadings were modeled to compare with experimental results. Mass performance of the fuel tank is characterized by the fraction of liquid hydrogen to full tank mass, and the insulation performance was characterized by effective thermal conductivity and boil-off rate.

Multimodal UAV detection: study of various intrusion scenarios

NASA Astrophysics Data System (ADS)

Hengy, Sebastien; Laurenzis, Martin; Schertzer, Stéphane; Hommes, Alexander; Kloeppel, Franck; Shoykhetbrod, Alex; Geibig, Thomas; Johannes, Winfried; Rassy, Oussama; Christnacher, Frank

2017-10-01

Small unmanned aerial vehicles (UAVs) are becoming increasingly popular and affordable the last years for professional and private consumer market, with varied capacities and performances. Recent events showed that illicit or hostile uses constitute an emergent, quickly evolutionary threat. Recent developments in UAV technologies tend to bring autonomous, highly agile and capable unmanned aerial vehicles to the market. These UAVs can be used for spying operations as well as for transporting illicit or hazardous material (smuggling, flying improvised explosive devices). The scenario of interest concerns the protection of sensitive zones against the potential threat constituted by small drones. In the recent past, field trials were carried out to investigate the detection and tracking of multiple UAV flying at low altitude. Here, we present results which were achieved using a heterogeneous sensor network consisting of acoustic antennas, small FMCW RADAR systems and optical sensors. While acoustics and RADAR was applied to monitor a wide azimuthal area (360°), optical sensors were used for sequentially identification. The localization results have been compared to the ground truth data to estimate the efficiency of each detection system. Seven-microphone acoustic arrays allow single source localization. The mean azimuth and elevation estimation error has been measured equal to 1.5 and -2.5 degrees respectively. The FMCW radar allows tracking of multiple UAVs by estimating their range, azimuth and motion speed. Both technologies can be linked to the electro-optical system for final identification of the detected object.

Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives.

PubMed

Yang, Guijun; Liu, Jiangang; Zhao, Chunjiang; Li, Zhenhong; Huang, Yanbo; Yu, Haiyang; Xu, Bo; Yang, Xiaodong; Zhu, Dongmei; Zhang, Xiaoyan; Zhang, Ruyang; Feng, Haikuan; Zhao, Xiaoqing; Li, Zhenhai; Li, Heli; Yang, Hao

2017-01-01

Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

PubMed Central

Yang, Guijun; Liu, Jiangang; Zhao, Chunjiang; Li, Zhenhong; Huang, Yanbo; Yu, Haiyang; Xu, Bo; Yang, Xiaodong; Zhu, Dongmei; Zhang, Xiaoyan; Zhang, Ruyang; Feng, Haikuan; Zhao, Xiaoqing; Li, Zhenhai; Li, Heli; Yang, Hao

2017-01-01

Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping. PMID:28713402

Critical infrastructure monitoring using UAV imagery

NASA Astrophysics Data System (ADS)

Maltezos, Evangelos; Skitsas, Michael; Charalambous, Elisavet; Koutras, Nikolaos; Bliziotis, Dimitris; Themistocleous, Kyriacos

2016-08-01

The constant technological evolution in Computer Vision enabled the development of new techniques which in conjunction with the use of Unmanned Aerial Vehicles (UAVs) may extract high quality photogrammetric products for several applications. Dense Image Matching (DIM) is a Computer Vision technique that can generate a dense 3D point cloud of an area or object. The use of UAV systems and DIM techniques is not only a flexible and attractive solution to produce accurate and high qualitative photogrammetric results but also is a major contribution to cost effectiveness. In this context, this study aims to highlight the benefits of the use of the UAVs in critical infrastructure monitoring applying DIM. A Multi-View Stereo (MVS) approach using multiple images (RGB digital aerial and oblique images), to fully cover the area of interest, is implemented. The application area is an Olympic venue in Attica, Greece, at an area of 400 acres. The results of our study indicate that the UAV+DIM approach respond very well to the increasingly greater demands for accurate and cost effective applications when provided with, a 3D point cloud and orthomosaic.

Common Operating Picture: UAV Security Study

NASA Technical Reports Server (NTRS)

2004-01-01

This initial communication security study is a top-level assessment of basic security issues related to the operation of Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). Security considerations will include information relating to the use of International Civil Aviation Organization (ICAO) Aeronautical Telecommunications Network (ATN) protocols and applications identifying their maturity, as well as the use of IPV4 and a version of mobile IPV6. The purpose of this assessment is to provide an initial analysis of the security implications of introducing UAVs into the NAS.

Water level observations from Unmanned Aerial Vehicles (UAVs) for improving probabilistic estimations of interaction between rivers and groundwater

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Butts, Michael; Vammen Jacobsen, Torsten; Bauer-Gottwein, Peter

2016-04-01

Integrated hydrological models are generally calibrated against observations of river discharge and piezometric head in groundwater aquifers. Integrated hydrological models are rarely calibrated against spatially distributed water level observations measured by either in-situ stations or spaceborne platforms. Indeed in-situ observations derived from ground-based stations are generally spaced too far apart to capture spatial patterns in the water surface. On the other hand spaceborne observations have limited spatial resolution. Additionally satellite observations have a temporal resolution which is not ideal for observing the temporal patterns of the hydrological variables during extreme events. UAVs (Unmanned Aerial Vehicles) offer several advantages: i) high spatial resolution; ii) tracking of the water body better than any satellite technology; iii) timing of the sampling merely depending on the operators. In this case study the Mølleåen river (Denmark) and its catchment have been simulated through an integrated hydrological model (MIKE 11-MIKE SHE). This model was initially calibrated against observations of river discharge retrieved by in-situ stations and against piezometric head of the aquifers. Subsequently the hydrological model has been calibrated against dense spatially distributed water level observations, which could potentially be retrieved by UAVs. Error characteristics of synthetic UAV water level observations were taken from a recent proof-of-concept study. Since the technology for ranging water level is under development, UAV synthetic water level observations were extracted from another model of the river with higher spatial resolution (cross sections located every 10 m). This model with high resolution is assumed to be absolute truth for the purpose of this work. The river model with the coarser resolution has been calibrated against the synthetic water level observations through Differential Evolution Adaptive Metropolis (DREAM) algorithm, an

Employing unmanned aerial vehicle to monitor the health condition of wind turbines

NASA Astrophysics Data System (ADS)

Huang, Yishuo; Chiang, Chih-Hung; Hsu, Keng-Tsang; Cheng, Chia-Chi

2018-04-01

Unmanned aerial vehicle (UAV) can gather the spatial information of huge structures, such as wind turbines, that can be difficult to obtain with traditional approaches. In this paper, the UAV used in the experiments is equipped with high resolution camera and thermal infrared camera. The high resolution camera can provide a series of images with resolution up to 10 Megapixels. Those images can be used to form the 3D model using the digital photogrammetry technique. By comparing the 3D scenes of the same wind turbine at different times, possible displacement of the supporting tower of the wind turbine, caused by ground movement or foundation deterioration may be determined. The recorded thermal images are analyzed by applying the image segmentation methods to the surface temperature distribution. A series of sub-regions are separated by the differences of the surface temperature. The high-resolution optical image and the segmented thermal image are fused such that the surface anomalies are more easily identified for wind turbines.

Modeling and Inverse Controller Design for an Unmanned Aerial Vehicle Based on the Self-Organizing Map

NASA Technical Reports Server (NTRS)

Cho, Jeongho; Principe, Jose C.; Erdogmus, Deniz; Motter, Mark A.

2005-01-01

The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

Prospective use of unmanned aerial vehicles for military medical evacuation in future conflicts.

PubMed

Handford, Charles; Reeves, F; Parker, P

2018-03-09

In order to continue to deliver outstanding medical care on the battlefield, the UK Defence Medical Services must continue to adapt, overcome and actively embrace change. One potential area is the rapid proliferation and sophistication of automated and remote systems such as unmanned aerial vehicles (UAVs). UAVs are already used to deliver blood to remote military locations in Afghanistan and defibrillators to those that need them in the USA and Sweden. An area of future opportunity would be to facilitate rapid evacuation of wounded personnel from high intensity, high threat, remote and austere areas directly to specialist care. Such a capability would reduce threat to human life while allowing rapid extraction of casualties from high risk or inaccessible environments straight back to Role 3 care, all of which in these situations is either not possible or carries too much risk using conventional aerial assets. The article aims to highlight a potential future capability, stimulate debate and reflection, all of which is essential for innovation and future organisational development. The potential uses and benefits of UAVs are highlighted including both the challenges and rewards of utilising UAVs for casualty evacuation. Key benefits are reduced risk to human life, cost, ability to insert into areas conventional aircraft cannot and the rapidity of transfer. Challenges are likely to be airspace management, decisions on appropriate level of care to deliver during transit and ultimately user acceptability. The article also highlights that in order to maximise our ability to exploit new technologies, all arms and trades within the military must be involved in collective research and development. Furthermore, sensible corroboration with private companies will further enhance our ability to acquire products that best serve our needs. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use

Development and Integration of a Solar Powered Unmanned Aerial Vehicle and a Wireless Sensor Network to Monitor Greenhouse Gases

PubMed Central

Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

2015-01-01

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology. PMID:25679312

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases.

PubMed

Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

2015-02-11

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

Towards FAA Certification of UAVs

NASA Technical Reports Server (NTRS)

Nelson, Stacy

2003-01-01

As of June 30, 2003, all Unmanned Aerial Vehicles (UAV), no matter how small, must adhere to the same FAA regulations as human-piloted aircraft. These regulations include certification for flying in controlled airspace and certification of flight software based on RTCA DO-178B. This paper provides an overview of the steps necessary to obtain certification, as well as a discussion about the challenges UAV's face when trying to meet these requirements. It is divided into two parts: 1) Certifications for Flying in Controlled Airspace; 2) Certification of Flight Software per RTCA DO-178B.

An autonomous unmanned aerial vehicle sensing system for structural health monitoring of bridges

NASA Astrophysics Data System (ADS)

Reagan, Daniel; Sabato, Alessandro; Niezrecki, Christopher; Yu, Tzuyang; Wilson, Richard

2016-04-01

As civil infrastructure (i.e. bridges, railways, and tunnels) continues to age; the frequency and need to perform inspection more quickly on a broader scale increases. Traditional inspection and monitoring techniques (e.g., visual inspection, mechanical sounding, rebound hammer, cover meter, electrical potential measurements, ultrasound, and ground penetrating radar) may produce inconsistent results, require lane closure, are labor intensive and time-consuming. Therefore, new structural health monitoring systems must be developed that are automated, highly accurate, minimally invasive, and cost effective. Three-dimensional (3D) digital image correlation (DIC) systems have the merits of extracting full-field strain, deformation, and geometry profiles. These profiles can then be stitched together to generate a complete integrity map of the area of interest. Concurrently, unmanned aerial vehicles (UAVs) have emerged as valuable resources for positioning sensing equipment where it is either difficult to measure or poses a risk to human safety. UAVs have the capability to expedite the optical-based measurement process, offer increased accessibility, and reduce interference with local traffic. Within this work, an autonomous unmanned aerial vehicle in conjunction with 3D DIC was developed for monitoring bridges. The capabilities of the proposed system are demonstrated in both laboratory measurements and data collected from bridges currently in service. Potential measurement influences from platform instability, rotor vibration and positioning inaccuracy are also studied in a controlled environment. The results of these experiments show that the combination of autonomous flight with 3D DIC and other non-contact measurement systems provides a valuable and effective civil inspection platform.

Uav Photogrammetry: a Practical Solution for Challenging Mapping Projects

NASA Astrophysics Data System (ADS)

Saadatseresht, M.; Hashempour, A. H.; Hasanlou, M.

2015-12-01

We have observed huge attentions to application of unmanned aerial vehicle (UAV) in aerial mapping since a decade ago. Though, it has several advantages for handling time/cost/quality issues, there are a dozen of challenges in working with UAVs. In this paper, we; as the Robotic Photogrammetry Research Group (RPRG), will firstly review these challenges then show its advantages in three special practical projects. For each project, we will share our experiences through description of the UAV specifications, flight settings and processing steps. At the end, we will illustrate final result of each project and show how this technology could make unbelievable benefits to clients including 3D city realistic model in decimetre level, ultra high quality map production in several centimetre level, and accessing to a high risk and rough relief area for mapping aims.

Low cost infrared and near infrared sensors for UAVs

NASA Astrophysics Data System (ADS)

Aden, S. T.; Bialas, J. P.; Champion, Z.; Levin, E.; McCarty, J. L.

2014-11-01

Thermal remote sensing has a wide range of applications, though the extent of its use is inhibited by cost. Robotic and computer components are now widely available to consumers on a scale that makes thermal data a readily accessible resource. In this project, thermal imagery collected via a lightweight remote sensing Unmanned Aerial Vehicle (UAV) was used to create a surface temperature map for the purpose of providing wildland firefighting crews with a cost-effective and time-saving resource. The UAV system proved to be flexible, allowing for customized sensor packages to be designed that could include visible or infrared cameras, GPS, temperature sensors, and rangefinders, in addition to many data management options. Altogether, such a UAV system could be used to rapidly collect thermal and aerial data, with a geographic accuracy of less than one meter.

Thermal Imaging of Subsurface Coal Fires by means of an Unmanned Aerial Vehicle (UAV) in the Autonomous Province Xinjiang, PRC

NASA Astrophysics Data System (ADS)

Vasterling, Margarete; Schloemer, Stefan; Fischer, Christian; Ehrler, Christoph

2010-05-01

Spontaneous combustion of coal and resulting coal fires lead to very high temperatures in the subsurface. To a large amount the heat is transferred to the surface by convective and conductive transport inducing a more or less pronounced thermal anomaly. During the past decade satellite-based infrared-imaging (ASTER, MODIS) was the method of choice for coal fire detection on a local and regional scale. However, the resolution is by far too low for a detailed analysis of single coal fires which is essential prerequisite for corrective measures (i.e. fire fighting) and calculation of carbon dioxide emission based on a complex correlation between energy release and CO2 generation. Consequently, within the framework of the Sino-German research project "Innovative Technologies for Exploration, Extinction and Monitoring of Coal Fires in Northern China", a new concept was developed and successfully tested. An unmanned aerial vehicle (UAV) was equipped with a lightweight camera for thermografic (resolution 160 by 120 pixel, dynamic range -20 to 250°C) and for visual imaging. The UAV designed as an octocopter is able to hover at GPS controlled waypoints during predefined flight missions. The application of a UAV has several advantages. Compared to point measurements on the ground the thermal imagery quickly provides the spatial distribution of the temperature anomaly with a much better resolution. Areas otherwise not accessible (due to topography, fire induced cracks, etc.) can easily be investigated. The results of areal surveys on two coal fires in Xinjiang are presented. Georeferenced thermal and visual images were mosaicked together and analyzed. UAV-born data do well compared to temperatures measured directly on the ground and cover large areas in detail. However, measuring surface temperature alone is not sufficient. Simultaneous measurements made at the surface and in roughly 15cm depth proved substantial temperature gradients in the upper soil. Thus the temperature

Using unmanned aerial vehicle (UAV) surveys and image analysis in the study of large surface-associated marine species: a case study on reef sharks Carcharhinus melanopterus shoaling behaviour.

PubMed

Rieucau, G; Kiszka, J J; Castillo, J C; Mourier, J; Boswell, K M; Heithaus, M R

2018-06-01

A novel image analysis-based technique applied to unmanned aerial vehicle (UAV) survey data is described to detect and locate individual free-ranging sharks within aggregations. The method allows rapid collection of data and quantification of fine-scale swimming and collective patterns of sharks. We demonstrate the usefulness of this technique in a small-scale case study exploring the shoaling tendencies of blacktip reef sharks Carcharhinus melanopterus in a large lagoon within Moorea, French Polynesia. Using our approach, we found that C. melanopterus displayed increased alignment with shoal companions when distributed over a sandflat where they are regularly fed for ecotourism purposes as compared with when they shoaled in a deeper adjacent channel. Our case study highlights the potential of a relatively low-cost method that combines UAV survey data and image analysis to detect differences in shoaling patterns of free-ranging sharks in shallow habitats. This approach offers an alternative to current techniques commonly used in controlled settings that require time-consuming post-processing effort. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

High Resolution UAV-based Passive Microwave L-band Imaging of Soil Moisture

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Stachura, M.; Elston, J.; McIntyre, E. M.

2013-12-01

Due to long electrical wavelengths and aperture size limitations the scaling of passive microwave remote sensing of soil moisture from spaceborne low-resolution applications to high resolution applications suitable for precision agriculture requires use of low flying aerial vehicles. This presentation summarizes a project to develop a commercial Unmanned Aerial Vehicle (UAV) hosting a precision microwave radiometer for mapping of soil moisture in high-value shallow root-zone crops. The project is based on the use of the Tempest electric-powered UAV and a compact digital L-band (1400-1427 MHz) passive microwave radiometer developed specifically for extremely small and lightweight aerial platforms or man-portable, tractor, or tower-based applications. Notable in this combination are a highly integrated UAV/radiometer antenna design and use of both the upwelling emitted signal from the surface and downwelling cold space signal for precise calibration using a lobe-correlating radiometer architecture. The system achieves a spatial resolution comparable to the altitude of the UAV above the ground while referencing upwelling measurements to the constant and well-known background temperature of cold space. The radiometer incorporates digital sampling and radio frequency interference mitigation along with infrared, near-infrared, and visible (red) sensors for surface temperature and vegetation biomass correction. This NASA-sponsored project is being developed both for commercial application in cropland water management, L-band satellite validation, and estuarian plume studies.

Long Corridor Survey for High Voltage Power Lines Design Using Uav

NASA Astrophysics Data System (ADS)

Skarlatos, D.; Vamvakousis, V.

2017-11-01

The term Unmanned Aerial Vehicle (UAV) is often directly associated with the armed forces due to their widely-criticized use of such vehicles on the modern battlefield. However, with the advancement of UAV technology, the acquisition and operational cost of small civilian UAV have reduced while their functionalities have increased. Therefore, a wide variety of new civilian applications have emerged. Mapping industry has been benefited as affordable UAV can partially replace traditional platforms, such as helicopters and small aircrafts, for low altitude photography acquisition. Although relatively new to the industry, the use of UAV is rapidly commercialized and they are expected to have a sizeable impact on the mapping industry in the coming years. The aim of this work was to test the use of a low-cost UAV for orthophoto production and Digital Surface Model (DSM) creation, to be used for the design of a new 23km high voltage line of Electricity Authority of Cyprus.

An evaluation of a UAV guidance system with consumer grade GPS receivers

NASA Astrophysics Data System (ADS)

Rosenberg, Abigail Stella

Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies. Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data. Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes. Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The

The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network.

PubMed

Harmon, Frederick G; Frank, Andrew A; Joshi, Sanjay S

2005-01-01

A Simulink model, a propulsion energy optimization algorithm, and a CMAC controller were developed for a small parallel hybrid-electric unmanned aerial vehicle (UAV). The hybrid-electric UAV is intended for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, and reconnaissance (ISR). The Simulink model is a forward-facing simulation program used to test different control strategies. The flexible energy optimization algorithm for the propulsion system allows relative importance to be assigned between the use of gasoline, electricity, and recharging. A cerebellar model arithmetic computer (CMAC) neural network approximates the energy optimization results and is used to control the parallel hybrid-electric propulsion system. The hybrid-electric UAV with the CMAC controller uses 67.3% less energy than a two-stroke gasoline-powered UAV during a 1-h ISR mission and 37.8% less energy during a longer 3-h ISR mission.

UAV low-altitude remote sensing for precision weed management

USDA-ARS?s Scientific Manuscript database

Precision weed management, an application of precision agriculture, accounts for within-field variability of weed infestation and herbicide damage. Unmanned aerial vehicles (UAVs) provide a unique platform for remote sensing of field crops. They are more efficient and flexible than manned agricultur...

Scaling forest phenology from trees to the landscape using an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Klosterman, S.; Melaas, E. K.; Martinez, A.; Richardson, A. D.

2013-12-01

Vegetation phenology monitoring has yielded a decades-long archive documenting the impacts of global change on the biosphere. However, the coarse spatial resolution of remote sensing obscures the organismic level processes driving phenology, while point measurements on the ground limit the extent of observation. Unmanned aerial vehicles (UAVs) enable low altitude remote sensing at higher spatial and temporal resolution than available from space borne platforms, and have the potential to elucidate the links between organism scale processes and landscape scale analyses of terrestrial phenology. This project demonstrates the use of a low cost multirotor UAV, equipped with a consumer grade digital camera, for observation of deciduous forest phenology and comparison to ground- and tower-based data as well as remote sensing. The UAV was flown approximately every five days during the spring green-up period in 2013, to obtain aerial photography over an area encompassing a 250m resolution MODIS (Moderate Resolution Imaging Spectroradiometer) pixel at Harvard Forest in central Massachusetts, USA. The imagery was georeferenced and tree crowns were identified using a detailed species map of the study area. Image processing routines were used to extract canopy 'greenness' time series, which were used to calculate phenology transition dates corresponding to early, middle, and late stages of spring green-up for the dominant canopy trees. Aggregated species level phenology estimates from the UAV data, including the mean and variance of phenology transition dates within species in the study area, were compared to model predictions based on visual assessment of a smaller sample size of individual trees, indicating the extent to which limited ground observations represent the larger landscape. At an intermediate scale, the UAV data was compared to data from repeat digital photography, integrating over larger portions of canopy within and near the study area, as a validation step and

UAV Flight Control Using Distributed Actuation and Sensing

NASA Technical Reports Server (NTRS)

Barnwell, William G.; Heinzen, Stearns N.; Hall, Charles E., Jr.; Chokani, Ndaona; Raney, David L. (Technical Monitor)

2003-01-01

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). This UAV is modified to serve as a flying, controls research, testbed. This effectorhensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Power Management for Fuel Cell and Battery Hybrid Unmanned Aerial Vehicle Applications

NASA Astrophysics Data System (ADS)

Stein, Jared Robert

As electric powered unmanned aerial vehicles enter a new age of commercial viability, market opportunities in the small UAV sector are expanding. Extending UAV flight time through a combination of fuel cell and battery technologies enhance the scope of potential applications. A brief survey of UAV history provides context and examples of modern day UAVs powered by fuel cells are given. Conventional hybrid power system management employs DC-to-DC converters to control the power split between battery and fuel cell. In this study, a transistor replaces the DC-to-DC converter which lowers weight and cost. Simulation models of a lithium ion battery and a proton exchange membrane fuel cell are developed and integrated into a UAV power system model. Flight simulations demonstrate the operation of the transistor-based power management scheme and quantify the amount of hydrogen consumed by a 5.5 kg fixed wing UAV during a six hour flight. Battery power assists the fuel cell during high throttle periods but may also augment fuel cell power during cruise flight. Simulations demonstrate a 60 liter reduction in hydrogen consumption when battery power assists the fuel cell during cruise flight. Over the full duration of the flight, averaged efficiency of the power system exceeds 98%. For scenarios where inflight battery recharge is desirable, a constant current battery charger is integrated into the UAV power system. Simulation of inflight battery recharge is performed. Design of UAV hybrid power systems must consider power system weight against potential flight time. Data from the flight simulations are used to identify a simple formula that predicts flight time as a function of energy stored onboard the modeled UAV. A small selection of commercially available batteries, fuel cells, and compressed air storage tanks are listed to characterize the weight of possible systems. The formula is then used in conjunction with the weight data to generate a graph of power system weight

Determination of the Actual Land Use Pattern Using Unmanned Aerial Vehicles and Multispectral Camera

NASA Astrophysics Data System (ADS)

Dindaroğlu, T.; Gündoğan, R.; Gülci, S.

2017-11-01

The international initiatives developed in the context of combating global warming are based on the monitoring of Land Use, Land Use Changes, and Forests (LULUCEF). Determination of changes in land use patterns is used to determine the effects of greenhouse gas emissions and to reduce adverse effects in subsequent processes. This process, which requires the investigation and control of quite large areas, has undoubtedly increased the importance of technological tools and equipment. The use of carrier platforms and commercially cheaper various sensors have become widespread. In this study, multispectral camera was used to determine the land use pattern with high sensitivity. Unmanned aerial flights were carried out in the research fields of Kahramanmaras Sutcu Imam University campus area. Unmanned aerial vehicle (UAV) (multi-propeller hexacopter) was used as a carrier platform for aerial photographs. Within the scope of this study, multispectral cameras were used to determine the land use pattern with high sensitivity.

Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hervas, Jaime Rubio; Tang, Hui; Reyhanoglu, Mahmut

2014-12-10

This paper presents a motion tracking and control system for automatically landing Unmanned Aerial Vehicles (UAVs) on an oscillating platform using Laser Radar (LADAR) observations. The system itself is assumed to be mounted on a ship deck. A full nonlinear mathematical model is first introduced for the UAV. The ship motion is characterized by a Fourier transform based method which includes a realistic characterization of the sea waves. LADAR observation models are introduced and an algorithm to process those observations for yielding the relative state between the vessel and the UAV is presented, from which the UAV's state relative tomore » an inertial frame can be obtained and used for feedback purposes. A sliding mode control algorithm is derived for tracking a landing trajectory defined by a set of desired waypoints. An extended Kalman filter (EKF) is proposed to account for process and observation noises in the design of a state estimator. The effectiveness of the control algorithm is illustrated through a simulation example.« less

Rapid mapping of landslide disaster using UAV- photogrammetry

NASA Astrophysics Data System (ADS)

Cahyono, A. B.; Zayd, R. A.

2018-03-01

Unmanned Aerial Vehicle (UAV) systems offered many advantages in several mapping applications such as slope mapping, geohazard studies, etc. This study utilizes UAV system for landslide disaster occurred in Jombang Regency, East Java. This study concentrates on type of rotor-wing UAV, that is because rotor wing units are stable and able to capture images easily. Aerial photograph were acquired in the form of strips which followed the procedure of acquiring aerial photograph where taken 60 photos. Secondary data of ground control points using GPS Geodetic and check points established using Total Station technique was used. The digital camera was calibrated using close range photogrammetric software and the recovered camera calibration parameters were then used in the processing of digital images. All the aerial photographs were processed using digital photogrammetric software and the output in the form of orthophoto was produced. The final result shows a 1: 1500 scale orthophoto map from the data processing with SfM algorithm with GSD accuracy of 3.45 cm. And the calculated volume of contour line delineation of 10527.03 m3. The result is significantly different from the result of terrestrial methode equal to 964.67 m3 or 8.4% of the difference of both.

Center Overview and UAV Highlights at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Feng, Deborah; Yan, Jerry Chi Yiu

2017-01-01

The PowerPoint presentation gives an overview of NASA Ames Research Center and its core competencies, as well as some of the highlights of Unmanned Aerial Vehicle (UAV) and Unmanned Aircraft Systems (UAS) accomplishments and innovations by researchers at Ames.

Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery

PubMed Central

Ma, Yalong; Wu, Xinkai; Yu, Guizhen; Xu, Yongzheng; Wang, Yunpeng

2016-01-01

Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM) with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG) and Discrete Cosine Transform (DCT) features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness. PMID:27023564

Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery.

PubMed

Ma, Yalong; Wu, Xinkai; Yu, Guizhen; Xu, Yongzheng; Wang, Yunpeng

2016-03-26

Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM) with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG) and Discrete Cosine Transform (DCT) features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness.

Algorithm for automatic image dodging of unmanned aerial vehicle images using two-dimensional radiometric spatial attributes

NASA Astrophysics Data System (ADS)

Li, Wenzhuo; Sun, Kaimin; Li, Deren; Bai, Ting

2016-07-01

Unmanned aerial vehicle (UAV) remote sensing technology has come into wide use in recent years. The poor stability of the UAV platform, however, produces more inconsistencies in hue and illumination among UAV images than other more stable platforms. Image dodging is a process used to reduce these inconsistencies caused by different imaging conditions. We propose an algorithm for automatic image dodging of UAV images using two-dimensional radiometric spatial attributes. We use object-level image smoothing to smooth foreground objects in images and acquire an overall reference background image by relative radiometric correction. We apply the Contourlet transform to separate high- and low-frequency sections for every single image, and replace the low-frequency section with the low-frequency section extracted from the corresponding region in the overall reference background image. We apply the inverse Contourlet transform to reconstruct the final dodged images. In this process, a single image must be split into reasonable block sizes with overlaps due to large pixel size. Experimental mosaic results show that our proposed method reduces the uneven distribution of hue and illumination. Moreover, it effectively eliminates dark-bright interstrip effects caused by shadows and vignetting in UAV images while maximally protecting image texture information.

Unmanned Aerial Vehicles: Background and Issues for Congress

DTIC Science & Technology

2005-11-21

services are buying million dollar UAVs using operations and maintenance funding that has never been specifically authorized for UAVs and for which...H.R. 2863, H.Rept. 109-119, H.R. 2863, S.Rept. 109-141 CRS-43 135 Peter La Franchi . “Directory: Unmanned Air Vehicles.” Flight International, June...Communications and Electronics FY2006, February 2005, TUAV (B00301), Item No. 62, p. 1 of 16. 162 Peter La Franchi . “Directory: Unmanned Air Vehicles

Use of multi-temporal UAV-derived imagery for estimating individual tree growth in Pinus pinea stands

Treesearch

Juan Guerra-Hernández; Eduardo González-Ferreiro; Vicente Monleon; Sonia Faias; Margarida Tomé; Ramón Díaz-Varela

2017-01-01

High spatial resolution imagery provided by unmanned aerial vehicles (UAVs) can yield accurate and efficient estimation of tree dimensions and canopy structural variables at the local scale. We flew a low-cost, lightweight UAV over an experimental Pinus pinea L. plantation (290 trees distributed over 16 ha with different fertirrigation treatments)...

Research on performance requirements of turbofan engine used on carrier-based UAV

NASA Astrophysics Data System (ADS)

Zhao, Shufan; Li, Benwei; Zhang, Wenlong; Wu, Heng; Feng, Tang

2017-05-01

According to the mission requirements of the carrier-based unmanned aerial vehicle (UAV), a mode level flight was established to calculate the thrust requirements from altitude 9 km to 13 km. Then, the estimation method of flight profile was used to calculate the weight of UAV in each stage to get the specific fuel consumption requirements of the UAV in standby stage. The turbofan engine of carrier-based UAV should meet the thrust and specific fuel consumption requirements. Finally, the GSP software was used to verify the simulation of a small high-bypass turbofan engine. The conclusion is useful for the turbofan engine selection of carrier-based UAV.

Self-Contained Avionics Sensing and Flight Control System for Small Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Ingham, John C. (Inventor); Shams, Qamar A. (Inventor); Logan, Michael J. (Inventor); Fox, Robert L. (Inventor); Fox, legal representative, Melanie L. (Inventor); Kuhn, III, Theodore R. (Inventor); Babel, III, Walter C. (Inventor); Fox, legal representative, Christopher L. (Inventor); Adams, James K. (Inventor); Laughter, Sean A. (Inventor)

2011-01-01

A self-contained avionics sensing and flight control system is provided for an unmanned aerial vehicle (UAV). The system includes sensors for sensing flight control parameters and surveillance parameters, and a Global Positioning System (GPS) receiver. Flight control parameters and location signals are processed to generate flight control signals. A Field Programmable Gate Array (FPGA) is configured to provide a look-up table storing sets of values with each set being associated with a servo mechanism mounted on the UAV and with each value in each set indicating a unique duty cycle for the servo mechanism associated therewith. Each value in each set is further indexed to a bit position indicative of a unique percentage of a maximum duty cycle for the servo mechanism associated therewith. The FPGA is further configured to provide a plurality of pulse width modulation (PWM) generators coupled to the look-up table. Each PWM generator is associated with and adapted to be coupled to one of the servo mechanisms.

Radiometric and geometric analysis of hyperspectral imagery acquired from an unmanned aerial vehicle

DOE PAGES

Hruska, Ryan; Mitchell, Jessica; Anderson, Matthew; ...

2012-09-17

During the summer of 2010, an Unmanned Aerial Vehicle (UAV) hyperspectral in-flight calibration and characterization experiment of the Resonon PIKA II imaging spectrometer was conducted at the U.S. Department of Energy’s Idaho National Laboratory (INL) UAV Research Park. The purpose of the experiment was to validate the radiometric calibration of the spectrometer and determine the georegistration accuracy achievable from the on-board global positioning system (GPS) and inertial navigation sensors (INS) under operational conditions. In order for low-cost hyperspectral systems to compete with larger systems flown on manned aircraft, they must be able to collect data suitable for quantitative scientific analysis.more » The results of the in-flight calibration experiment indicate an absolute average agreement of 96.3%, 93.7% and 85.7% for calibration tarps of 56%, 24%, and 2.5% reflectivity, respectively. The achieved planimetric accuracy was 4.6 meters (based on RMSE).« less

Hurricane Harvey Building Damage Assessment Using UAV Data

NASA Astrophysics Data System (ADS)

Yeom, J.; Jung, J.; Chang, A.; Choi, I.

2017-12-01

Hurricane Harvey which was extremely destructive major hurricane struck southern Texas, U.S.A on August 25, causing catastrophic flooding and storm damages. We visited Rockport suffered severe building destruction and conducted UAV (Unmanned Aerial Vehicle) surveying for building damage assessment. UAV provides very high resolution images compared with traditional remote sensing data. In addition, prompt and cost-effective damage assessment can be performed regardless of several limitations in other remote sensing platforms such as revisit interval of satellite platforms, complicated flight plan in aerial surveying, and cloud amounts. In this study, UAV flight and GPS surveying were conducted two weeks after hurricane damage to generate an orthomosaic image and a DEM (Digital Elevation Model). 3D region growing scheme has been proposed to quantitatively estimate building damages considering building debris' elevation change and spectral difference. The result showed that the proposed method can be used for high definition building damage assessment in a time- and cost-effective way.

Design and control of a vertical takeoff and landing fixed-wing unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Malang, Yasir

With the goal of extending capabilities of multi-rotor unmanned aerial vehicles (UAVs) for wetland conservation missions, a novel hybrid aircraft design consisting of four tilting rotors and a fixed wing is designed and built. The tilting rotors and nonlinear aerodynamic effects introduce a control challenge for autonomous flight, and the research focus is to develop and validate an autonomous transition flight controller. The overall controller structure consists of separate cascaded Proportional Integral Derivative (PID) controllers whose gains are scheduled according to the rotors' tilt angle. A control mechanism effectiveness factor is used to mix the multi-rotor and fixed-wing control actuators during transition. A nonlinear flight dynamics model is created and transition stability is shown through MATLAB simulations, which proves gain-scheduled control is a good fit for tilt-rotor aircraft. Experiments carried out using the prototype UAV validate simulation results for VTOL and tilted-rotor flight.

Application of Crack Identification Techniques for an Aging Concrete Bridge Inspection Using an Unmanned Aerial Vehicle.

PubMed

Kim, In-Ho; Jeon, Haemin; Baek, Seung-Chan; Hong, Won-Hwa; Jung, Hyung-Jo

2018-06-08

Bridge inspection using unmanned aerial vehicles (UAV) with high performance vision sensors has received considerable attention due to its safety and reliability. As bridges become obsolete, the number of bridges that need to be inspected increases, and they require much maintenance cost. Therefore, a bridge inspection method based on UAV with vision sensors is proposed as one of the promising strategies to maintain bridges. In this paper, a crack identification method by using a commercial UAV with a high resolution vision sensor is investigated in an aging concrete bridge. First, a point cloud-based background model is generated in the preliminary flight. Then, cracks on the structural surface are detected with the deep learning algorithm, and their thickness and length are calculated. In the deep learning method, region with convolutional neural networks (R-CNN)-based transfer learning is applied. As a result, a new network for the 384 collected crack images of 256 × 256 pixel resolution is generated from the pre-trained network. A field test is conducted to verify the proposed approach, and the experimental results proved that the UAV-based bridge inspection is effective at identifying and quantifying the cracks on the structures.

Determination of Shift/Bias in Digital Aerial Triangulation of UAV Imagery Sequences

NASA Astrophysics Data System (ADS)

Wierzbicki, Damian

2017-12-01

Currently UAV Photogrammetry is characterized a largely automated and efficient data processing. Depicting from the low altitude more often gains on the meaning in the uses of applications as: cities mapping, corridor mapping, road and pipeline inspections or mapping of large areas e.g. forests. Additionally, high-resolution video image (HD and bigger) is more often use for depicting from the low altitude from one side it lets deliver a lot of details and characteristics of ground surfaces features, and from the other side is presenting new challenges in the data processing. Therefore, determination of elements of external orientation plays a substantial role the detail of Digital Terrain Models and artefact-free ortophoto generation. Parallel a research on the quality of acquired images from UAV and above the quality of products e.g. orthophotos are conducted. Despite so fast development UAV photogrammetry still exists the necessity of accomplishment Automatic Aerial Triangulation (AAT) on the basis of the observations GPS/INS and via ground control points. During low altitude photogrammetric flight, the approximate elements of external orientation registered by UAV are burdened with the influence of some shift/bias errors. In this article, methods of determination shift/bias error are presented. In the process of the digital aerial triangulation two solutions are applied. In the first method shift/bias error was determined together with the drift/bias error, elements of external orientation and coordinates of ground control points. In the second method shift/bias error was determined together with the elements of external orientation, coordinates of ground control points and drift/bias error equals 0. When two methods were compared the difference for shift/bias error is more than ±0.01 m for all terrain coordinates XYZ.

UAV Swarm Attack: Protection System Alternatives for Destroyers

DTIC Science & Technology

2012-12-01

Tactical Rocket-Propelled Grenade Airbag Protection System TRL - Technology Readiness Level UAV - Unmanned Aerial Vehicle USN - United States...com- posed of 62 DDGs is $2.014 billion dollars for the 12 year life cycle. J. REACTIVE ARMOR The Tactical Rocket-Propelled Grenade (RPG) Airbag ...Protection System (TRAPS) system involves ‘close-in’ protection using airbags located around a vehicle to minimize the damage from RPGs. This system was

Augmented Reality Tool for the Situational Awareness Improvement of UAV Operators.

PubMed

Ruano, Susana; Cuevas, Carlos; Gallego, Guillermo; García, Narciso

2017-02-06

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and information coming from other sensors. To avoid the burden of fusing information displayed in the two screens, an Augmented Reality (AR) tool is proposed in this paper. The AR system has two functionalities for Medium-Altitude Long-Endurance (MALE) UAVs: route orientation and target identification. Route orientation allows the operator to identify the upcoming waypoints and the path that the UAV is going to follow. Target identification allows a fast target localization, even in the presence of occlusions. The AR tool is implemented following the North Atlantic Treaty Organization (NATO) standards so that it can be used in different GCSs. The experiments show how the AR tool improves significantly the situational awareness of the UAV operators.

An L-band SAR for repeat pass deformation measurements on a UAV platform

NASA Technical Reports Server (NTRS)

Wheeler, Kevin; Hensley, Scott; Lou, Yunling

2004-01-01

We are proposing to develop a miniaturized polarimetric L-band synthetic aperture radar (SAR) for repeatpass differential interferometric measurements of deformation for rapidly deforming surfaces of geophysical interest such as volcanoes or earthquakes that is to be flown on a unmanned aerial vehicle (UAV or minimally piloted vehicle (MPV).

Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System.

PubMed

Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang

2017-03-03

In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R²) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively.

Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System

PubMed Central

Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang

2017-01-01

In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R2) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively. PMID:28273815

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes

PubMed Central

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-yung

2016-01-01

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency. PMID:27792156

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes.

PubMed

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-Yung

2016-10-25

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

Low-cost, quantitative assessment of highway bridges through the use of unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Ellenberg, Andrew; Kontsos, Antonios; Moon, Franklin; Bartoli, Ivan

2016-04-01

Many envision that in the near future the application of Unmanned Aerial Vehicles (UAVs) will impact the civil engineering industry. Use of UAVs is currently experiencing tremendous growth, primarily in military and homeland security applications. It is only a matter of time until UAVs will be widely accepted as platforms for implementing monitoring/surveillance and inspection in other fields. Most UAVs already have payloads as well as hardware/software capabilities to incorporate a number of non-contact remote sensors, such as high resolution cameras, multi-spectral imaging systems, and laser ranging systems (LIDARs). Of critical importance to realizing the potential of UAVs within the infrastructure realm is to establish how (and the extent to which) such information may be used to inform preservation and renewal decisions. Achieving this will depend both on our ability to quantify information from images (through, for example, optical metrology techniques) and to fuse data from the array of non-contact sensing systems. Through a series of applications to both laboratory-scale and field implementations on operating infrastructure, this paper will present and evaluate (through comparison with conventional approaches) various image processing and data fusion strategies tailored specifically for the assessment of highway bridges. Example scenarios that guided this study include the assessment of delaminations within reinforced concrete bridge decks, the quantification of the deterioration of steel coatings, assessment of the functionality of movement mechanisms, and the estimation of live load responses (inclusive of both strain and displacement).

Automated Snow Extent Mapping Based on Orthophoto Images from Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Spallek, Waldemar; Witek-Kasprzak, Matylda

2018-04-01

The paper presents the application of the k-means clustering in the process of automated snow extent mapping using orthophoto images generated using the Structure-from-Motion (SfM) algorithm from oblique aerial photographs taken by unmanned aerial vehicle (UAV). A simple classification approach has been implemented to discriminate between snow-free and snow-covered terrain. The procedure uses the k-means clustering and classifies orthophoto images based on the three-dimensional space of red-green-blue (RGB) or near-infrared-red-green (NIRRG) or near-infrared-green-blue (NIRGB) bands. To test the method, several field experiments have been carried out, both in situations when snow cover was continuous and when it was patchy. The experiments have been conducted using three fixed-wing UAVs (swinglet CAM by senseFly, eBee by senseFly, and Birdie by FlyTech UAV) on 10/04/2015, 23/03/2016, and 16/03/2017 within three test sites in the Izerskie Mountains in southwestern Poland. The resulting snow extent maps, produced automatically using the classification method, have been validated against real snow extents delineated through a visual analysis and interpretation offered by human analysts. For the simplest classification setup, which assumes two classes in the k-means clustering, the extent of snow patches was estimated accurately, with areal underestimation of 4.6% (RGB) and overestimation of 5.5% (NIRGB). For continuous snow cover with sparse discontinuities at places where trees or bushes protruded from snow, the agreement between automatically produced snow extent maps and observations was better, i.e. 1.5% (underestimation with RGB) and 0.7-0.9% (overestimation, either with RGB or with NIRRG). Shadows on snow were found to be mainly responsible for the misclassification.

Lighter-Than-Air and Pressurized Structures Technology for Unmanned Aerial Vehicles (UAVs)

DTIC Science & Technology

2010-01-01

through lighter-than-air or pressurized structures-based ( PSB ) technologies. Basically, we examined how to construct the UAV in such a way that a...considerable percentage of its weight will be supported by or composed of inflatable structures containing air or helium. In this way, PSB technology...will reduce the amount of energy required to keep the UAV aloft, thus allowing the use of smaller, slower, and quieter motors. Using PSB technology

Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)

NASA Astrophysics Data System (ADS)

Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.

2013-12-01

After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel

Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation

PubMed Central

Wen, Tingxi; Zhang, Zhongnan; Wong, Kelvin K. L.

2016-01-01

Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood’s temperature model during transportation, the UAVs’ scheduling and routes’ planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood’s temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance. PMID:27163361

New distributed radar technology based on UAV or UGV application

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo A.; Contarino, Vincent M.

2013-05-01

Regular micro and nano radars cannot provide reliable tracking of low altitude low profile aerial targets in urban and mountain areas because of reflection and re-reflections from buildings and terrain. They become visible and vulnerable to guided missiles if positioned on a tower or blimp. Doppler radar cannot distinguish moving cars and small low altitude aerial targets in an urban area. A new concept of pocket size distributed radar technology based on the application of UAV (Unmanned Air Vehicles), UGV (Unmanned Ground Vehicles) is proposed for tracking of low altitude low profile aerial targets at short and medium distances for protection of stadium, camp, military facility in urban or mountain areas.

Structurally Integrated Antenna Concepts for HALE UAVs

NASA Technical Reports Server (NTRS)

Cravey, Robin L.; Vedeler, Erik; Goins, Larry; Young, W. Robert; Lawrence, Roland W.

2006-01-01

This technical memorandum describes work done in support of the Multifunctional Structures and Materials Team under the Vehicle Systems Program's ITAS (Integrated Tailored Aero Structures) Project during FY 2005. The Electromagnetics and Sensors Branch (ESB) developed three ultra lightweight antenna concepts compatible with HALE UAVs (High Altitude Long Endurance Unmanned Aerial Vehicles). ESB also developed antenna elements that minimize the interaction between elements and the vehicle to minimize the impact of wing flexure on the EM (electromagnetic) performance of the integrated array. In addition, computer models were developed to perform phase correction for antenna arrays whose elements are moving relative to each other due to wing deformations expected in HALE vehicle concepts. Development of lightweight, conformal or structurally integrated antenna elements and compensating for the impact of a lightweight, flexible structure on a large antenna array are important steps in the realization of HALE UAVs for microwave applications such as passive remote sensing and communications.

Performance Characterization of a Lithium-ion Gel Polymer Battery Power Supply System for an Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Reid, Concha M.; Manzo, Michelle A.; Logan, Michael J.

2004-01-01

Unmanned aerial vehicles (UAVs) are currently under development for NASA missions, earth sciences, aeronautics, the military, and commercial applications. The design of an all electric power and propulsion system for small UAVs was the focus of a detailed study. Currently, many of these small vehicles are powered by primary (nonrechargeable) lithium-based batteries. While this type of battery is capable of satisfying some of the mission needs, a secondary (rechargeable) battery power supply system that can provide the same functionality as the current system at the same or lower system mass and volume is desired. A study of commercially available secondary battery cell technologies that could provide the desired performance characteristics was performed. Due to the strict mass limitations and wide operating temperature requirements of small UAVs, the only viable cell chemistries were determined to be lithium-ion liquid electrolyte systems and lithium-ion gel polymer electrolyte systems. Two lithium-ion gel polymer cell designs were selected as candidates and were tested using potential load profiles for UAV applications. Because lithium primary batteries have a higher specific energy and energy density, for the same mass and volume allocation, the secondary batteries resulted in shorter flight times than the primary batteries typically provide. When the batteries were operated at lower ambient temperatures (0 to -20 C), flight times were even further reduced. Despite the reduced flight times demonstrated, for certain UAV applications, the secondary batteries operated within the acceptable range of flight times at room temperature and above. The results of this testing indicate that a secondary battery power supply system can provide some benefits over the primary battery power supply system. A UAV can be operated for hundreds of flights using a secondary battery power supply system that provides the combined benefits of rechargeability and an inherently safer

Commercial vs professional UAVs for mapping

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Koukouvelas, Ioannis

2017-09-01

The continuous advancements in the technology behind Unmanned Aerial Vehicles (UAVs), in accordance with the consecutive decrease to their cost and the availability of photogrammetric software, make the use of UAVs an excellent tool for large scale mapping. In addition with the use of UAVs, the problems of increased costs, time consumption and the possible terrain accessibility problems, are significantly reduced. However, despite the growing number of UAV applications there has been a little quantitative assessment of UAV performance and of the quality of the derived products (orthophotos and Digital Surface Models). Here, we present results from field experiments designed to evaluate the accuracy of photogrammetrically-derived digital surface models (DSM) developed from imagery acquired with onboard digital cameras. We also show the comparison of the high resolution vs moderate resolution imagery for largescale geomorphic mapping. The acquired data analyzed in this study comes from a small commercial and a professional UAV. The test area was mapped using the same photogrammetric grid by the two UAVs. 3D models, DSMs and orthophotos were created using special software. Those products were compared to in situ survey measurements and the results are presented in this paper.

Utilization of Unmanned Aerial Vehicles for Rangeland Resources Monitoring in a Changing Regulatory Environment (Invited)

NASA Astrophysics Data System (ADS)

Rango, A.; Vivoni, E. R.; Browning, D. M.; Anderson, C.; Laliberte, A. S.

2013-12-01

It is taking longer than expected to realize the immense potential of Unmanned Aerial Vehicles (UAVs)for civil applications due to the complexity of regulations being developed by the Federal Aviation Authority (FAA) that can be applied to both manned and unmanned flight in the National Airspace System (NAS). As a result, FAA has required that for all UAV flights in the NAS, an external pilot must maintain line-of-sight contact with the UAV. Properly trained observers must also be present to assist the external pilot in collision avoidance. Additionally, in order to fly in the NAS, formal approval must be requested from FAA through application for a Certificate of Authorization (COA for government applicants or a Special Airworthiness Certificate (SAC) in the experimental category for non-government applicants. Flight crews of UAVs must pass exams also required for manned airplane pilots. Although flight crews for UAVs are not required to become manned airplane pilots, UAV flight missions are much more efficient if one or two of the UAV flight crew are also manned aircraft pilots so they can serve as the UAV mission commander. Our group has performed numerous UAV flights within the Jornada Experimental Range in southern New Mexico. Two developments with Jornada UAVs can be recommended to other UAV operators that would increase flight time experience and study areas covered by UAV images. First, do not overlook the possibility of obtaining permission to fly in Restricted Military Airspace (RMA). At the Jornada, our airspace is approximately 50% NAS and 50% RMA. With experiments ongoing in both types of airspace, we can fly in both areas and continue to increase UAV flights. Second, we have developed an air- and-ground vehicle approach for long distance, continuous pilot transport that always maintains line-of-sight requirements. This allows flying several target areas on a single mission and increasing the number of acquired UAV images - over 90,000 UAV images have

Multi-temporal high resolution monitoring of debris-covered glaciers using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kraaijenbrink, Philip; Immerzeel, Walter; de Jong, Steven; Shea, Joseph; Pellicciotti, Francesca; Meijer, Sander; Shresta, Arun

2016-04-01

Debris-covered glaciers in the Himalayas are relatively unstudied due to the difficulties in fieldwork caused by the inaccessible terrain and the presence of debris layers, which complicate in situ measurements. To overcome these difficulties an unmanned aerial vehicle (UAV) has been deployed multiple times over two debris covered glaciers in the Langtang catchment, located in the Nepalese Himalayas. Using differential GPS measurements and the Structure for Motion algorithm the UAV imagery was processed into accurate high-resolution digital elevation models and orthomosaics for both pre- and post-monsoon periods. These data were successfully used to estimate seasonal surface flow and mass wasting by using cross-correlation feature tracking and DEM differencing techniques. The results reveal large heterogeneity in mass loss and surface flow over the glacier surfaces, which are primarily caused by the presence of surface features such as ice cliffs and supra-glacial lakes. Accordingly, we systematically analyze those features using an object-based approach and relate their characteristics to the observed dynamics. We show that ice cliffs and supra-glacial lakes are contributing to a significant portion of the melt water of debris covered glaciers and we conclude that UAVs have great potential in understanding the key surface processes that remain largely undetected by using satellite remote sensing.

Fuel cell system with sodium borohydride as hydrogen source for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kim, Kyunghwan; Kim, Taegyu; Lee, Kiseong; Kwon, Sejin

In this study, we design and fabricate a fuel cell system for application as a power source in unmanned aerial vehicles (UAVs). The fuel cell system consists of a fuel cell stack, hydrogen generator, and hybrid power management system. PEMFC stack with an output power of 100 W is prepared and tested to decide the efficient operating conditions; the stack must be operated in the dead-end mode with purge in order to ensure prolonged stack performance. A hydrogen generator is fabricated to supply gaseous hydrogen to the stack. Sodium borohydride (NaBH 4) is used as the hydrogen source in the present study. Co/Al 2O 3 catalyst is prepared for the hydrolysis of the alkaline NaBH 4 solution at room temperature. The fabricated Co catalyst is comparable to the Ru catalyst. The UAV consumes more power in the takeoff mode than in the cruising mode. A hybrid power management system using an auxiliary battery is developed and evaluated for efficient energy management. Hybrid power from both the fuel cell and battery powers takeoff and turning flight operations, while the fuel cell supplies steady power during the cruising flight. The capabilities of the fuel-cell UAVs for long endurance flights are validated by successful flight tests.

Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

PubMed

Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

Automated Aerial Refueling Hitches a Ride on AFF

NASA Technical Reports Server (NTRS)

Hansen, Jennifer L.; Murray, James E.; Bever, Glenn; Campos, Norma V.; Schkolnik, Gerard

2007-01-01

The recent introduction of uninhabited aerial vehicles [UAVs (basically, remotely piloted or autonomous aircraft)] has spawned new developments in autonomous operation and posed new challenges. Automated aerial refueling (AAR) is a capability that will enable UAVs to travel greater distances and loiter longer over targets. NASA Dryden Flight Research Center, in cooperation with the Defense Advanced Research Projects Agency (DARPA), the Naval Air Systems Command (NAVAIR), the Naval Air Force Pacific Fleet, and the Air Force Research Laboratory, rapidly conceived and accomplished an AAR flight research project focused on collecting a unique, high-quality database on the dynamics of the hose and drogue of an aerial refueling system. This flight-derived database would be used to validate mathematical models of the dynamics in support of design and analysis of AAR systems for future UAVs. The project involved the use of two Dryden F/A-18 airplanes and an S-3 hose-drogue refueling store on loan from the Navy. In this year-long project, which was started on October 1, 2002, 583 research maneuvers were completed during 23 flights.

Roadside IED detection using subsurface imaging radar and rotary UAV

NASA Astrophysics Data System (ADS)

Qin, Yexian; Twumasi, Jones O.; Le, Viet Q.; Ren, Yu-Jiun; Lai, C. P.; Yu, Tzuyang

2016-05-01

Modern improvised explosive device (IED) and mine detection sensors using microwave technology are based on ground penetrating radar operated by a ground vehicle. Vehicle size, road conditions, and obstacles along the troop marching direction limit operation of such sensors. This paper presents a new conceptual design using a rotary unmanned aerial vehicle (UAV) to carry subsurface imaging radar for roadside IED detection. We have built a UAV flight simulator with the subsurface imaging radar running in a laboratory environment and tested it with non-metallic and metallic IED-like targets. From the initial lab results, we can detect the IED-like target 10-cm below road surface while carried by a UAV platform. One of the challenges is to design the radar and antenna system for a very small payload (less than 3 lb). The motion compensation algorithm is also critical to the imaging quality. In this paper, we also demonstrated the algorithm simulation and experimental imaging results with different IED target materials, sizes, and clutters.

Enabling high-quality observations of surface imperviousness for water runoff modelling from unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Tokarczyk, Piotr; Leitao, Joao Paulo; Rieckermann, Jörg; Schindler, Konrad; Blumensaat, Frank

2015-04-01

Modelling rainfall-runoff in urban areas is increasingly applied to support flood risk assessment particularly against the background of a changing climate and an increasing urbanization. These models typically rely on high-quality data for rainfall and surface characteristics of the area. While recent research in urban drainage has been focusing on providing spatially detailed rainfall data, the technological advances in remote sensing that ease the acquisition of detailed land-use information are less prominently discussed within the community. The relevance of such methods increase as in many parts of the globe, accurate land-use information is generally lacking, because detailed image data is unavailable. Modern unmanned air vehicles (UAVs) allow acquiring high-resolution images on a local level at comparably lower cost, performing on-demand repetitive measurements, and obtaining a degree of detail tailored for the purpose of the study. In this study, we investigate for the first time the possibility to derive high-resolution imperviousness maps for urban areas from UAV imagery and to use this information as input for urban drainage models. To do so, an automatic processing pipeline with a modern classification method is tested and applied in a state-of-the-art urban drainage modelling exercise. In a real-life case study in the area of Lucerne, Switzerland, we compare imperviousness maps generated from a consumer micro-UAV and standard large-format aerial images acquired by the Swiss national mapping agency (swisstopo). After assessing their correctness, we perform an end-to-end comparison, in which they are used as an input for an urban drainage model. Then, we evaluate the influence which different image data sources and their processing methods have on hydrological and hydraulic model performance. We analyze the surface runoff of the 307 individual sub-catchments regarding relevant attributes, such as peak runoff and volume. Finally, we evaluate the model

Development of Hardware-in-the-Loop Simulation Based on Gazebo and Pixhawk for Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Nguyen, Khoa Dang; Ha, Cheolkeun

2018-04-01

Hardware-in-the-loop simulation (HILS) is well known as an effective approach in the design of unmanned aerial vehicles (UAV) systems, enabling engineers to test the control algorithm on a hardware board with a UAV model on the software. Performance of HILS is determined by performances of the control algorithm, the developed model, and the signal transfer between the hardware and software. The result of HILS is degraded if any signal could not be transferred to the correct destination. Therefore, this paper aims to develop a middleware software to secure communications in HILS system for testing the operation of a quad-rotor UAV. In our HILS, the Gazebo software is used to generate a nonlinear six-degrees-of-freedom (6DOF) model, sensor model, and 3D visualization for the quad-rotor UAV. Meanwhile, the flight control algorithm is designed and implemented on the Pixhawk hardware. New middleware software, referred to as the control application software (CAS), is proposed to ensure the connection and data transfer between Gazebo and Pixhawk using the multithread structure in Qt Creator. The CAS provides a graphical user interface (GUI), allowing the user to monitor the status of packet transfer, and perform the flight control commands and the real-time tuning parameters for the quad-rotor UAV. Numerical implementations have been performed to prove the effectiveness of the middleware software CAS suggested in this paper.

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

NASA Technical Reports Server (NTRS)

Tran, Loc; Cross, Charles; Montague, Gilbert; Motter, Mark; Neilan, James; Qualls, Garry; Rothhaar, Paul; Trujillo, Anna; Allen, B. Danette

2015-01-01

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

Analysis of Nondeterministic Search Patterns for Minimization of UAV Counter-Targeting

DTIC Science & Technology

2013-03-01

Defense System NPS Naval Postgraduate School PDF Probability Distribution Function SLS Sea Level Standard UAV Unmanned Aerial Vehicle UAS Unmanned Aerial... intelli - gence regarding a target’s position is obtained, or when contact on a known target is lost. The shape of the AOU is often circular or elliptical...exceed this artificial boundary, ensuring that the searcher will never violate the actual area boundary. This constraint still enables the searcher to

Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Keller, James F.

This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent

Evaluation of Bare Ground on Rangelands using Unmanned Aerial Vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert P. Breckenridge; Maxine Dakins

2011-01-01

Attention is currently being given to methods that assess the ecological condition of rangelands throughout the United States. There are a number of different indicators that assess ecological condition of rangelands. Bare Ground is being considered by a number of agencies and resource specialists as a lead indicator that can be evaluated over a broad area. Traditional methods of measuring bare ground rely on field technicians collecting data along a line transect or from a plot. Unmanned aerial vehicles (UAVs) provide an alternative to collecting field data, can monitor a large area in a relative short period of time, andmore » in many cases can enhance safety and time required to collect data. In this study, both fixed wing and helicopter UAVs were used to measure bare ground in a sagebrush steppe ecosystem. The data were collected with digital imagery and read using the image analysis software SamplePoint. The approach was tested over seven different plots and compared against traditional field methods to evaluate accuracy for assessing bare ground. The field plots were located on the Idaho National Laboratory (INL) site west of Idaho Falls, Idaho in locations where there is very little disturbance by humans and the area is grazed only by wildlife. The comparison of fixed-wing and helicopter UAV technology against field estimates shows good agreement for the measurement of bare ground. This study shows that if a high degree of detail and data accuracy is desired, then a helicopter UAV may be a good platform. If the data collection objective is to assess broad-scale landscape level changes, then the collection of imagery with a fixed-wing system is probably more appropriate.« less

UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment.

PubMed

Chen, Jessie Y C

2010-08-01

A military reconnaissance environment was simulated to examine the performance of ground robotics operators who were instructed to utilise streaming video from an unmanned aerial vehicle (UAV) to navigate his/her ground robot to the locations of the targets. The effects of participants' spatial ability on their performance and workload were also investigated. Results showed that participants' overall performance (speed and accuracy) was better when she/he had access to images from larger UAVs with fixed orientations, compared with other UAV conditions (baseline- no UAV, micro air vehicle and UAV with orbiting views). Participants experienced the highest workload when the UAV was orbiting. Those individuals with higher spatial ability performed significantly better and reported less workload than those with lower spatial ability. The results of the current study will further understanding of ground robot operators' target search performance based on streaming video from UAVs. The results will also facilitate the implementation of ground/air robots in military environments and will be useful to the future military system design and training community.

Small Unmanned Aerial Vehicles in coastal areas: lessons learned from applications in Liguria, NW Mediterranean.

NASA Astrophysics Data System (ADS)

Rovere, A.; Casella, E.; Pedroncini, A.; Mucerino, L.; Casella, M.; Cusati, L. A.; Vacchi, M.; Ferrari, M.; Firpo, M.

2014-12-01

In 2013 we started to apply small UAVs to the study of coastal areas in Liguria, NW Mediterranean Sea. In this region monitoring coastal evolution and the impact of sea storms is a primary administrative need, as a large part of the economic income derives from summer tourism. In two years, we accumulated almost 200 hours of flight with two different UAVs, a professional-grade Mikrokopter Okto and a consumer-grade Phantom DJI. We used photogrammetric and orthorectification techniques to obtain Digital Elevation Models (DEMs) and orthophotos of different beaches in the region. Data from UAVs allowed us to answer several questions. What is the accuracy of DEMs obtained from UAVs in low-relief areas such as beaches? What are the problems encountered in the photogrammetric procedure near the shoreline? Are the results obtained with consumer-grade UAVs comparable to those obtained with professional-grade ones? Aside from these technical questions, we used the data obtained from UAVs for different local studies aimed at giving management tools to the local administrations. We used the cloudpoint obtained from DEMs and the orthophotos to set up a runup modelling chain, to detect short-term changes in the coastal zone, and to give a first estimate of the debris deposited on the beach after a major storm. As stated by Watts et al., 2012 (Remote Sensing 4, 1671-1692) the application of Unmanned Aerial Vehicles and photogrammetry techniques in earth sciences is flourishing, and has the potential to revolutionize the study of geomorphology. Surely, UAVs opened new research perspectives for our group, which has been actively working on coastal changes in Liguria for almost 25 years.

Comparison of Unmanned Aerial Vehicle Technology Versus Standard Practice in Identification of Hazards at a Mass Casualty Incident Scenario by Primary Care Paramedic Students.

PubMed

Jain, Trevor; Sibley, Aaron; Stryhn, Henrik; Hubloue, Ives

2018-01-31

Introduction The proliferation of unmanned aerial vehicles (UAV) has the potential to change the situational awareness of incident commanders allowing greater scene safety. The aim of this study was to compare UAV technology to standard practice (SP) in hazard identification during a simulated multi-vehicle motor collision (MVC) in terms of time to identification, accuracy and the order of hazard identification. A prospective observational cohort study was conducted with 21 students randomized into UAV or SP group, based on a MVC with 7 hazards. The UAV group remained at the UAV ground station while the SP group approached the scene. After identifying hazards the time and order was recorded. The mean time (SD, range) to identify the hazards were 3 minutes 41 seconds (1 minute 37 seconds, 1 minute 48 seconds-6 minutes 51 seconds) and 2 minutes 43 seconds (55 seconds, 1 minute 43 seconds-4 minutes 38 seconds) in UAV and SP groups corresponding to a mean difference of 58 seconds (P=0.11). A non-parametric permutation test showed a significant (P=0.04) difference in identification order. Both groups had 100% accuracy in hazard identification with no statistical difference in time for hazard identification. A difference was found in the identification order of hazards. (Disaster Med Public Health Preparedness. 2018;page 1 of 4).

Multiple UAV Cooperation for Wildfire Monitoring

NASA Astrophysics Data System (ADS)

Lin, Zhongjie

Wildfires have been a major factor in the development and management of the world's forest. An accurate assessment of wildfire status is imperative for fire management. This thesis is dedicated to the topic of utilizing multiple unmanned aerial vehicles (UAVs) to cooperatively monitor a large-scale wildfire. This is achieved through wildfire spreading situation estimation based on on-line measurements and wise cooperation strategy to ensure efficiency. First, based on the understanding of the physical characteristics of the wildfire propagation behavior, a wildfire model and a Kalman filter-based method are proposed to estimate the wildfire rate of spread and the fire front contour profile. With the enormous on-line measurements from on-board sensors of UAVs, the proposed method allows a wildfire monitoring mission to benefit from on-line information updating, increased flexibility, and accurate estimation. An independent wildfire simulator is utilized to verify the effectiveness of the proposed method. Second, based on the filter analysis, wildfire spreading situation and vehicle dynamics, the influence of different cooperation strategies of UAVs to the overall mission performance is studied. The multi-UAV cooperation problem is formulated in a distributed network. A consensus-based method is proposed to help address the problem. The optimal cooperation strategy of UAVs is obtained through mathematical analysis. The derived optimal cooperation strategy is then verified in an independent fire simulation environment to verify its effectiveness.

Spurious RF signals emitted by mini-UAVs

NASA Astrophysics Data System (ADS)

Schleijpen, Ric (H. M. A.); Voogt, Vincent; Zwamborn, Peter; van den Oever, Jaap

2016-10-01

This paper presents experimental work on the detection of spurious RF emissions of mini Unmanned Aerial Vehicles (mini-UAV). Many recent events have shown that mini-UAVs can be considered as a potential threat for civil security. For this reason the detection of mini-UAVs has become of interest to the sensor community. The detection, classification and identification chain can take advantage of different sensor technologies. Apart from the signatures used by radar and electro-optical sensor systems, the UAV also emits RF signals. These RF signatures can be split in intentional signals for communication with the operator and un-intentional RF signals emitted by the UAV. These unintentional or spurious RF emissions are very weak but could be used to discriminate potential UAV detections from false alarms. The goal of this research was to assess the potential of exploiting spurious emissions in the classification and identification chain of mini-UAVs. It was already known that spurious signals are very weak, but the focus was on the question whether the emission pattern could be correlated to the behaviour of the UAV. In this paper experimental examples of spurious RF emission for different types of mini-UAVs and their correlation with the electronic circuits in the UAVs will be shown

Integrating Unmanned Aerial Vehicles and Terrestrial Structure from Motion Photogrammetry for Assessing High Mountain Glacier Change, Huaytapallana, Peru

NASA Astrophysics Data System (ADS)

Wigmore, O.; Mark, B. G.; Lagos, P.; Somers, L. D.; McKenzie, J. M.; Huh, K. I.; Hopkinson, C.; Baraer, M.; Crumley, R. L.

2016-12-01

Terrestrial photogrammetry has a long and successful history of application to glaciological research. However, traditional methods rely upon large and expensive metric cameras and detailed triangulation of in-scene points for derivation of terrain models and analysis of glacier change. Recent developments in computer vision, including the advent of Structure from Motion (SfM) algorithms and associated software packages have made it possible to use consumer grade digital cameras to produce highly precise digital elevation models. This has facilitated the rapid expansion of unmanned aerial vehicles (UAVs) for mapping purposes. However, without onboard RTK GNSS positions of the UAV, within scene survey-grade ground targets are required for accurate georectification. Gaining access to mountain glaciers for the installation and survey of ground targets is often labour intensive, hazardous and sometimes impossible. Compounding this are limitations of UAV flight within these confined and high elevation locations and reduced flight times that limit the total survey area. Luckily, these environments also present a highly suitable location for the application of terrestrial SfM photogrammetry; because; high moraines, cliffs and ridgelines provide excellent 'semi-nadir' viewing of the glacier surface; while steep mountain walls present a close to nadir view from an oblique angle. In this study we present a workflow and results from an integrated UAV and terrestrial SfM photogrammetry campaign at Huaytapallana glacier, Huancayo Peru. We combined terrestrial images taken from GNSS surveyed positions with oblique UAV imagery of the mountain face. From this data a centimetre resolution orthomosaic and a decimetre resolution DEM of the snow and ice covered mountain face and proglacial lake were generated, covering over 6km2. Accuracy of the surface was determined from comparison over ice free areas to 1m aerial LiDAR data collected in 2009. Changes in glacier volume were then

Measuring atmospheric aerosols of organic origin on multirotor Unmanned Aerial Vehicles (UAVs).

NASA Astrophysics Data System (ADS)

Crazzolara, Claudio; Platis, Andreas; Bange, Jens

2017-04-01

In-situ measurements of the spatial distribution and transportation of atmospheric organic particles such as pollen and spores are of great interdisciplinary interest such as: - In agriculture to investigate the spread of transgenetic material, - In paleoclimatology to improve the accuracy of paleoclimate models derived from pollen grains retrieved from sediments, and - In meteorology/climate research to determine the role of spores and pollen acting as nuclei in cloud formation processes. The few known state of the art in-situ measurement systems are using passive sampling units carried by fixed wing UAVs, thus providing only limited spatial resolution of aerosol concentration. Also the passively sampled air volume is determined with low accuracy as it is only calculated by the length of the flight path. We will present a new approach, which is based on the use of a multirotor UAV providing a versatile platform. On this UAV an optical particle counter in addition to a particle collecting unit, e.g. a conventional filter element and/or a inertial mass separator were installed. Both sampling units were driven by a mass flow controlled blower. This allows not only an accurate determination of the number and size concentration, but also an exact classification of the type of collected aerosol particles as well as an accurate determination of the sampled air volume. In addition, due to the application of a multirotor UAV with its automated position stabilisation system, the aerosol concentration can be measured with a very high spatial resolution of less than 1 m in all three dimensions. The combination of comprehensive determination of number, type and classification of aerosol particles in combination with the very high spatial resolution provides not only valuable progress in agriculture, paleoclimatology and meteorology, but also opens up the application of multirotor UAVs in new fields, for example for precise determination of the mechanisms of generation and

Video change detection for fixed wing UAVs

NASA Astrophysics Data System (ADS)

Bartelsen, Jan; Müller, Thomas; Ring, Jochen; Mück, Klaus; Brüstle, Stefan; Erdnüß, Bastian; Lutz, Bastian; Herbst, Theresa

2017-10-01

In this paper we proceed the work of Bartelsen et al.1 We present the draft of a process chain for an image based change detection which is designed for videos acquired by fixed wing unmanned aerial vehicles (UAVs). From our point of view, automatic video change detection for aerial images can be useful to recognize functional activities which are typically caused by the deployment of improvised explosive devices (IEDs), e.g. excavations, skid marks, footprints, left-behind tooling equipment, and marker stones. Furthermore, in case of natural disasters, like flooding, imminent danger can be recognized quickly. Due to the necessary flight range, we concentrate on fixed wing UAVs. Automatic change detection can be reduced to a comparatively simple photogrammetric problem when the perspective change between the "before" and "after" image sets is kept as small as possible. Therefore, the aerial image acquisition demands a mission planning with a clear purpose including flight path and sensor configuration. While the latter can be enabled simply by a fixed and meaningful adjustment of the camera, ensuring a small perspective change for "before" and "after" videos acquired by fixed wing UAVs is a challenging problem. Concerning this matter, we have performed tests with an advanced commercial off the shelf (COTS) system which comprises a differential GPS and autopilot system estimating the repetition accuracy of its trajectory. Although several similar approaches have been presented,23 as far as we are able to judge, the limits for this important issue are not estimated so far. Furthermore, we design a process chain to enable the practical utilization of video change detection. It consists of a front-end of a database to handle large amounts of video data, an image processing and change detection implementation, and the visualization of the results. We apply our process chain on the real video data acquired by the advanced COTS fixed wing UAV and synthetic data. For the

Spectral Imaging from Uavs Under Varying Illumination Conditions

NASA Astrophysics Data System (ADS)

Hakala, T.; Honkavaara, E.; Saari, H.; Mäkynen, J.; Kaivosoja, J.; Pesonen, L.; Pölönen, I.

2013-08-01

Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes with stereoscopic overlaps. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14-0.18. In the corrected data, the homogeneity was 0.10-0.12 with a correction based on broadband irradiance measured in UAV, 0.07-0.09 with a correction based on spectral irradiance measurement on ground, and 0.05-0.08 with a radiometric block adjustment based on image data. Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications.

Draper Laboratory small autonomous aerial vehicle

NASA Astrophysics Data System (ADS)

DeBitetto, Paul A.; Johnson, Eric N.; Bosse, Michael C.; Trott, Christian A.

1997-06-01

The Charles Stark Draper Laboratory, Inc. and students from Massachusetts Institute of Technology and Boston University have cooperated to develop an autonomous aerial vehicle that won the 1996 International Aerial Robotics Competition. This paper describes the approach, system architecture and subsystem designs for the entry. This entry represents a combination of many technology areas: navigation, guidance, control, vision processing, human factors, packaging, power, real-time software, and others. The aerial vehicle, an autonomous helicopter, performs navigation and control functions using multiple sensors: differential GPS, inertial measurement unit, sonar altimeter, and a flux compass. The aerial transmits video imagery to the ground. A ground based vision processor converts the image data into target position and classification estimates. The system was designed, built, and flown in less than one year and has provided many lessons about autonomous vehicle systems, several of which are discussed. In an appendix, our current research in augmenting the navigation system with vision- based estimates is presented.

Numerical RCS and micro-Doppler investigations of a consumer UAV

NASA Astrophysics Data System (ADS)

Schröder, Arne; Aulenbacher, Uwe; Renker, Matthias; Böniger, Urs; Oechslin, Roland; Murk, Axel; Wellig, Peter

2016-10-01

This contribution gives an overview of recent investigations regarding the detection of a consumer market unmanned aerial vehicles (UAV). The steadily increasing number of such drones gives rise to the threat of UAVs interfering civil air traffic. Technologies for monitoring UAVs which are flying in restricted air space, i. e. close to airports or even over airports, are desperately needed. One promising way for tracking drones is to employ radar systems. For the detection and classification of UAVs, the knowledge about their radar cross section (RCS) and micro-Doppler signature is of particular importance. We have carried out numerical and experimental studies of the RCS and the micro-Doppler of an example commercial drone in order to study its detectability with radar systems.

Direct Penguin Counting Using Unmanned Aerial Vehicle Image

NASA Astrophysics Data System (ADS)

Hyun, C. U.; Kim, H. C.; Kim, J. H.; Hong, S. G.

2015-12-01

This study presents an application of unmanned aerial vehicle (UAV) images to monitor penguin colony in Baton Peninsula, King George Island, Antarctica. The area around Narębski Point located on the southeast coast of Barton Peninsula was designated as Antarctic Specially Protected Area No. 171 (ASPA 171), and Chinstrap and Gentoo penguins inhabit in this area. The UAV images were acquired in a part of ASPA 171 from four flights in a single day, Jan 18, 2014. About 360 images were mosaicked as an image of about 3 cm spatial resolution and then a subset including representative penguin rookeries was selected. The subset image was segmented based on gradient map of pixel values, and spectral and spatial attributes were assigned to each segment. The object based image analysis (OBIA) was conducted with consideration of spectral attributes including mean and minimum values of each segment and various shape attributes such as area, length, compactness and roundness to detect individual penguin. The segments indicating individual penguin were effectively detected on rookeries with high contrasts in the spectral and shape attributes. The importance of periodic and precise monitoring of penguins has been recognized because variations of their populations reflect environmental changes and disturbance from human activities. Utilization of very high resolution imaging method shown in this study can be applied to other penguin habitats in Antarctica, and the results will be able to support establishing effective environmental management plans.

Building Information Modelling (BIM) and Unmanned Aerial Vehicle (UAV) technologies in infrastructure construction project management and delay and disruption analysis

NASA Astrophysics Data System (ADS)

Vacanas, Yiannis; Themistocleous, Kyriacos; Agapiou, Athos; Hadjimitsis, Diofantos

2015-06-01

Time in infrastructure construction projects has always been a fundamental issue as early as from the inception of a project, during the construction process and often after the completion and delivery. In a typical construction contract time related matters such as the completion date and possible delays are among the most important issues that are dealt with by the contract provisions. In the event of delay there are usually provisions for extension of time award to the contractor with possible reimbursement for the extra cost and expenses caused by this extension of time to the contract duration. In the case the contractor is not entitled to extension of time, the owner will be possibly entitled to amounts as compensation for the time prohibited from using his development. Even in the event of completion within the time agreed, under certain circumstances a contractor may have claims for reimbursement for extra costs incurred due to induced acceleration measures he had to take in order to mitigate disruption effects caused to the progress of the works by the owner or his representatives. Depending on the size of the project and the agreement amount, these reimbursement sums may be extremely high. Therefore innovative methods with the exploitation of new technologies for effective project management for the avoidance of delays, delay analysis and mitigation measures are essential; moreover, methods for collecting efficiently information during the construction process so that disputes regarding time are avoided or resolved in a quick and fair manner are required. This paper explores the state of art for existing use of Building Information Modelling (BIM) and Unmanned Aerial Vehicles (UAV) technologies in the construction industry in general. Moreover the paper considers the prospect of using BIM technology in conjunction with the use of UAV technology for efficient and accurate as-built data collection and illustration of the works progress during an

Cooperative Monocular-Based SLAM for Multi-UAV Systems in GPS-Denied Environments.

PubMed

Trujillo, Juan-Carlos; Munguia, Rodrigo; Guerra, Edmundo; Grau, Antoni

2018-04-26

This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation.

Diverse Planning for UAV Control and Remote Sensing

PubMed Central

Tožička, Jan; Komenda, Antonín

2016-01-01

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs. PMID:28009831

Diverse Planning for UAV Control and Remote Sensing.

PubMed

Tožička, Jan; Komenda, Antonín

2016-12-21

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

Augmented Reality Tool for the Situational Awareness Improvement of UAV Operators

PubMed Central

Ruano, Susana; Cuevas, Carlos; Gallego, Guillermo; García, Narciso

2017-01-01

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and information coming from other sensors. To avoid the burden of fusing information displayed in the two screens, an Augmented Reality (AR) tool is proposed in this paper. The AR system has two functionalities for Medium-Altitude Long-Endurance (MALE) UAVs: route orientation and target identification. Route orientation allows the operator to identify the upcoming waypoints and the path that the UAV is going to follow. Target identification allows a fast target localization, even in the presence of occlusions. The AR tool is implemented following the North Atlantic Treaty Organization (NATO) standards so that it can be used in different GCSs. The experiments show how the AR tool improves significantly the situational awareness of the UAV operators. PMID:28178189

Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

PubMed Central

Xi jun, Gao; Zi li, Chen; Yong Jiang, Hu

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication. PMID:24977185

The UAV: A unique platform for electrodynamic studies of upward lightning in the middle atmosphere

NASA Technical Reports Server (NTRS)

Goldberg, Richard A.; Desch, Michael D.; Farrell, William M.

1997-01-01

The use of unmanned aerial vehicles (UAVs), a platform for investigations in an environment hostile to manned spacecraft, is discussed. A program which includes the use of UAVs coupled with ground-based measurements to conduct scientific studies on the electrical state of the atmosphere during electrically active periods is proposed. The radiating power from alternate current and transient components of the storm electrification was investigated.

The application of the unmanned aerial vehicle remote sensing technology in the FAST project construction

NASA Astrophysics Data System (ADS)

Zhu, Boqin

2015-08-01

The purpose of using unmanned aerial vehicle (UAV) remote sensing application in Five-hundred-meter aperture spherical telescope (FAST) project is to dynamically record the construction process with high resolution image, monitor the environmental impact, and provide services for local environmental protection and the reserve immigrants. This paper introduces the use of UAV remote sensing system and the course design and implementation for the FAST site. Through the analysis of the time series data, we found that: (1) since the year 2012, the project has been widely carried out; (2) till 2013, the internal project begun to take shape;(3) engineering excavation scope was kept stable in 2014, and the initial scale of the FAST engineering construction has emerged as in the meantime, the vegetation recovery went well on the bare soil area; (4) in 2015, none environmental problems caused by engineering construction and other engineering geological disaster were found in the work area through the image interpretation of UAV images. This paper also suggested that the UAV technology need some improvements to fulfill the requirements of surveying and mapping specification., including a new data acquisition and processing measures assigned with the background of highly diverse elevation, usage of telephoto camera, hierarchical photography with different flying height, and adjustment with terrain using the joint empty three settlement method.

Pheromone-based coordination strategy to static sensors on the ground and unmanned aerial vehicles carried sensors

NASA Astrophysics Data System (ADS)

Pignaton de Freitas, Edison; Heimfarth, Tales; Pereira, Carlos Eduardo; Morado Ferreira, Armando; Rech Wagner, Flávio; Larsson, Tony

2010-04-01

A current trend that is gaining strength in the wireless sensor network area is the use of heterogeneous sensor nodes in one coordinated overall network, needed to fulfill the requirements of sophisticated emerging applications, such as area surveillance systems. One of the main concerns when developing such sensor networks is how to provide coordination among the heterogeneous nodes, in order to enable them to efficiently respond the user needs. This study presents an investigation of strategies to coordinate a set of static sensor nodes on the ground cooperating with wirelessly connected Unmanned Aerial Vehicles (UAVs) carrying a variety of sensors, in order to provide efficient surveillance over an area of interest. The sensor nodes on the ground are set to issue alarms on the occurrence of a given event of interest, e.g. entrance of a non-authorized vehicle in the area, while the UAVs receive the issued alarms and have to decide which of them is the most suitable to handle the issued alarm. A bio-inspired coordination strategy based on the concept of pheromones is presented. As a complement of this strategy, a utility-based decision making approach is proposed.

A Smart Irrigation Approach Aided by Monitoring Surface Soil Moisture using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Wienhold, K. J.; Li, D.; Fang, N. Z.

2017-12-01

Soil moisture is a critical component in the optimization of irrigation scheduling in water resources management. Unmanned Aerial Vehicles (UAV) equipped with multispectral sensors represent an emerging technology capable of detecting and estimating soil moisture for irrigation and crop management. This study demonstrates a method of using a UAV as an optical and thermal remote sensing platform combined with genetic programming to derive high-resolution, surface soil moisture (SSM) estimates. The objective is to evaluate the feasibility of spatially-variable irrigation management for a golf course (about 50 acres) in North Central Texas. Multispectral data is collected over the course of one month in the visible, near infrared and longwave infrared spectrums using a UAV capable of rapid and safe deployment for daily estimates. The accuracy of the model predictions is quantified using a time domain reflectometry (TDR) soil moisture sensor and a holdout validation test set. The model produces reasonable estimates for SSM with an average coefficient of correlation (r) = 0.87 and coefficient of determination of (R2) = 0.76. The study suggests that the derived SSM estimates be used to better inform irrigation scheduling decisions for lightly vegetated areas such as the turf or native roughs found on golf courses.

Development of a Rotary Wing Unmanned Aerial Vehicle (UAV) Simulation Model

DTIC Science & Technology

2014-03-01

Features Language URL Autopilot: DIY UAV - 2 DOF proportional controller - Kalman filtering C http://autopilot.sour ceforge.net Paperazzi - 3 DOF...proprtional controller - Basic navigation OCaml http://paparazzi.ena c.fr JSBSim - Basic control system blockset - Sample autopilot

Possibilities of Use of UAVS for Technical Inspection of Buildings and Constructions

NASA Astrophysics Data System (ADS)

Banaszek, Anna; Banaszek, Sebastian; Cellmer, Anna

2017-12-01

In recent years, Unmanned Aerial Vehicles (UAVs) have been used in various sectors of the economy. This is due to the development of new technologies for acquiring and processing geospatial data. The paper presents the results of experiments using UAV, equipped with a high resolution digital camera, for a visual assessment of the technical condition of the building roof and for the inventory of energy infrastructure and its surroundings. The usefulness of digital images obtained from the UAV deck is presented in concrete examples. The use of UAV offers new opportunities in the area of technical inspection due to the detail and accuracy of the data, low operating costs and fast data acquisition.

Research on UAV Intelligent Obstacle Avoidance Technology During Inspection of Transmission Line

NASA Astrophysics Data System (ADS)

Wei, Chuanhu; Zhang, Fei; Yin, Chaoyuan; Liu, Yue; Liu, Liang; Li, Zongyu; Wang, Wanguo

Autonomous obstacle avoidance of unmanned aerial vehicle (hereinafter referred to as UAV) in electric power line inspection process has important significance for operation safety and economy for UAV intelligent inspection system of transmission line as main content of UAV intelligent inspection system on transmission line. In the paper, principles of UAV inspection obstacle avoidance technology of transmission line are introduced. UAV inspection obstacle avoidance technology based on particle swarm global optimization algorithm is proposed after common obstacle avoidance technologies are studied. Stimulation comparison is implemented with traditional UAV inspection obstacle avoidance technology which adopts artificial potential field method. Results show that UAV inspection strategy of particle swarm optimization algorithm, adopted in the paper, is prominently better than UAV inspection strategy of artificial potential field method in the aspects of obstacle avoidance effect and the ability of returning to preset inspection track after passing through the obstacle. An effective method is provided for UAV inspection obstacle avoidance of transmission line.

Development of Cloud-Based UAV Monitoring and Management System

PubMed Central

Itkin, Mason; Kim, Mihui; Park, Younghee

2016-01-01

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery). The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation. PMID:27854267

Development of Cloud-Based UAV Monitoring and Management System.

PubMed

Itkin, Mason; Kim, Mihui; Park, Younghee

2016-11-15

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery). The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation.

Evaluating the accuracy of orthophotos and 3D models from UAV photogrammetry

NASA Astrophysics Data System (ADS)

Julge, Kalev; Ellmann, Artu

2015-04-01

Rapid development of unmanned aerial vehicles (UAV) in recent years has made their use for various applications more feasible. This contribution evaluates the accuracy and quality of different UAV remote sensing products (i.e. orthorectified image, point cloud and 3D model). Two different autonomous fixed wing UAV systems were used to collect the aerial photographs. One is a mass-produced commercial UAV system, the other is a similar state-of-the-art UAV system. Three different study areas with varying sizes and characteristics (including urban areas, forests, fields, etc.) were surveyed. The UAV point clouds, 3D models and orthophotos were generated with three different commercial and free-ware software. The performance of each of these was evaluated. The effect of flying height on the accuracy of the results was explored, as well as the optimum number and placement of ground control points. Also the achieved results, when the only georeferencing data originates from the UAV system's on-board GNSS and inertial measurement unit, are investigated. Problems regarding the alignment of certain types of aerial photos (e.g. captured over forested areas) are discussed. The quality and accuracy of UAV photogrammetry products are evaluated by comparing them with control measurements made with GNSS-measurements on the ground, as well as high-resolution airborne laser scanning data and other available orthophotos (e.g. those acquired for large scale national mapping). Vertical comparisons are made on surfaces that have remained unchanged in all campaigns, e.g. paved roads. Planar comparisons are performed by control surveys of objects that are clearly identifiable on orthophotos. The statistics of these differences are used to evaluate the accuracy of UAV remote sensing. Some recommendations are given on how to conduct UAV mapping campaigns cost-effectively and with minimal time-consumption while still ensuring the quality and accuracy of the UAV data products. Also the

Estimating snow depth in real time using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Mizinski, Bartlomiej; Witek, Matylda; Spallek, Waldemar; Szymanowski, Mariusz

2016-04-01

In frame of the project no. LIDER/012/223/L-5/13/NCBR/2014, financed by the National Centre for Research and Development of Poland, we elaborated a fully automated approach for estimating snow depth in real time in the field. The procedure uses oblique aerial photographs taken by the unmanned aerial vehicle (UAV). The geotagged images of snow-covered terrain are processed by the Structure-from-Motion (SfM) method which is used to produce a non-georeferenced dense point cloud. The workflow includes the enhanced RunSFM procedure (keypoint detection using the scale-invariant feature transform known as SIFT, image matching, bundling using the Bundler, executing the multi-view stereo PMVS and CMVS2 software) which is preceded by multicore image resizing. The dense point cloud is subsequently automatically georeferenced using the GRASS software, and the ground control points are borrowed from positions of image centres acquired from the UAV-mounted GPS receiver. Finally, the digital surface model (DSM) is produced which - to improve the accuracy of georeferencing - is shifted using a vector obtained through precise geodetic GPS observation of a single ground control point (GCP) placed on the Laboratory for Unmanned Observations of Earth (mobile lab established at the University of Wroclaw, Poland). The DSM includes snow cover and its difference with the corresponding snow-free DSM or digital terrain model (DTM), following the concept of the digital elevation model of differences (DOD), produces a map of snow depth. Since the final result depends on the snow-free model, two experiments are carried out. Firstly, we show the performance of the entire procedure when the snow-free model reveals a very high resolution (3 cm/px) and is produced using the UAV-taken photographs and the precise GCPs measured by the geodetic GPS receiver. Secondly, we perform a similar exercise but the 1-metre resolution light detection and ranging (LIDAR) DSM or DTM serves as the snow-free model

Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring.

PubMed

Trasviña-Moreno, Carlos A; Blasco, Rubén; Marco, Álvaro; Casas, Roberto; Trasviña-Castro, Armando

2017-02-24

Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario.

Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring

PubMed Central

Trasviña-Moreno, Carlos A.; Blasco, Rubén; Marco, Álvaro; Casas, Roberto; Trasviña-Castro, Armando

2017-01-01

Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario. PMID:28245587

Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

NASA Astrophysics Data System (ADS)

Izumida, Atsuto; Uchiyama, Shoichiro; Sugai, Toshihiko

2017-09-01

Geomorphic impacts of a disastrous crevasse splay that formed in September 2015 and its post-formation modifications were quantitatively documented by using repeated, high-definition digital surface models (DSMs) of an inhabited and cultivated floodplain of the Kinu River, central Japan. The DSMs were based on pre-flood (resolution: 2 m) and post-flood (resolution: 1 m) aerial light detection and ranging (lidar) data from January 2007 and September 2015, respectively, and on structure-from-motion (SfM) photogrammetry data (resolution: 3.84 cm) derived from aerial photos taken by an unmanned aerial vehicle (UAV) in December 2015. After elimination of systematic errors among the DSMs and down-sampling of the SfM-derived DSM, elevation changes on the order of 10-1 m - including not only topography but also growth of vegetation, vanishing of flood waters, and restoration and repair works - were detected. Comparison of the DSMs showed that the volume eroded by the flood was more than twice the deposited volume in the area within 300-500 m of the breached artificial levee, where the topography was significantly affected. The results suggest that DSMs based on a combination of UAV-SfM and lidar data can be used to quantify, rapidly and in rich detail, topographic changes on floodplains caused by floods.

Observing changes at Santiaguito Volcano, Guatemala with an Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

von Aulock, Felix W.; Lavallée, Yan; Hornby, Adrian J.; Lamb, Oliver D.; Andrews, Benjamin J.; Kendrick, Jackie E.

2016-04-01

Santiaguito Volcano (Guatemala) is one of the most active volcanoes in Central America, producing several ash venting explosions per day for almost 100 years. Lahars, lava flows and dome and flank collapses that produce major pyroclastic density currents also present a major hazard to nearby farms and communities. Optical observations of both the vent as well as the lava flow fronts can provide scientists and local monitoring staff with important information on the current state of volcanic activity and hazard. Due to the strong activity, and difficult terrain, unmanned aerial vehicles can help to provide valuable data on the activities of the volcano at a safe distance. We collected a series of images and video footage of A.) The active vent of Caliente and B.) The flow front of the active lava flow and its associated lahar channels, both in May 2015 and in December 2015- January 2016. Images of the crater and the lava flows were used for the reconstruction of 3D terrain models using structure-from-motion. These were supported by still frames from the video recording. Video footage of the summit crater (during two separate ash venting episodes) and the lava flow fronts indicate the following differences in activity during those two field campaigns: A.) - A new breach opened on the east side of the crater rim, possibly during the collapse in November 2015. - The active lava dome is now almost completely covered with ash, only leaving the largest blocks and faults exposed in times without gas venting - A recorded explosive event in December 2015 initiates at subparallel linear faults near the centre of the dome, rather than arcuate or ring faults, with a later, separate, and more ash-laden burst occurring from an off-centre fracture, however, other explosions during the observation period were seen to persist along the ring fault system observed on the lava dome since at least 2007 - suggesting a diversification of explosive activity. B.) - The lava flow fronts did

Conceptual Design of a Vertical Takeoff and Landing Unmanned Aerial Vehicle with 24-HR Endurance

NASA Technical Reports Server (NTRS)

Fredericks, William J.

2010-01-01

This paper describes a conceptual design study for a vertical takeoff and landing (VTOL) unmanned aerial vehicle (UAV) that is able to carry a 25-lb science payload for 24 hr and is able to land and take off at elevations as high as 15,000 ft without human intervention. In addition to the science payload, this vehicle must be able to carry a satellite communication system, and the vehicle must be able to be transported in a standard full-size pickup truck and assembled by only two operators. This project started with a brainstorming phase to devise possible vehicle configurations that might satisfy the requirements. A down select was performed to select a near-term solution and two advanced vehicle concepts that are better suited to the intent of the mission. Sensitivity analyses were also performed on the requirements and the technology levels to obtain a better understanding of the design space. This study found that within the study assumptions the mission is feasible; the selected concepts are recommended for further development.

Technologies Advance UAVs for Science, Military

NASA Technical Reports Server (NTRS)

2010-01-01

A Space Act Agreement with Goddard Space Flight Center and West Virginia University enabled Aurora Flight Sciences Corporation, of Manassas, Virginia, to develop cost-effective composite manufacturing capabilities and open a facility in West Virginia. The company now employs 160 workers at the plant, tasked with crafting airframe components for the Global Hawk unmanned aerial vehicle (UAV) program. While one third of the company's workforce focuses on Global Hawk production, the rest of the company develops advanced UAV technologies that are redefining traditional approaches to unmanned aviation. Since the company's founding, Aurora s cutting-edge work has been supported with funding from NASA's Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs.

Geohazard reconnaissance mapping for potential rock boulder fall using low altitude UAV photogrammetry

NASA Astrophysics Data System (ADS)

Sharan Kumar, N.; Ashraf Mohamad Ismail, Mohd; Sukor, Nur Sabahiah Abdul; Cheang, William

2018-05-01

This paper discusses potential applications of unmanned aerial vehicles (UAVs) for evaluation of risk immediately with photos and 3-dimensional digital element. Aerial photography using UAV ready to give a powerful technique for potential rock boulder fall recognition. High-resolution outputs from this method give the chance to evaluate the site for potential rock boulder falls spatially. The utilization of UAV to capture the aerial photos is a quick, reliable, and cost-effective technique contrasted with terrestrial laser scanning method. Reconnaissance of potential rock boulder susceptible to fall is very crucial during the geotechnical investigation. This process is essential in the view of the rock fall hazards nearby site before the beginning of any preliminary work. Photogrammetric applications have empowered the automated way to deal with identification of rock boulder susceptible to fall by recognizing the location, size, and position. A developing examination of the utilization of digital photogrammetry gives numerous many benefits for civil engineering application. These advancements have made important contributions to our capabilities to create the geohazard map on potential rock boulder fall.

Metadata-assisted nonuniform atmospheric scattering model of image haze removal for medium-altitude unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Liu, Chunlei; Ding, Wenrui; Li, Hongguang; Li, Jiankun

2017-09-01

Haze removal is a nontrivial work for medium-altitude unmanned aerial vehicle (UAV) image processing because of the effects of light absorption and scattering. The challenges are attributed mainly to image distortion and detail blur during the long-distance and large-scale imaging process. In our work, a metadata-assisted nonuniform atmospheric scattering model is proposed to deal with the aforementioned problems of medium-altitude UAV. First, to better describe the real atmosphere, we propose a nonuniform atmospheric scattering model according to the aerosol distribution, which directly benefits the image distortion correction. Second, considering the characteristics of long-distance imaging, we calculate the depth map, which is an essential clue to modeling, on the basis of UAV metadata information. An accurate depth map reduces the color distortion compared with the depth of field obtained by other existing methods based on priors or assumptions. Furthermore, we use an adaptive median filter to address the problem of fuzzy details caused by the global airlight value. Experimental results on both real flight and synthetic images demonstrate that our proposed method outperforms four other existing haze removal methods.

Intification and modelling of flight characteristics for self-build shock flyer type UAV

NASA Astrophysics Data System (ADS)

Rashid., Z. A.; Dardin, A. S. F. Syed.; Azid, A. A.; Ahmad, K. A.

2018-02-01

The development of an autonomous Unmanned Aerial Vehicle (UAV) requires a fundamentals studies of the UAV's flight characteristic. The aim of this study is to identify and model the flight characteristic of a conventional fixed-wing type UAV. Subsequence to this, the mode of flight of the UAV can be investigated. One technique to identify the characteristic of a UAV is a flight test where it required specific maneuvering to be executed while measuring the attitude sensor. In this study, a simple shock flyer type UAV was used as the aircraft. The result shows that the modeled flight characteristic has a significant relation with actual values but the fitting value is rather small. It is suggested that the future study is conducted with an improvement of the physical UAV, data filtering and better system identification methods.

'Fly Like This': Natural Language Interface for UAV Mission Planning

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Meszaros, Erica L.; Trujillo, Anna; Allen, B. Danette

2017-01-01

With the increasing presence of unmanned aerial vehicles (UAVs) in everyday environments, the user base of these powerful and potentially intelligent machines is expanding beyond exclusively highly trained vehicle operators to include non-expert system users. Scientists seeking to augment costly and often inflexible methods of data collection historically used are turning towards lower cost and reconfigurable UAVs. These new users require more intuitive and natural methods for UAV mission planning. This paper explores two natural language interfaces - gesture and speech - for UAV flight path generation through individual user studies. Subjects who participated in the user studies also used a mouse-based interface for a baseline comparison. Each interface allowed the user to build flight paths from a library of twelve individual trajectory segments. Individual user studies evaluated performance, efficacy, and ease-of-use of each interface using background surveys, subjective questionnaires, and observations on time and correctness. Analysis indicates that natural language interfaces are promising alternatives to traditional interfaces. The user study data collected on the efficacy and potential of each interface will be used to inform future intuitive UAV interface design for non-expert users.

Using small unmanned aerial vehicle for instream habitat evaluation and modelling

NASA Astrophysics Data System (ADS)

Astegiano, Luca; Vezza, Paolo; Comoglio, Claudio; Lingua, Andrea; Spairani, Michele

2015-04-01

Recent advances in digital image collection and processing have led to the increased use of unmanned aerial vehicles (UAV) for river research and management. In this paper, we assess the capabilities of a small UAV to characterize physical habitat for fish in three river stretches of North-Western Italy. The main aim of the study was identifying the advantages and challenges of this technology for environmental river management, in the context of the increasing river exploitation for hydropower production. The UAV used to acquire overlapping images was a small quadcopter with a two different high-resolution (non-metric) cameras (Nikon J1™ and Go-Pro Hero 3 Black Edition™). The quadcopter was preprogrammed to fly set waypoints using a small tablet PC. With the acquired imagery, we constructed a 5-cm resolution orthomosaic image and a digital surface model (DSM). The two products were used to map the distribution of aquatic and riparian habitat features, i.e., wetted area, morphological unit distributions, bathymetry, water surface gradient, substrates and grain sizes, shelters and cover for fish. The study assessed the quality of collected data and used such information to identify key reach-scale metrics and important aspects of fluvial morphology and aquatic habitat. The potential and limitations of using UAV for physical habitat survey were evaluated and the collected data were used to initialize and run common habitat simulation tools (MesoHABSIM). Several advantages of using UAV-based imagery were found, including low cost procedures, high resolution and efficiency in data collection. However, some challenges were identified for bathymetry extraction (vegetation obstructions, white waters, turbidity) and grain size assessment (preprocessing of data and automatic object detection). The application domain and possible limitation for instream habitat mapping were defined and will be used as a reference for future studies. Ongoing activities include the

Atmospheric Mining in the Outer Solar System:. [Aerial Vehicle Reconnaissance and Exploration Options

NASA Technical Reports Server (NTRS)

Palaszewski, Bryan A.

2014-01-01

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and hydrogen can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and hydrogen (deuterium, etc.) were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. Additional supporting analyses were conducted to illuminate vehicle sizing and orbital transportation issues. While capturing 3He, large amounts of hydrogen and 4He are produced. With these two additional gases, the potential for fueling small and large fleets of additional exploration and exploitation vehicles exists. Additional aerospacecraft or other aerial vehicles (UAVs, balloons, rockets, etc.) could fly through the outer planet atmospheres, for global weather observations, localized storm or other disturbance investigations, wind speed measurements, polar observations, etc. Deep-diving aircraft (built with the strength to withstand many atmospheres of pressure) powered by the excess hydrogen or helium 4 may be designed to probe the higher density regions of the gas giants. Outer planet atmospheric properties, atmospheric storm data, and mission planning for future outer planet UAVs are presented.

Solar Cell to Support Perpetual Flight of High Altitude Long Endurance UAV ITB

NASA Astrophysics Data System (ADS)

Luqmanul Hakim, Muhammad; Silitonga, Faber Y.; Rosid, Nurhayyan H.; Mochammad Agoes Moelyadi, Ing., Dr.

2018-04-01

Research on a High Altitude Long Endurance (HALE) Unmanned Aerial Vehicle (UAV) is currently being conducted at Bandung Institute of Technology to reach the flight duration needed and to get the solution of today’s challenges, minimizing pollution. Besides the good aerodynamic efficiency needed, energy resource is now becoming important. The energy resource must have a good endurance, easy to get, and of course, less pollution. Discussion in this paper is about the analysis of power needed by HALE UAV while takeoff and cruise flight conditions, and then determine the amount of solar cell and battery needed by the UAV.

Implementation of an unmanned aerial vehicle for new generation Peterbilt trucks

NASA Astrophysics Data System (ADS)

Srinivasan K, Venkatesh

As science and technology continue to advance, innovative developments in transportation can enhance product safety and security for the benefit and welfare of society. The federal government requires every commercial truck to be inspected before each trip. This pre-trip inspection ensures the safe mechanical condition of each vehicle before it is used. An Unmanned Aerial Vehicle (UAV) could be used to provide an automated inspection, thus reducing driver workload, inspection costs and time while increasing inspection accuracy. This thesis develops a primary component of the algorithm that is required to implement UAV pre-trip inspections for commercial trucks using an android-based application. Specifically, this thesis provides foundational work of providing stable height control in an outdoor environment using a laser sensor and an android flight control application that includes take-off, landing, throttle control, and real-time video transmission. The height algorithm developed is the core of this thesis project. Phantom 2 Vision+ uses a pressure sensor to calculate the altitude of the drone for height stabilization. However, these altitude readings do not provide the precision required for this project. Rather, the goal of autonomously controlling height with great precision necessitated the use of a laser rangefinder sensor in the development of the height control algorithm. Another major contribution from this thesis research is to extend the limited capabilities of the DJI software development kit in order to provide more sophisticated control goals without modifying the drone dynamics. The results of this project are also directly applicable to a number of additional uses of drones in the transportation industry.

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

PubMed

Chang, Kai; Xia, Yuanqing; Huang, Kaoli

2016-01-01

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

3D Tree Dimensionality Assessment Using Photogrammetry and Small Unmanned Aerial Vehicles.

PubMed

Gatziolis, Demetrios; Lienard, Jean F; Vogs, Andre; Strigul, Nikolay S

2015-01-01

Detailed, precise, three-dimensional (3D) representations of individual trees are a prerequisite for an accurate assessment of tree competition, growth, and morphological plasticity. Until recently, our ability to measure the dimensionality, spatial arrangement, shape of trees, and shape of tree components with precision has been constrained by technological and logistical limitations and cost. Traditional methods of forest biometrics provide only partial measurements and are labor intensive. Active remote technologies such as LiDAR operated from airborne platforms provide only partial crown reconstructions. The use of terrestrial LiDAR is laborious, has portability limitations and high cost. In this work we capitalized on recent improvements in the capabilities and availability of small unmanned aerial vehicles (UAVs), light and inexpensive cameras, and developed an affordable method for obtaining precise and comprehensive 3D models of trees and small groups of trees. The method employs slow-moving UAVs that acquire images along predefined trajectories near and around targeted trees, and computer vision-based approaches that process the images to obtain detailed tree reconstructions. After we confirmed the potential of the methodology via simulation we evaluated several UAV platforms, strategies for image acquisition, and image processing algorithms. We present an original, step-by-step workflow which utilizes open source programs and original software. We anticipate that future development and applications of our method will improve our understanding of forest self-organization emerging from the competition among trees, and will lead to a refined generation of individual-tree-based forest models.

Chemiluminescent methods and instruments for monitoring of the atmosphere and satellite validation on board of research aircrafts and unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Sitnikov, Nikolay; Borisov, Yuriy; Akmulin, Dimitry; Chekulaev, Igor; Sitnikova, Vera; Ulanovsky, Alexey; Sokolov, Alexey

The results of development of instruments based on heterophase chemiluminescence for measurements of space distribution of ozone and nitrogen oxides concentrations on board of research aircrafts and unmanned aerial vehicles carried out in Central Aerological Observatory are presented. Some results of atmospheric investigations on board of research aircrafts M55 “Geophysica” (Russia) and “Falcon” (Germany) carried out using developed instruments in frame of international projects are demonstrated. Small and low power instruments based on chemiluminescent principle for UAV are developed. The results of measurements on board of UAV are shown. The development can be used for satellite data validation, as well as operative environmental monitoring of contaminated areas in particular, chemical plants, natural and industrial disasters territories, areas and facilities for space purposes etc.

UAV field demonstration of social media enabled tactical data link

NASA Astrophysics Data System (ADS)

Olson, Christopher C.; Xu, Da; Martin, Sean R.; Castelli, Jonathan C.; Newman, Andrew J.

2015-05-01

This paper addresses the problem of enabling Command and Control (C2) and data exfiltration functions for missions using small, unmanned, airborne surveillance and reconnaissance platforms. The authors demonstrated the feasibility of using existing commercial wireless networks as the data transmission infrastructure to support Unmanned Aerial Vehicle (UAV) autonomy functions such as transmission of commands, imagery, metadata, and multi-vehicle coordination messages. The authors developed and integrated a C2 Android application for ground users with a common smart phone, a C2 and data exfiltration Android application deployed on-board the UAVs, and a web server with database to disseminate the collected data to distributed users using standard web browsers. The authors performed a mission-relevant field test and demonstration in which operators commanded a UAV from an Android device to search and loiter; and remote users viewed imagery, video, and metadata via web server to identify and track a vehicle on the ground. Social media served as the tactical data link for all command messages, images, videos, and metadata during the field demonstration. Imagery, video, and metadata were transmitted from the UAV to the web server via multiple Twitter, Flickr, Facebook, YouTube, and similar media accounts. The web server reassembled images and video with corresponding metadata for distributed users. The UAV autopilot communicated with the on-board Android device via on-board Bluetooth network.

An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives

PubMed Central

Villa, Tommaso Francesco; Gonzalez, Felipe; Miljievic, Branka; Ristovski, Zoran D.; Morawska, Lidia

2016-01-01

Assessment of air quality has been traditionally conducted by ground based monitoring, and more recently by manned aircrafts and satellites. However, performing fast, comprehensive data collection near pollution sources is not always feasible due to the complexity of sites, moving sources or physical barriers. Small Unmanned Aerial Vehicles (UAVs) equipped with different sensors have been introduced for in-situ air quality monitoring, as they can offer new approaches and research opportunities in air pollution and emission monitoring, as well as for studying atmospheric trends, such as climate change, while ensuring urban and industrial air safety. The aims of this review were to: (1) compile information on the use of UAVs for air quality studies; and (2) assess their benefits and range of applications. An extensive literature review was conducted using three bibliographic databases (Scopus, Web of Knowledge, Google Scholar) and a total of 60 papers was found. This relatively small number of papers implies that the field is still in its early stages of development. We concluded that, while the potential of UAVs for air quality research has been established, several challenges still need to be addressed, including: the flight endurance, payload capacity, sensor dimensions/accuracy, and sensitivity. However, the challenges are not simply technological, in fact, policy and regulations, which differ between countries, represent the greatest challenge to facilitating the wider use of UAVs in atmospheric research. PMID:27420065

The Evaluation of GPS techniques for UAV-based Photogrammetry in Urban Area

NASA Astrophysics Data System (ADS)

Yeh, M. L.; Chou, Y. T.; Yang, L. S.

2016-06-01

The efficiency and high mobility of Unmanned Aerial Vehicle (UAV) made them essential to aerial photography assisted survey and mapping. Especially for urban land use and land cover, that they often changes, and need UAVs to obtain new terrain data and the new changes of land use. This study aims to collect image data and three dimensional ground control points in Taichung city area with Unmanned Aerial Vehicle (UAV), general camera and Real-Time Kinematic with positioning accuracy down to centimetre. The study area is an ecological park that has a low topography which support the city as a detention basin. A digital surface model was also built with Agisoft PhotoScan, and there will also be a high resolution orthophotos. There will be two conditions for this study, with or without ground control points and both were discussed and compared for the accuracy level of each of the digital surface models. According to check point deviation estimate, the model without ground control points has an average two-dimension error up to 40 centimeter, altitude error within one meter. The GCP-free RTK-airborne approach produces centimeter-level accuracy with excellent to low risk to the UAS operators. As in the case of the model with ground control points, the accuracy of x, y, z coordinates has gone up 54.62%, 49.07%, and 87.74%, and the accuracy of altitude has improved the most.

Design and development of a robust ATP subsystem for the Altair UAV-to-Ground lasercomm 2.5 Gbps demonstration

NASA Technical Reports Server (NTRS)

Ortiz, G. G.; Lee, S.; Monacos, S.; Wright, M.; Biswas, A.

2003-01-01

A robust acquisition, tracking and pointing (ATP) subsystem is being developed for the 2.5 Gigabit per second (Gbps) Unmanned-Aerial-Vehicle (UAV) to ground free-space optical communications link project.

The Design of the Longitudinal Autopilot for the LSU-05 Unmanned Aerial Surveillance Vehicle

NASA Astrophysics Data System (ADS)

Fajar, Muhammad; Arifianto, Ony

2018-04-01

Longitudinal autopilot design for the LAPAN Surveillance Vehicle LSU-05 will be described in this paper. The LSU-05 is the most recent Unmanned Aerial Vehicle (UAV) project of the Aeronautics Technology Center (Pusat Teknologi Penerbangan – Pustekbang), LAPAN. This UAV is expected to be able to carry 30 kg of payload, four surveillance purposes. The longitudinal autopilot described in this paper consists of four modes, those are Pitch damper, Pitch Attitude Hold, Altitude Hold, and Speed Hold. The Autopilot of the UAV will be designed at four operating speeds, namely 15 m/s, 20 m/s, 25 m/s, and 30 m/. The Athena Vortex Lattice software is used to generate the aerodynamic model of the LSU-05. Non-linear longitudinal aircraft dynamics model is then developed in MATLAB/SIMULINK environment. Linearization of the non-linear model is performed using the linearization tool of SIMULINK. The controller is designed, based on the linear model of the aircraft in the state space form. A Proportional-Integral-Derivative (PID) controller structure is chosen, using root locus method to determine mainly the proportional (P) gain. Integral (I) and derivative (D) gain will only be used if the proportional gain can not achieve the desired target or if an overshoot / undershoot reduction is required. The overshoot/undershoot should not exceed 5% and settling time is less than 20 seconds. The controller designed is simulated using MATLAB and SIMULINK. Preliminary analysis of the controller performance shows that the controller can be used to stabilize the aircraft and to automatize the speed and altitude control throughout the considered speed range.

Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV).

PubMed

Poblete, Tomas; Ortega-Farías, Samuel; Moreno, Miguel Angel; Bardeen, Matthew

2017-10-30

Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψ stem ). However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV) is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI) that use information between 500-800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN) models derived from multispectral images to predict the Ψ stem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R²) obtained between ANN outputs and ground-truth measurements of Ψ stem were between 0.56-0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψ stem with a mean absolute error (MAE) of 0.1 MPa, root mean square error (RMSE) of 0.12 MPa, and relative error (RE) of -9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26-0.27 MPa, 0.32-0.34 MPa and -24.2-25.6%, respectively.

Brief communication: Landslide motion from cross correlation of UAV-derived morphological attributes

NASA Astrophysics Data System (ADS)

Peppa, Maria V.; Mills, Jon P.; Moore, Phil; Miller, Pauline E.; Chambers, Jonathan E.

2017-12-01

Unmanned aerial vehicles (UAVs) can provide observations of high spatio-temporal resolution to enable operational landslide monitoring. In this research, the construction of digital elevation models (DEMs) and orthomosaics from UAV imagery is achieved using structure-from-motion (SfM) photogrammetric procedures. The study examines the additional value that the morphological attribute of openness, amongst others, can provide to surface deformation analysis. Image-cross-correlation functions and DEM subtraction techniques are applied to the SfM outputs. Through the proposed integrated analysis, the automated quantification of a landslide's motion over time is demonstrated, with implications for the wider interpretation of landslide kinematics via UAV surveys.

Cooperative Monocular-Based SLAM for Multi-UAV Systems in GPS-Denied Environments †

PubMed Central

Guerra, Edmundo

2018-01-01

This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation. PMID:29701722

Mapping Surface Temperatures on a Debris-Covered Glacier with an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Kraaijenbrink, Philip D. A.; Shea, Joseph M.; Litt, Maxime; Steiner, Jakob F.; Treichler, Désirée; Koch, Inka; Immerzeel, Walter W.

2018-05-01

A mantel of debris cover often accumulates across the surface of glaciers in active mountain ranges with exceptionally steep terrain, such as the Andes, Himalaya and New Zealand Alps. Such a supraglacial debris layer has a major influence on a glacier's surface energy budget, enhancing radiation absorption and melt when the layer is thin, but insulating the ice when thicker than a few cm. Information on spatially distributed debris surface temperature has the potential to provide insight into the properties of the debris, its effects on the ice below and its influence on the near-surface boundary layer. Here, we deploy an unmanned aerial vehicle (UAV) equipped with a thermal infrared sensor on three separate missions over one day to map changing surface temperatures across the debris-covered Lirung Glacier in the Central Himalaya. We present a methodology to georeference and process the acquired thermal imagery, and correct for emissivity and sensor bias. Derived UAV surface temperatures are compared with distributed simultaneous in situ temperature measurements as well as with Landsat 8 thermal satellite imagery. Results show that the UAV-derived surface temperatures vary greatly both spatially and temporally, with -1.4±1.8, 11.0 ±5.2 and 15.3±4.7 °C for the three flights (mean±sd), respectively. The range in surface temperatures over the glacier during the morning is very large with almost 50 °C. Ground-based measurements are generally in agreement with the UAV imagery, but considerable deviations are present that are likely due to differences in measurement technique and approach, and validation is difficult as a result. The difference in spatial and temporal variability captured by the UAV as compared with much coarser satellite imagery is striking and it shows that satellite derived temperature maps should be interpreted with care. We conclude that UAVs provide a suitable means to acquire surface temperature maps of debris-covered glacier surfaces at

Unmanned air vehicle (UAV) ultra-persitence research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dron, S. B.

2012-03-01

Sandia National Laboratories and Northrop Grumman Corporation Integrated Systems, Unmanned Systems (NGIS UMS) collaborated to further ultra-persistence technologies for unmanned air vehicles (UAVs). The greatest shortfalls in UAV capabilities have been repeatedly identified as (1) insufficient flight persistence or 'hang time,' (2) marginal electrical power for running higher power avionics and payload systems, and (3) inadequate communications bandwidth and reach. NGIS UMS requested support from Sandia to develop an ultra-persistent propulsion and power system (UP3S) for potential incorporation into next generation UAV systems. The team members tried to determine which energy storage and power generation concepts could most effectively pushmore » UAV propulsion and electrical power capabilities to increase UAV sortie duration from days to months while increasing available electrical power at least two-fold. Primary research and development areas that were pursued included these goals: perform general system engineering and integration analyses; develop initial thermal and electrical power estimates; provide mass, volume, dimensional, and balance estimates; conduct preliminary safety assessments; assess logistics support requirements; perform, preliminary assessments of any security and safeguards; evaluate options for removal, replacement, and disposition of materials; generally advance the potential of the UP3S concept. The effort contrasted and compared eight heat sources technologies, three power conversion, two dual cycle propulsion system configurations, and a single electrical power generation scheme. Overall performance, specific power parameters, technical complexities, security, safety, and other operational features were successfully investigated. Large and medium sized UAV systems were envisioned and operational flight profiles were developed for each concept. Heat source creation and support challenges for domestic and expeditionary operations were

Recording animal vocalizations from a UAV: bat echolocation during roost re-entry.

PubMed

Kloepper, Laura N; Kinniry, Morgan

2018-05-17

Unmanned aerial vehicles (UAVs) are rising in popularity for wildlife monitoring, but direct recordings of animal vocalizations have not yet been accomplished, likely due to the noise generated by the UAV. Echolocating bats, especially Tadarida brasiliensis, are good candidates for UAV recording due to their high-speed, high-altitude flight. Here, we use a UAV to record the signals of bats during morning roost re-entry. We designed a UAV to block the noise of the propellers from the receiving microphone, and report on the characteristics of bioacoustic recordings from a UAV. We report the first published characteristics of echolocation signals from bats during group flight and cave re-entry. We found changes in inter-individual time-frequency shape, suggesting that bats may use differences in call design when sensing in complex groups. Furthermore, our first documented successful recordings of animals in their natural habitat demonstrate that UAVs can be important tools for bioacoustic monitoring, and we discuss the ethical considerations for such monitoring.

UAV telemetry communications using ZigBee protocol

NASA Astrophysics Data System (ADS)

Nasution, T. H.; Siregar, I.; Yasir, M.

2017-10-01

Wireless communication has been widely used in various fields or disciplines such as agriculture, health, engineering, military, and aerospace so as to support the work in that field. The communication technology is typically used for controlling devices and data monitoring. One development of wireless communication is the widely used telemetry system used to reach areas that cannot be reached by humans using UAV (Unmanned Aerial Vehicle) or unmanned aircraft. In this paper we discuss the design of telemetry system in UAV using ZigBee protocol. From the test obtained the system can work well with visualization displays without pause is 20 data per second with a maximum data length of 120 characters.

A proposed UAV for indoor patient care.

PubMed

Todd, Catherine; Watfa, Mohamed; El Mouden, Yassine; Sahir, Sana; Ali, Afrah; Niavarani, Ali; Lutfi, Aoun; Copiaco, Abigail; Agarwal, Vaibhavi; Afsari, Kiyan; Johnathon, Chris; Okafor, Onyeka; Ayad, Marina

2015-09-10

Indoor flight, obstacle avoidance and client-server communication of an Unmanned Aerial Vehicle (UAV) raises several unique research challenges. This paper examines current methods and associated technologies adapted within the literature toward autonomous UAV flight, for consideration in a proposed system for indoor healthcare administration with a quadcopter. We introduce Healthbuddy, a unique research initiative towards overcoming challenges associated with indoor navigation, collision detection and avoidance, stability, wireless drone-server communications and automated decision support for patient care in a GPS-denied environment. To address the identified research deficits, a drone-based solution is presented. The solution is preliminary as we develop and refine the suggested algorithms and hardware system to achieve the research objectives.

Obstacle Detection and Avoidance System Based on Monocular Camera and Size Expansion Algorithm for UAVs

PubMed Central

Al-Kaff, Abdulla; García, Fernando; Martín, David; De La Escalera, Arturo; Armingol, José María

2017-01-01

One of the most challenging problems in the domain of autonomous aerial vehicles is the designing of a robust real-time obstacle detection and avoidance system. This problem is complex, especially for the micro and small aerial vehicles, that is due to the Size, Weight and Power (SWaP) constraints. Therefore, using lightweight sensors (i.e., Digital camera) can be the best choice comparing with other sensors; such as laser or radar.For real-time applications, different works are based on stereo cameras in order to obtain a 3D model of the obstacles, or to estimate their depth. Instead, in this paper, a method that mimics the human behavior of detecting the collision state of the approaching obstacles using monocular camera is proposed. The key of the proposed algorithm is to analyze the size changes of the detected feature points, combined with the expansion ratios of the convex hull constructed around the detected feature points from consecutive frames. During the Aerial Vehicle (UAV) motion, the detection algorithm estimates the changes in the size of the area of the approaching obstacles. First, the method detects the feature points of the obstacles, then extracts the obstacles that have the probability of getting close toward the UAV. Secondly, by comparing the area ratio of the obstacle and the position of the UAV, the method decides if the detected obstacle may cause a collision. Finally, by estimating the obstacle 2D position in the image and combining with the tracked waypoints, the UAV performs the avoidance maneuver. The proposed algorithm was evaluated by performing real indoor and outdoor flights, and the obtained results show the accuracy of the proposed algorithm compared with other related works. PMID:28481277

Atmospheric radiation measurement unmanned aerospace vehicle (ARM-UAV) program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolton, W.R.

1996-11-01

ARM-UAV is part of the multi-agency U.S. Global Change Research Program and is addressing the largest source of uncertainty in predicting climatic response: the interaction of clouds and the sun`s energy in the Earth`s atmosphere. An important aspect of the program is the use of unmanned aerospace vehicles (UAVs) as the primary airborne platform. The ARM-UAV Program has completed two major flight series: The first series conducted in April, 1994, using an existing UAV (the General Atomics Gnat 750) consisted of eight highly successful flights at the DOE climate site in Oklahoma. The second series conducted in September/October, 1995, usingmore » two piloted aircraft (Egrett and Twin Otter), featured simultaneous measurements above and below clouds and in clear sky. Additional flight series are planned to continue study of the cloudy and clear sky energy budget in the Spring and Fall of 1996 over the DOE climate site in Oklahoma. 3 refs., 4 figs., 1 tab.« less

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs.

PubMed

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E; Hernandez, Carmen; Dalmau, Oscar

2017-06-16

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow.

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images

PubMed Central

Ortega-Terol, Damian; Ballesteros, Rocio

2017-01-01

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology. PMID:29036930

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

PubMed

Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

2017-10-15

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

Applications of UAVs in row-crop agriculture: advantages and limitations

NASA Astrophysics Data System (ADS)

Basso, B.; Putnam, G.; Price, R.; Zhang, J.

2016-12-01

The application of Unmanned Aerial Vehicles (UAV) to monitor agricultural fields has increased over the last few years due to advances in the technology, sensors, post-processing software for image analysis, along with more favorable regulations that allowed UAVs to be flown for commercial use. UAV have several capabilities depending on the type of sensors that are mounted onboard. The most widely used application remains crop scouting to identify areas within fields where the crops underperform for various reasons (nutritional status and water stress, presence of weeds, poor stands etc). In this talk, we present the preliminary results of UAVs field based research to better understand spatial and temporal variability of crop yield. Their advantage in providing timely information is critical, but adaptive management requires a system approach to account for the interactions occurring between genetics, environment and management.

Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Knox, Lenora A.

The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.

Surveying a Landslide in a Road Embankment Using Unmanned Aerial Vehicle Photogrammetry

NASA Astrophysics Data System (ADS)

Carvajal, F.; Agüera, F.; Pérez, M.

2011-09-01

Most of the works of civil engineering, and some others applications, need to be designed using a basic cartography with a suitable scale to the accuracy and extension of the plot.The Unmanned Aerial Vehicle (UAV) Photogrammetry covers the gap between classical manned aerial photogrammetry and hand- made surveying techniques because it works in the close-range domain, combining aerial and terrestrial photogrammetry, but also introduces low-cost alternatives. The aim of this work is developing of an accurate and low-cost method to characterize landslides located on the size of a road. It was applied at the kilometric point 339 belonging to the A92 dual carriageway, in the Abla municipal term, province of Almeria, Spain. A photogrammetric project was carried out from a set of images taken from an md4-200 Microdrones with an on-board calibrated camera 12 Megapixels Pentax Optio A40. The flight was previously planned to cover the whole extension of the embankment with three passes composed of 18 photos each one. All the images were taken with the vertical axe and it was registered 85% and 60% longitudinal and transversal overlaps respectively. The accuracy of the products, with planimetric and altimetric errors of 0.049 and 0.108m repectively, lets to take measurements of the landslide and projecting preventive and palliative actuations.

The NASA Dryden Flight Test Approach to an Aerial Refueling System

NASA Technical Reports Server (NTRS)

Hansen, Jennifer L.; Murray, James E.; Campos, Norma V.

2005-01-01

The integration of uninhabited aerial vehicles (UAVs) into controlled airspace has generated a new era of autonomous technologies and challenges. Autonomous aerial refueling would enable UAVs to travel further distances and loiter for extended periods over time-critical targets. The NASA Dryden Flight Research Center recently has completed a flight research project directed at developing a dynamic hose and drogue system model to support the development of an automated aerial refueling system. A systematic dynamic model of the hose and drogue system would include the effects of various influences on the system, such as flight condition, hose and drogue type, tanker type and weight, receiver type, and tanker and receiver maneuvering. Using two NASA F/A-18 aircraft and a conventional hose and drogue aerial refueling store from the Navy, NASA has obtained flight research data that document the response of the hose and drogue system to these effects. Preliminary results, salient trends, and important lessons are presented

Implementation and Testing of Low Cost Uav Platform for Orthophoto Imaging

NASA Astrophysics Data System (ADS)

Brucas, D.; Suziedelyte-Visockiene, J.; Ragauskas, U.; Berteska, E.; Rudinskas, D.

2013-08-01

Implementation of Unmanned Aerial Vehicles for civilian applications is rapidly increasing. Technologies which were expensive and available only for military use have recently spread on civilian market. There is a vast number of low cost open source components and systems for implementation on UAVs available. Using of low cost hobby and open source components ensures considerable decrease of UAV price, though in some cases compromising its reliability. In Space Science and Technology Institute (SSTI) in collaboration with Vilnius Gediminas Technical University (VGTU) researches have been performed in field of constructing and implementation of small UAVs composed of low cost open source components (and own developments). Most obvious and simple implementation of such UAVs - orthophoto imaging with data download and processing after the flight. The construction, implementation of UAVs, flight experience, data processing and data implementation will be further covered in the paper and presentation.

Evaluation of unmanned aerial vehicles (UAVs) for detection of cattle in the Cattle Fever Tick Permanent Quarantine Zone

USDA-ARS?s Scientific Manuscript database

An unmanned aerial vehicle was used to capture videos of cattle in pastures to determine the efficiency of this technology for use by Mounted Inspectors in the Permanent Quarantine zone (PQZ) of the Cattle Fever Tick Eradication Program in south Texas along the U.S.-Mexico Border. These videos were ...

Cloud Water Content Sensor for Sounding Balloons and Small UAVs

NASA Technical Reports Server (NTRS)

Bognar, John A.

2009-01-01

A lightweight, battery-powered sensor was developed for measuring cloud water content, which is the amount of liquid or solid water present in a cloud, generally expressed as grams of water per cubic meter. This sensor has near-zero power consumption and can be flown on standard sounding balloons and small, unmanned aerial vehicles (UAVs). The amount of solid or liquid water is important to the study of atmospheric processes and behavior. Previous sensing techniques relied on strongly heating the incoming air, which requires a major energy input that cannot be achieved on sounding balloons or small UAVs.

High-Fidelity Computational Aerodynamics of the Elytron 4S UAV

NASA Technical Reports Server (NTRS)

Ventura Diaz, Patricia; Yoon, Seokkwan; Theodore, Colin R.

2018-01-01

High-fidelity Computational Fluid Dynamics (CFD) have been carried out for the Elytron 4S Unmanned Aerial Vehicle (UAV), also known as the converticopter "proto12". It is the scaled wind tunnel model of the Elytron 4S, an Urban Air Mobility (UAM) concept, a tilt-wing, box-wing rotorcraft capable of Vertical Take-Off and Landing (VTOL). The three-dimensional unsteady Navier-Stokes equations are solved on overset grids employing high-order accurate schemes, dual-time stepping, and a hybrid turbulence model using NASA's CFD code OVERFLOW. The Elytron 4S UAV has been simulated in airplane mode and in helicopter mode.

Monitoring landslide dynamics using timeseries of UAV imagery

NASA Astrophysics Data System (ADS)

de Jong, S. M.; Van Beek, L. P.

2017-12-01

Landslides are worldwide occurring processes that can have large economic impact and sometimes result in fatalities. Multiple factors are important in landslide processes and can make an area prone to landslide activity. Human factors like drainage and removal of vegetation or land clearing are examples of factors that may cause a landslide. Other environmental factors such as topography and the shear strength of the slope material are more difficult to control. Triggering factors for landslides are typically heavy rainfall events or sometimes by earthquakes or under cutting processes by a river. The collection of data about existing landslides in a given area is important for predicting future landslides in that region. We have setup a monitoring program for landslide using cameras aboard Unmanned Airborne Vehicles. UAV with cameras are able to collect ultra-high resolution images and UAVs can be operated in a very flexible way, they just fit in the back of a car. Here, in this study we used Unmanned Aerial Vehicles to collect a time series of high-resolution images over landslides in France and Australia. The algorithm used to process the UAV images into OrthoMosaics and OrthoDEMs is Structure from Motion (SfM). The process generally results in centimeter precision in the horizontal and vertical direction. Such multi-temporal datasets enable the detection of landslide area, the leading edge slope, temporal patterns and volumetric changes of particular areas of the landslide. We measured and computed surface movement of the landslide using the COSI-Corr image correlation algorithm with ground validation. Our study shows the possibilities of generating accurate Digital Surface Models (DSMs) of landslides using images collected with an Unmanned Aerial Vehicle (UAV). The technique is robust and repeatable such that a substantial time series of datasets can be routinely collected. It is shown that a time-series of UAV images can be used to map landslide movements with

Active landslide monitoring using remote sensing data, GPS measurements and cameras on board UAV

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Kavoura, Katerina; Depountis, Nikolaos; Argyropoulos, Nikolaos; Koukouvelas, Ioannis; Sabatakakis, Nikolaos

2015-10-01

An active landslide can be monitored using many different methods: Classical geotechnical measurements like inclinometer, topographical survey measurements with total stations or GPS and photogrammetric techniques using airphotos or high resolution satellite images. As the cost of the aerial photo campaign and the acquisition of very high resolution satellite data is quite expensive the use of cameras on board UAV could be an identical solution. Small UAVs (Unmanned Aerial Vehicles) have started their development as expensive toys but they currently became a very valuable tool in remote sensing monitoring of small areas. The purpose of this work is to demonstrate a cheap but effective solution for an active landslide monitoring. We present the first experimental results of the synergistic use of UAV, GPS measurements and remote sensing data. A six-rotor aircraft with a total weight of 6 kg carrying two small cameras has been used. Very accurate digital airphotos, high accuracy DSM, DGPS measurements and the data captured from the UAV are combined and the results are presented in the current study.

On a Fundamental Evaluation of a Uav Equipped with a Multichannel Laser Scanner

NASA Astrophysics Data System (ADS)

Nakano, K.; Suzuki, H.; Omori, K.; Hayakawa, K.; Kurodai, M.

2018-05-01

Unmanned aerial vehicles (UAVs), which have been widely used in various fields such as archaeology, agriculture, mining, and construction, can acquire high-resolution images at the millimetre scale. It is possible to obtain realistic 3D models using high-overlap images and 3D reconstruction software based on computer vision technologies such as Structure from Motion and Multi-view Stereo. However, it remains difficult to obtain key points from surfaces with limited texture such as new asphalt or concrete, or from areas like forests that may be concealed by vegetation. A promising method for conducting aerial surveys is through the use of UAVs equipped with laser scanners. We conducted a fundamental performance evaluation of the Velodyne VLP-16 multi-channel laser scanner equipped to a DJI Matrice 600 Pro UAV at a construction site. Here, we present our findings with respect to both the geometric and radiometric aspects of the acquired data.

Comparison of Unmanned Aerial Vehicle Platforms for Assessing Vegetation Cover in Sagebrush Steppe Ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert P. Breckenridge; Maxine Dakins; Stephen Bunting

2011-09-01

In this study, the use of unmanned aerial vehicles (UAVs) as a quick and safe method for monitoring biotic resources was evaluated. Vegetation cover and the amount of bare ground are important factors in understanding the sustainability of many ecosystems and assessment of rangeland health. Methods that improve speed and cost efficiency could greatly improve how biotic resources are monitored on western lands. Sagebrush steppe ecosystems provide important habitat for a variety of species (including sage grouse and pygmy rabbit). Improved methods are needed to support monitoring these habitats because there are not enough resource specialists or funds available formore » comprehensive ground evaluations. In this project, two UAV platforms, fixed wing and helicopter, were used to collect still-frame imagery to assess vegetation cover in sagebrush steppe ecosystems. This paper discusses the process for collecting and analyzing imagery from the UAVs to (1) estimate percent cover for six different vegetation types (shrub, dead shrub, grass, forb, litter, and bare ground) and (2) locate sage grouse using representative decoys. The field plots were located on the Idaho National Engineering (INL) site west of Idaho Falls, Idaho, in areas with varying amounts and types of vegetation cover. A software program called SamplePoint was used along with visual inspection to evaluate percent cover for the six cover types. Results were compared against standard field measurements to assess accuracy. The comparison of fixed-wing and helicopter UAV technology against field estimates shows good agreement for the measurement of bare ground. This study shows that if a high degree of detail and data accuracy is desired, then a helicopter UAV may be a good platform to use. If the data collection objective is to assess broad-scale landscape level changes, then the collection of imagery with a fixed-wing system is probably more appropriate.« less

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

PubMed Central

Nitti, Davide O.; Bovenga, Fabio; Chiaradia, Maria T.; Greco, Mario; Pinelli, Gianpaolo

2015-01-01

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimate UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system. PMID:26225977

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

PubMed

Nitti, Davide O; Bovenga, Fabio; Chiaradia, Maria T; Greco, Mario; Pinelli, Gianpaolo

2015-07-28

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

A Mobile System for Measuring Water Surface Velocities Using Unmanned Aerial Vehicle and Large-Scale Particle Image Velocimetry

NASA Astrophysics Data System (ADS)

Chen, Y. L.

2015-12-01

Measurement technologies for velocity of river flow are divided into intrusive and nonintrusive methods. Intrusive method requires infield operations. The measuring process of intrusive methods are time consuming, and likely to cause damages of operator and instrument. Nonintrusive methods require fewer operators and can reduce instrument damages from directly attaching to the flow. Nonintrusive measurements may use radar or image velocimetry to measure the velocities at the surface of water flow. The image velocimetry, such as large scale particle image velocimetry (LSPIV) accesses not only the point velocity but the flow velocities in an area simultaneously. Flow properties of an area hold the promise of providing spatially information of flow fields. This study attempts to construct a mobile system UAV-LSPIV by using an unmanned aerial vehicle (UAV) with LSPIV to measure flows in fields. The mobile system consists of a six-rotor UAV helicopter, a Sony nex5T camera, a gimbal, an image transfer device, a ground station and a remote control device. The activate gimbal helps maintain the camera lens orthogonal to the water surface and reduce the extent of images being distorted. The image transfer device can monitor the captured image instantly. The operator controls the UAV by remote control device through ground station and can achieve the flying data such as flying height and GPS coordinate of UAV. The mobile system was then applied to field experiments. The deviation of velocities measured by UAV-LSPIV of field experiments and handhold Acoustic Doppler Velocimeter (ADV) is under 8%. The results of the field experiments suggests that the application of UAV-LSPIV can be effectively applied to surface flow studies.

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.

PubMed

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-07-17

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system.