Cooperative remote sensing and actuation using networked unmanned vehicles

NASA Astrophysics Data System (ADS)

Chao, Haiyang

This dissertation focuses on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes in the current information-rich world. The target scenarios are environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks, etc. AggieAir, a small and low-cost unmanned aircraft system, is designed based on the remote sensing requirements from environmental monitoring missions. The state estimation problem and the advanced lateral flight controller design problem are further attacked focusing on the small unmanned aerial vehicle (UAV) platform. Then the UAV-based remote sensing problem is focused with further flight test results. Given the measurements from unmanned vehicles, the actuation algorithms are needed for missions like the diffusion control. A consensus-based central Voronoi tessellation (CVT) algorithm is proposed for better control of the diffusion process. Finally, the dissertation conclusion and some new research suggestions are presented.

Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

NASA Astrophysics Data System (ADS)

Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

2017-12-01

In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four

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.

Detection of MAVs (Micro Aerial Vehicles) based on millimeter wave radar

NASA Astrophysics Data System (ADS)

Noetel, Denis; Johannes, Winfried; Caris, Michael; Hommes, Alexander; Stanko, Stephan

2016-10-01

In this paper we present two system approaches for perimeter surveillance with radar techniques focused on the detection of Micro Aerial Vehicles (MAVs). The main task of such radars is to detect movements of targets such as an individual or a vehicle approaching a facility. The systems typically cover a range of several hundred meters up to several kilometers. In particular, the capability of identifying Remotely Piloted Aircraft Systems (RPAS), which pose a growing threat on critical infrastructure areas, is of great importance nowadays. The low costs, the ease of handling and a considerable payload make them an excellent tool for unwanted surveillance or attacks. Most platforms can be equipped with all kind of sensors or, in the worst case, with destructive devices. A typical MAV is able to take off and land vertically, to hover, and in many cases to fly forward at high speed. Thus, it can reach all kinds of places in short time while the concealed operator of the MAV resides at a remote and riskless place.

Unmanned aerial systems for photogrammetry and remote sensing: A review

NASA Astrophysics Data System (ADS)

Colomina, I.; Molina, P.

2014-06-01

We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.

Vehicle detection in aerial surveillance using dynamic Bayesian networks.

PubMed

Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

2012-04-01

We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

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...

Remotely deployable aerial inspection using tactile sensors

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

MacLeod, C. N.; Cao, J.; Pierce, S. G.

For structural monitoring applications, the use of remotely deployable Non-Destructive Evaluation (NDE) inspection platforms offer many advantages, including improved accessibility, greater safety and reduced cost, when compared to traditional manual inspection techniques. The use of such platforms, previously reported by researchers at the University Strathclyde facilitates the potential for rapid scanning of large areas and volumes in hazardous locations. A common problem for both manual and remote deployment approaches lies in the intrinsic stand-off and surface coupling issues of typical NDE probes. The associated complications of these requirements are obviously significantly exacerbated when considering aerial based remote inspection and deployment,more » resulting in simple visual techniques being the preferred sensor payload. Researchers at Bristol Robotics Laboratory have developed biomimetic tactile sensors modelled on the facial whiskers (vibrissae) of animals such as rats and mice, with the latest sensors actively sweeping their tips across the surface in a back and forth motion. The current work reports on the design and performance of an aerial inspection platform and the suitability of tactile whisking sensors to aerial based surface monitoring applications.« less

Unmanned Aerial Vehicle (UAV) associated DTM quality evaluation and hazard assessment

NASA Astrophysics Data System (ADS)

Huang, Mei-Jen; Chen, Shao-Der; Chao, Yu-Jui; Chiang, Yi-Lin; Chang, Kuo-Jen

2014-05-01

Taiwan, due to the high seismicity and high annual rainfall, numerous landslides triggered every year and severe impacts affect the island. Concerning to the catastrophic landslides, the key information of landslide, including range of landslide, volume estimation and the subsequent evolution are important when analyzing the triggering mechanism, hazard assessment and mitigation. Thus, the morphological analysis gives a general overview for the landslides and been considered as one of the most fundamental information. We try to integrate several technologies, especially by Unmanned Aerial Vehicle (UAV) and multi-spectral camera, to decipher the consequence and the potential hazard, and the social impact. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious information. Benefited of the advancing of informatics, remote-sensing and electric technologies, the Unmanned Aerial Vehicle (UAV) photogrammetry mas been improve significantly. The study tries to integrate several methods, including, 1) Remote-sensing images gathered by Unmanned Aerial Vehicle (UAV) and by aerial photos taken in different periods; 2) field in-situ geologic investigation; 3) Differential GPS, RTK GPS and Ground LiDAR field in-site geoinfomatics measurements; 4) Construct the DTMs before and after landslide, as well as the subsequent periods using UAV and aerial photos; 5) Discrete element method should be applied to understand the geomaterial composing the slope failure, for predicting earthquake-induced and rainfall-induced landslides displacement. First at all, we evaluate the Microdrones MD4-1000 UAV airphotos derived Digital Terrain Model (DTM). The ground resolution of the DSM point cloud of could be as high as 10 cm. By integrated 4 ground control point within an area of 56 hectares, compared with LiDAR DSM and filed RTK-GPS surveying, the mean error is as low as 6cm with a standard deviation of 17cm. The quality of the

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.

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

Vision-Based Corrosion Detection Assisted by a Micro-Aerial Vehicle in a Vessel Inspection Application.

PubMed

Ortiz, Alberto; Bonnin-Pascual, Francisco; Garcia-Fidalgo, Emilio; Company-Corcoles, Joan P

2016-12-14

Vessel maintenance requires periodic visual inspection of the hull in order to detect typical defective situations of steel structures such as, among others, coating breakdown and corrosion. These inspections are typically performed by well-trained surveyors at great cost because of the need for providing access means (e.g., scaffolding and/or cherry pickers) that allow the inspector to be at arm's reach from the structure under inspection. This paper describes a defect detection approach comprising a micro-aerial vehicle which is used to collect images from the surfaces under inspection, particularly focusing on remote areas where the surveyor has no visual access, and a coating breakdown/corrosion detector based on a three-layer feed-forward artificial neural network. As it is discussed in the paper, the success of the inspection process depends not only on the defect detection software but also on a number of assistance functions provided by the control architecture of the aerial platform, whose aim is to improve picture quality. Both aspects of the work are described along the different sections of the paper, as well as the classification performance attained.

Vision-Based Corrosion Detection Assisted by a Micro-Aerial Vehicle in a Vessel Inspection Application

PubMed Central

Ortiz, Alberto; Bonnin-Pascual, Francisco; Garcia-Fidalgo, Emilio; Company-Corcoles, Joan P.

2016-01-01

Vessel maintenance requires periodic visual inspection of the hull in order to detect typical defective situations of steel structures such as, among others, coating breakdown and corrosion. These inspections are typically performed by well-trained surveyors at great cost because of the need for providing access means (e.g., scaffolding and/or cherry pickers) that allow the inspector to be at arm’s reach from the structure under inspection. This paper describes a defect detection approach comprising a micro-aerial vehicle which is used to collect images from the surfaces under inspection, particularly focusing on remote areas where the surveyor has no visual access, and a coating breakdown/corrosion detector based on a three-layer feed-forward artificial neural network. As it is discussed in the paper, the success of the inspection process depends not only on the defect detection software but also on a number of assistance functions provided by the control architecture of the aerial platform, whose aim is to improve picture quality. Both aspects of the work are described along the different sections of the paper, as well as the classification performance attained. PMID:27983627

Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance

DTIC Science & Technology

2007-03-31

IFinal 03/01/04 - 02/28/07 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Neuromorphic VLSI-based Bat Echolocation for Micro-aerial 5b.GRANTNUMBER Vehicle...uncovered interesting new issues in our choice for representing the intensity of signals. We have just finished testing the first chip version of an echo...timing-based algorithm (’openspace’) for sonar-guided navigation amidst multiple obstacles. 15. SUBJECT TERMS Neuromorphic VLSI, bat echolocation

Mapping of Rill Erosion of Arable Soils Based on Unmanned Aerial Vehicles Survey

NASA Astrophysics Data System (ADS)

Kashtanov, A. N.; Vernyuk, Yu. I.; Savin, I. Yu.; Shchepot'ev, V. V.; Dokukin, P. A.; Sharychev, D. V.; Li, K. A.

2018-04-01

Possibilities of using data obtained from unmanned aerial vehicles for detection and mapping of rill erosion on arable lands are analyzed. Identification and mapping of rill erosion was performed on a key plot with a predominance of arable gray forest soils (Greyzemic Phaeozems) under winter wheat in Tula oblast. This plot was surveyed from different heights and in different periods to determine the reliability of identification of rill erosion on the basis of automated procedures in a GIS. It was found that, despite changes in the pattern of rills during the warm season, only one survey during this season is sufficient for adequate assessment of the area of eroded soils. According to our data, the most reliable identification of rill erosion is based on the aerial survey from the height of 50 m above the soil surface. When the height of the flight is more than 200 m, erosional rills virtually escape identification. The efficiency of identification depends on the type of crops, their status, and time of the survey. The surveys of bare soil surface in periods with maximum possible interval from the previous rain or snowmelt season are most efficient. The results of our study can be used in the systems of remote sensing monitoring of erosional processes on arable fields. Application of multiand hyperspectral cameras can improve the efficiency of monitoring.

Remote Estimation of Vegetation Fraction and Yield in Oilseed Rape with Unmanned Aerial Vehicle Data

NASA Astrophysics Data System (ADS)

Peng, Y.; Fang, S.; Liu, K.; Gong, Y.

2017-12-01

This study developed an approach for remote estimation of Vegetation Fraction (VF) and yield in oilseed rape, which is a crop species with conspicuous flowers during reproduction. Canopy reflectance in green, red, red edge and NIR bands was obtained by a camera system mounted on an unmanned aerial vehicle (UAV) when oilseed rape was in the vegetative growth and flowering stage. The relationship of several widely-used Vegetation Indices (VI) vs. VF was tested and found to be different in different phenology stages. At the same VF when oilseed rape was flowering, canopy reflectance increased in all bands, and the tested VI decreased. Therefore, two algorithms to estimate VF were calibrated respectively, one for samples during vegetative growth and the other for samples during flowering stage. During the flowering season, we also explored the potential of using canopy reflectance or VIs to estimate Flower Fraction (FF) in oilseed rape. Based on FF estimates, rape yield can be estimated using canopy reflectance data. Our model was validated in oilseed rape planted under different nitrogen fertilization applications and in different phenology stages. The results showed that it was able to predict VF and FF accurately in oilseed rape with estimation error below 6% and predict yield with estimation error below 20%.

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.

MEMS Based Micro Aerial Vehicles

NASA Astrophysics Data System (ADS)

Joshi, Niranjan; Köhler, Elof; Enoksson, Peter

2016-10-01

Designing a flapping wing insect robot requires understanding of insect flight mechanisms, wing kinematics and aerodynamic forces. These subsystems are interconnected and their dependence on one another affects the overall performance. Additionally it requires an artificial muscle like actuator and transmission to power the wings. Several kinds of actuators and mechanisms are candidates for this application with their own strengths and weaknesses. This article provides an overview of the insect scaled flight mechanism along with discussion of various methods to achieve the Micro Aerial Vehicle (MAV) flight. Ongoing projects in Chalmers is aimed at developing a low cost and low manufacturing time MAV. The MAV design considerations and design specifications are mentioned. The wings are manufactured using 3D printed carbon fiber and are under experimental study.

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

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.

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.

Cooperative Surveillance and Pursuit Using Unmanned Aerial Vehicles and Unattended Ground Sensors

PubMed Central

Las Fargeas, Jonathan; Kabamba, Pierre; Girard, Anouck

2015-01-01

This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles' paths nominally. The algorithm uses detections from the sensors to predict intruders' locations and selects the vehicles' paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm's completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios. PMID:25591168

Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Shin, Yoonghyun; Calise, Anthony J.; Motter, Mark A.

2005-01-01

This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.

Nocturnal Visual Orientation in Flying Insects: A Benchmark for the Design of Vision-Based Sensors in Micro-Aerial Vehicles

DTIC Science & Technology

2011-03-09

anu.edu.au Nocturnal visual orientation in flying insects: a benchmark for the design of vision-based sensors in Micro-Aerial Vehicles Report...9 10 Technical horizon sensors Over the past few years, a remarkable proliferation of designs for micro-aerial vehicles (MAVs) has occurred...possible elevations, it may severely degrade the performance of sensors by local saturation. Therefore it is necessary to find a method whereby the effect

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

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

Person identification from aerial footage by a remote-controlled drone.

PubMed

Bindemann, Markus; Fysh, Matthew C; Sage, Sophie S K; Douglas, Kristina; Tummon, Hannah M

2017-10-19

Remote-controlled aerial drones (or unmanned aerial vehicles; UAVs) are employed for surveillance by the military and police, which suggests that drone-captured footage might provide sufficient information for person identification. This study demonstrates that person identification from drone-captured images is poor when targets are unfamiliar (Experiment 1), when targets are familiar and the number of possible identities is restricted by context (Experiment 2), and when moving footage is employed (Experiment 3). Person information such as sex, race and age is also difficult to access from drone-captured footage (Experiment 4). These findings suggest that such footage provides a particularly poor medium for person identification. This is likely to reflect the sub-optimal quality of such footage, which is subject to factors such as the height and velocity at which drones fly, viewing distance, unfavourable vantage points, and ambient conditions.

A Primer on Autonomous Aerial Vehicle Design

PubMed Central

Coppejans, Hugo H. G.; Myburgh, Herman C.

2015-01-01

There is a large amount of research currently being done on autonomous micro-aerial vehicles (MAV), such as quadrotor helicopters or quadcopters. The ability to create a working autonomous MAV depends mainly on integrating a simultaneous localization and mapping (SLAM) solution with the rest of the system. This paper provides an introduction for creating an autonomous MAV for enclosed environments, aimed at students and professionals alike. The standard autonomous system and MAV automation are discussed, while we focus on the core concepts of SLAM systems and trajectory planning algorithms. The advantages and disadvantages of using remote processing are evaluated, and recommendations are made regarding the viability of on-board processing. Recommendations are made regarding best practices to serve as a guideline for aspirant MAV designers. PMID:26633410

A Primer on Autonomous Aerial Vehicle Design.

PubMed

Coppejans, Hugo H G; Myburgh, Herman C

2015-12-02

There is a large amount of research currently being done on autonomous micro-aerial vehicles (MAV), such as quadrotor helicopters or quadcopters. The ability to create a working autonomous MAV depends mainly on integrating a simultaneous localization and mapping (SLAM) solution with the rest of the system. This paper provides an introduction for creating an autonomous MAV for enclosed environments, aimed at students and professionals alike. The standard autonomous system and MAV automation are discussed, while we focus on the core concepts of SLAM systems and trajectory planning algorithms. The advantages and disadvantages of using remote processing are evaluated, and recommendations are made regarding the viability of on-board processing. Recommendations are made regarding best practices to serve as a guideline for aspirant MAV designers.

US Army remotely piloted vehicle supporting technology program

NASA Technical Reports Server (NTRS)

Gossett, T. D.

1981-01-01

Essential technology programs that lead to the full scale engineering development of the Aquila Remotely Piloted Vehicle system for U.S. Army are described. The Aquila system uses a small recoverable and reusable RPV to provide target acquisition, designation, and aerial reconnaissance mission support for artillery and smart munitions. Developments that will provide growth capabilities to the Aquila RPV system, as well as future RPV mission concepts being considered by the U.S. Army are presented.

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

Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

NASA Astrophysics Data System (ADS)

Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

2017-12-01

Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

Development of sea ice monitoring with aerial remote sensing technology

NASA Astrophysics Data System (ADS)

Jiang, Xuhui; Han, Lei; Dong, Liang; Cui, Lulu; Bie, Jun; Fan, Xuewei

2014-11-01

In the north China Sea district, sea ice disaster is very serious every winter, which brings a lot of adverse effects to shipping transportation, offshore oil exploitation, and coastal engineering. In recent years, along with the changing of global climate, the sea ice situation becomes too critical. The monitoring of sea ice is playing a very important role in keeping human life and properties in safety, and undertaking of marine scientific research. The methods to monitor sea ice mainly include: first, shore observation; second, icebreaker monitoring; third, satellite remote sensing; and then aerial remote sensing monitoring. The marine station staffs use relevant equipments to monitor the sea ice in the shore observation. The icebreaker monitoring means: the workers complete the test of the properties of sea ice, such as density, salinity and mechanical properties. MODIS data and NOAA data are processed to get sea ice charts in the satellite remote sensing means. Besides, artificial visual monitoring method and some airborne remote sensors are adopted in the aerial remote sensing to monitor sea ice. Aerial remote sensing is an important means in sea ice monitoring because of its strong maneuverability, wide watching scale, and high resolution. In this paper, several methods in the sea ice monitoring using aerial remote sensing technology are discussed.

Vehicle Detection of Aerial Image Using TV-L1 Texture Decomposition

NASA Astrophysics Data System (ADS)

Wang, Y.; Wang, G.; Li, Y.; Huang, Y.

2016-06-01

Vehicle detection from high-resolution aerial image facilitates the study of the public traveling behavior on a large scale. In the context of road, a simple and effective algorithm is proposed to extract the texture-salient vehicle among the pavement surface. Texturally speaking, the majority of pavement surface changes a little except for the neighborhood of vehicles and edges. Within a certain distance away from the given vector of the road network, the aerial image is decomposed into a smoothly-varying cartoon part and an oscillatory details of textural part. The variational model of Total Variation regularization term and L1 fidelity term (TV-L1) is adopted to obtain the salient texture of vehicles and the cartoon surface of pavement. To eliminate the noise of texture decomposition, regions of pavement surface are refined by seed growing and morphological operation. Based on the shape saliency analysis of the central objects in those regions, vehicles are detected as the objects of rectangular shape saliency. The proposed algorithm is tested with a diverse set of aerial images that are acquired at various resolution and scenarios around China. Experimental results demonstrate that the proposed algorithm can detect vehicles at the rate of 71.5% and the false alarm rate of 21.5%, and that the speed is 39.13 seconds for a 4656 x 3496 aerial image. It is promising for large-scale transportation management and planning.

Aerial surveillance vehicles augment security at shipping ports

NASA Astrophysics Data System (ADS)

Huck, Robert C.; Al Akkoumi, Muhammad K.; Cheng, Samuel; Sluss, James J., Jr.; Landers, Thomas L.

2008-10-01

With the ever present threat to commerce, both politically and economically, technological innovations provide a means to secure the transportation infrastructure that will allow efficient and uninterrupted freight-flow operations for trade. Currently, freight coming into United States ports is "spot checked" upon arrival and stored in a container yard while awaiting the next mode of transportation. For the most part, only fences and security patrols protect these container storage yards. To augment these measures, the authors propose the use of aerial surveillance vehicles equipped with video cameras and wireless video downlinks to provide a birds-eye view of port facilities to security control centers and security patrols on the ground. The initial investigation described in this paper demonstrates the use of unmanned aerial surveillance vehicles as a viable method for providing video surveillance of container storage yards. This research provides the foundation for a follow-on project to use autonomous aerial surveillance vehicles coordinated with autonomous ground surveillance vehicles for enhanced port security applications.

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.

Simulation and Flight Control of an Aeroelastic Fixed Wing Micro Aerial Vehicle

NASA Technical Reports Server (NTRS)

Waszak, Martin; Davidson, John B.; Ifju, Peter G.

2002-01-01

Micro aerial vehicles have been the subject of continued interest and development over the last several years. The majority of current vehicle concepts rely on rigid fixed wings or rotors. An alternate design based on an aeroelastic membrane wing has also been developed that exhibits desired characteristics in flight test demonstrations, competition, and in prior aerodynamics studies. This paper presents a simulation model and an assessment of flight control characteristics of the vehicle. Linear state space models of the vehicle associated with typical trimmed level flight conditions and which are suitable for control system design are presented as well. The simulation is used as the basis for the design of a measurement based nonlinear dynamic inversion control system and outer loop guidance system. The vehicle/controller system is the subject of ongoing investigations of autonomous and collaborative control schemes. The results indicate that the design represents a good basis for further development of the micro aerial vehicle for autonomous and collaborative controls research.

Unmanned Aerial Vehicle Systems for Disaster Relief: Tornado Alley

NASA Technical Reports Server (NTRS)

DeBusk, Wesley M.

2009-01-01

Unmanned aerial vehicle systems are currently in limited use for public service missions worldwide. Development of civil unmanned technology in the United States currently lags behind military unmanned technology development in part because of unresolved regulatory and technological issues. Civil unmanned aerial vehicle systems have potential to augment disaster relief and emergency response efforts. Optimal design of aerial systems for such applications will lead to unmanned vehicles which provide maximum potentiality for relief and emergency response while accounting for public safety concerns and regulatory requirements. A case study is presented that demonstrates application of a civil unmanned system to a disaster relief mission with the intent on saving lives. The concept utilizes unmanned aircraft to obtain advanced warning and damage assessments for tornados and severe thunderstorms. Overview of a tornado watch mission architecture as well as commentary on risk, cost, need for, and design tradeoffs for unmanned aerial systems are provided.

Real-Time Implementation of an Asynchronous Vision-Based Target Tracking System for an Unmanned Aerial Vehicle

DTIC Science & Technology

2007-06-01

Chin Khoon Quek. “Vision Based Control and Target Range Estimation for Small Unmanned Aerial Vehicle.” Master’s Thesis, Naval Postgraduate School...December 2005. [6] Kwee Chye Yap. “Incorporating Target Mensuration System for Target Motion Estimation Along a Road Using Asynchronous Filter

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.

Monitoring and Estimation of Soil Losses from Ephemeral Gully Erosion in Mediterranean Region Using Low Altitude Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Gündoğan, R.; Alma, V.; Dindaroğlu, T.; Günal, H.; Yakupoğlu, T.; Susam, T.; Saltalı, K.

2017-11-01

Calculation of gullies by remote sensing images obtained from satellite or aerial platforms is often not possible because gullies in agricultural fields, defined as the temporary gullies are filled in a very short time with tillage operations. Therefore, fast and accurate estimation of sediment loss with the temporary gully erosion is of great importance. In this study, it is aimed to monitor and calculate soil losses caused by the gully erosion that occurs in agricultural areas with low altitude unmanned aerial vehicles. According to the calculation with Pix4D, gully volume was estimated to be 10.41 m3 and total loss of soil was estimated to be 14.47 Mg. The RMSE value of estimations was found to be 0.89. The results indicated that unmanned aerial vehicles could be used in predicting temporary gully erosion and losses of soil.

FlyAR: augmented reality supported micro aerial vehicle navigation.

PubMed

Zollmann, Stefanie; Hoppe, Christof; Langlotz, Tobias; Reitmayr, Gerhard

2014-04-01

Micro aerial vehicles equipped with high-resolution cameras can be used to create aerial reconstructions of an area of interest. In that context automatic flight path planning and autonomous flying is often applied but so far cannot fully replace the human in the loop, supervising the flight on-site to assure that there are no collisions with obstacles. Unfortunately, this workflow yields several issues, such as the need to mentally transfer the aerial vehicle’s position between 2D map positions and the physical environment, and the complicated depth perception of objects flying in the distance. Augmented Reality can address these issues by bringing the flight planning process on-site and visualizing the spatial relationship between the planned or current positions of the vehicle and the physical environment. In this paper, we present Augmented Reality supported navigation and flight planning of micro aerial vehicles by augmenting the user’s view with relevant information for flight planning and live feedback for flight supervision. Furthermore, we introduce additional depth hints supporting the user in understanding the spatial relationship of virtual waypoints in the physical world and investigate the effect of these visualization techniques on the spatial understanding.

Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

NASA Astrophysics Data System (ADS)

Themistocleous, K.; Agapiou, A.; Cuca, B.; Hadjimitsis, D. G.

2015-04-01

Remote sensing has open up new dimensions in archaeological research. Although there has been significant progress in increasing the resolution of space/aerial sensors and image processing, the detection of the crop (and soil marks) formations, which relate to buried archaeological remains, are difficult to detect since these marks may not be visible in the images if observed over different period or at different spatial/spectral resolution. In order to support the improvement of earth observation remote sensing technologies specifically targeting archaeological research, a better understanding of the crop/soil marks formation needs to be studied in detail. In this paper the contribution of both Unmanned Aerial Systems as well ground spectroradiometers is discussed in a variety of examples applied in the eastern Mediterranean region (Cyprus and Greece) as well in Central Europe (Hungary). In- situ spectroradiometric campaigns can be applied for the removal of atmospheric impact to simultaneous satellite overpass images. In addition, as shown in this paper, the systematic collection of ground truth data prior to the satellite/aerial acquisition can be used to detect the optimum temporal and spectral resolution for the detection of stress vegetation related to buried archaeological remains. Moreover, phenological studies of the crops from the area of interest can be simulated to the potential sensors based on their Relative Response Filters and therefore prepare better the satellite-aerial campaigns. Ground data and the use of Unmanned Aerial Systems (UAS) can provide an increased insight for studying the formation of crop and soil marks. New algorithms such as vegetation indices and linear orthogonal equations for the enhancement of crop marks can be developed based on the specific spectral characteristics of the area. As well, UAS can be used for remote sensing applications in order to document, survey and model cultural heritage and archaeological sites.

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.

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.

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...

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

Vision based control of unmanned aerial vehicles with applications to an autonomous four-rotor helicopter, quadrotor

NASA Astrophysics Data System (ADS)

Altug, Erdinc

Our work proposes a vision-based stabilization and output tracking control method for a model helicopter. This is a part of our effort to produce a rotorcraft based autonomous Unmanned Aerial Vehicle (UAV). Due to the desired maneuvering ability, a four-rotor helicopter has been chosen as the testbed. On previous research on flying vehicles, vision is usually used as a secondary sensor. Unlike previous research, our goal is to use visual feedback as the main sensor, which is not only responsible for detecting where the ground objects are but also for helicopter localization. A novel two-camera method has been introduced for estimating the full six degrees of freedom (DOF) pose of the helicopter. This two-camera system consists of a pan-tilt ground camera and an onboard camera. The pose estimation algorithm is compared through simulation to other methods, such as four-point, and stereo method and is shown to be less sensitive to feature detection errors. Helicopters are highly unstable flying vehicles; although this is good for agility, it makes the control harder. To build an autonomous helicopter, two methods of control are studied---one using a series of mode-based, feedback linearizing controllers and the other using a back-stepping control law. Various simulations with 2D and 3D models demonstrate the implementation of these controllers. We also show global convergence of the 3D quadrotor controller even with large calibration errors or presence of large errors on the image plane. Finally, we present initial flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter. The helicopter was restricted with a tether to vertical, yaw motions and limited x and y translations.

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 ...

Remote control for motor vehicle

NASA Technical Reports Server (NTRS)

Johnson, Dale R. (Inventor); Ciciora, John A. (Inventor)

1984-01-01

A remote controller is disclosed for controlling the throttle, brake and steering mechanism of a conventional motor vehicle, with the remote controller being particularly advantageous for use by severely handicapped individuals. The controller includes a remote manipulator which controls a plurality of actuators through interfacing electronics. The remote manipulator is a two-axis joystick which controls a pair of linear actuators and a rotary actuator, with the actuators being powered by electric motors to effect throttle, brake and steering control of a motor vehicle adapted to include the controller. The controller enables the driver to control the adapted vehicle from anywhere in the vehicle with one hand with minimal control force and range of motion. In addition, even though a conventional vehicle is adapted for use with the remote controller, the vehicle may still be operated in the normal manner.

Exploration of the Use of Unmanned Aerial Vehicles along with Other Assets to Enhance Border Protection

DTIC Science & Technology

2009-06-01

Border Initiative SUAV Small Unmanned Aerial Vehicle SAR Synthetic Aperture Radar TTPs Tactics, Techniques, And Procedures TRVS Trailer Remote...2008). 4 3. Overview of Illegal Activities According to the CBP, 178,770 pounds of cocaine, 2,178 pounds of heroin, 2,471,931 pounds of marijuana ...Raytheon Company Web Site) Another component of Predator B is the high- resolution Lynx Synthetic Aperture Radar (SAR). In their study, Tsunoda, et

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.

Reducing environmental damage through the use of unmanned aerial vehicles as the best available technology

NASA Astrophysics Data System (ADS)

Fedulova, E. A.; Akulov, A. O.; Rada, A. O.; Alabina, T. A.; Savina, Ju Ju

2018-01-01

The article examines the possibilities of using unmanned aerial vehicles as the best available technologies in the field of agriculture and mining. The object of the study is the use of unmanned aerial vehicles as the best available technology. The main areas of application of this technology are identified: agro technical operations, aerial photography of mining operations. The technology of unmanned aerial vehicles is compared with the technologies of ground agricultural machinery. The research methodology includes an expert evaluation of the unmanned aerial vehicle technology belonging to the class of the best available technologies by the criteria: the level of environmental impact, resource saving, the use of low-waste, non-waste processes, the existence of at least two objects, economic efficiency. Expert evaluations were processed using the apparatus of fuzzy sets, which make it possible to construct membership functions. This allowed us to prove that the technology of unmanned aerial vehicles belongs to a fuzzy set of the best available technologies. The results of the research show that the use of unmanned aerial vehicles provides a saving of resources, especially non-renewable combustible minerals, reduces emissions and discharges of pollutants into the atmosphere, and also reduces soil erosion. Unmanned aerial vehicles should be included in the national directories of the best available technologies for the mining industry and agriculture.

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 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.

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

Corn and sorghum phenotyping using a fixed-wing UAV-based remote sensing system

NASA Astrophysics Data System (ADS)

Shi, Yeyin; Murray, Seth C.; Rooney, William L.; Valasek, John; Olsenholler, Jeff; Pugh, N. Ace; Henrickson, James; Bowden, Ezekiel; Zhang, Dongyan; Thomasson, J. Alex

2016-05-01

Recent development of unmanned aerial systems has created opportunities in automation of field-based high-throughput phenotyping by lowering flight operational cost and complexity and allowing flexible re-visit time and higher image resolution than satellite or manned airborne remote sensing. In this study, flights were conducted over corn and sorghum breeding trials in College Station, Texas, with a fixed-wing unmanned aerial vehicle (UAV) carrying two multispectral cameras and a high-resolution digital camera. The objectives were to establish the workflow and investigate the ability of UAV-based remote sensing for automating data collection of plant traits to develop genetic and physiological models. Most important among these traits were plant height and number of plants which are currently manually collected with high labor costs. Vegetation indices were calculated for each breeding cultivar from mosaicked and radiometrically calibrated multi-band imagery in order to be correlated with ground-measured plant heights, populations and yield across high genetic-diversity breeding cultivars. Growth curves were profiled with the aerial measured time-series height and vegetation index data. The next step of this study will be to investigate the correlations between aerial measurements and ground truth measured manually in field and from lab tests.

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...

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...

Applying Lessons Learned from Space Safety to Unmanned Aerial Vehicle Risk Assessments

NASA Astrophysics Data System (ADS)

Devoid, Wayne E.

2013-09-01

This paper will examine the application of current orbital launch risk methodology to assessing risk for unmanned aerial vehicle flights over populated areas. Major differences, such as the added complexity of lifting bodies, accounting for pilots-in-the-loop, and the complexity of using current population data to estimate risk for unmanned aerial vehicles, will be highlighted.

Development of a remote digital augmentation system and application to a remotely piloted research vehicle

NASA Technical Reports Server (NTRS)

Edwards, J. W.; Deets, D. A.

1975-01-01

A cost-effective approach to flight testing advanced control concepts with remotely piloted vehicles is described. The approach utilizes a ground based digital computer coupled to the remotely piloted vehicle's motion sensors and control surface actuators through telemetry links to provide high bandwidth feedback control. The system was applied to the control of an unmanned 3/8-scale model of the F-15 airplane. The model was remotely augmented; that is, the F-15 mechanical and control augmentation flight control systems were simulated by the ground-based computer, rather than being in the vehicle itself. The results of flight tests of the model at high angles of attack are discussed.

Intelligent unmanned vehicle systems suitable for individual or cooperative missions

NASA Astrophysics Data System (ADS)

Anderson, Matthew O.; McKay, Mark D.; Wadsworth, Derek C.

2007-04-01

The Department of Energy's Idaho National Laboratory (INL) has been researching autonomous unmanned vehicle systems for over fifteen years. Areas of research have included unmanned ground and aerial vehicles used for hazardous and remote operations as well as teamed together for advanced payloads and mission execution. Areas of application include aerial particulate sampling, cooperative remote radiological sampling, and persistent surveillance including real-time mosaic and geo-referenced imagery in addition to high-resolution still imagery. Both fixed-wing and rotary airframes are used possessing capabilities spanning remote control to fully autonomous operation. Patented INL-developed auto steering technology is taken advantage of to provide autonomous parallel path swathing with either manned or unmanned ground vehicles. Aerial look-ahead imagery is utilized to provide a common operating picture for the ground and air vehicles during cooperative missions. This paper will discuss the various robotic vehicles, including sensor integration, used to achieve these missions and anticipated cost and labor savings.

Remotely piloted vehicles. Citations from the International Aerospace abstracts data base

NASA Technical Reports Server (NTRS)

Mauk, S. C.

1980-01-01

These citations from the international literature cover various aspects of remotely piloted vehicles. Included are articles concerning aircraft design, flight tests, aircraft control, cost effectiveness, automatic flight control, automatic pilots, and data links. Civil aviation applications are included, although military uses of remotely piloted vehicles are stressed. This updated bibliography contains 224 citations, 43 of which are new additions to the previous edition.

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

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.

Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing.

PubMed

Popescu, Dan; Ichim, Loretta; Stoican, Florin

2017-02-23

Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication. The aerial component contains mobile nodes-fixed wing type UAVs. In order to evaluate flood damage, two tasks must be accomplished by the network: area coverage and image processing. The second novelty of the paper consists of texture analysis in a deep neural network, taking into account new criteria for feature selection and patch classification. Color and spatial information extracted from chromatic co-occurrence matrix and mass fractal dimension were used as well. Finally, the experimental results in a real mission demonstrate the validity of the proposed methodologies and the performances of the algorithms.

Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing

PubMed Central

Popescu, Dan; Ichim, Loretta; Stoican, Florin

2017-01-01

Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication. The aerial component contains mobile nodes—fixed wing type UAVs. In order to evaluate flood damage, two tasks must be accomplished by the network: area coverage and image processing. The second novelty of the paper consists of texture analysis in a deep neural network, taking into account new criteria for feature selection and patch classification. Color and spatial information extracted from chromatic co-occurrence matrix and mass fractal dimension were used as well. Finally, the experimental results in a real mission demonstrate the validity of the proposed methodologies and the performances of the algorithms. PMID:28241479

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.

The Ad Hoc Mars Airplane science working group. [remotely piloted airplane as a Mars exploration vehicle

NASA Technical Reports Server (NTRS)

Clarke, V. C., Jr.

1978-01-01

The capability of a remotely piloted airplane as a Mars exploration vehicle in the aerial survey mode is assessed. Specific experiment areas covered include: visual imaging; gamma ray and infrared reflectance spectroscopy; gravity field; magnetic field and electromagnetic sounding; and atmospheric composition and dynamics. It is concluded that (1) the most important use of a plane in the aerial survey mode would be in topical studies and returned sample site characterization; (2) the airplane offers the unique capability to do high resolution, oblique imaging, and repeated profile measurements in the atmospheric boundary layer; and (3) it offers the best platform from which to do electromagnetic sounding.

Stability and Control Properties of an Aeroelastic Fixed Wing Micro Aerial Vehicle

NASA Technical Reports Server (NTRS)

Waszak, Martin R.; Jenkins, Luther N.; Ifju, Peter

2001-01-01

Micro aerial vehicles have been the subject of considerable interest and development over the last several years. The majority of current vehicle concepts rely on rigid fixed wings or rotors. An alternate design based on an aeroelastic membrane wing concept has also been developed that has exhibited desired characteristics in flight test demonstrations and competition. This paper presents results from a wind tunnel investigation that sought to quantify stability and control properties for a family of vehicles using the aeroelastic design. The results indicate that the membrane wing does exhibit potential benefits that could be exploited to enhance the design of future flight vehicles.

Unmanned aerial systems-based remote sensing for monitoring sorghum growth and development

PubMed Central

Shafian, Sanaz; Schnell, Ronnie; Bagavathiannan, Muthukumar; Valasek, John; Shi, Yeyin; Olsenholler, Jeff

2018-01-01

Unmanned Aerial Vehicles and Systems (UAV or UAS) have become increasingly popular in recent years for agricultural research applications. UAS are capable of acquiring images with high spatial and temporal resolutions that are ideal for applications in agriculture. The objective of this study was to evaluate the performance of a UAS-based remote sensing system for quantification of crop growth parameters of sorghum (Sorghum bicolor L.) including leaf area index (LAI), fractional vegetation cover (fc) and yield. The study was conducted at the Texas A&M Research Farm near College Station, Texas, United States. A fixed-wing UAS equipped with a multispectral sensor was used to collect image data during the 2016 growing season (April–October). Flight missions were successfully carried out at 50 days after planting (DAP; 25 May), 66 DAP (10 June) and 74 DAP (18 June). These flight missions provided image data covering the middle growth period of sorghum with a spatial resolution of approximately 6.5 cm. Field measurements of LAI and fc were also collected. Four vegetation indices were calculated using the UAS images. Among those indices, the normalized difference vegetation index (NDVI) showed the highest correlation with LAI, fc and yield with R2 values of 0.91, 0.89 and 0.58 respectively. Empirical relationships between NDVI and LAI and between NDVI and fc were validated and proved to be accurate for estimating LAI and fc from UAS-derived NDVI values. NDVI determined from UAS imagery acquired during the flowering stage (74 DAP) was found to be the most highly correlated with final grain yield. The observed high correlations between UAS-derived NDVI and the crop growth parameters (fc, LAI and grain yield) suggests the applicability of UAS for within-season data collection of agricultural crops such as sorghum. PMID:29715311

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.

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.

Improving Rangeland Monitoring and Assessment: Integrating Remote Sensing, GIS, and Unmanned Aerial Vehicle Systems

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

Robert Paul Breckenridge

2007-05-01

Creeping environmental changes are impacting some of the largest remaining intact parcels of sagebrush steppe ecosystems in the western United States, creating major problems for land managers. The Idaho National Laboratory (INL), located in southeastern Idaho, is part of the sagebrush steppe ecosystem, one of the largest ecosystems on the continent. Scientists at the INL and the University of Idaho have integrated existing field and remotely sensed data with geographic information systems technology to analyze how recent fires on the INL have influenced the current distribution of terrestrial vegetation. Three vegetation mapping and classification systems were used to evaluate themore » changes in vegetation caused by fires between 1994 and 2003. Approximately 24% of the sagebrush steppe community on the INL was altered by fire, mostly over a 5-year period. There were notable differences between methods, especially for juniper woodland and grasslands. The Anderson system (Anderson et al. 1996) was superior for representing the landscape because it includes playa/bare ground/disturbed area and sagebrush steppe on lava as vegetation categories. This study found that assessing existing data sets is useful for quantifying fire impacts and should be helpful in future fire and land use planning. The evaluation identified that data from remote sensing technologies is not currently of sufficient quality to assess the percentage of cover. To fill this need, an approach was designed using both helicopter and fixed wing unmanned aerial vehicles (UAVs) and image processing software to evaluate six cover types on field plots located on the INL. The helicopter UAV provided the best system compared against field sampling, but is more dangerous and has spatial coverage limitations. It was reasonably accurate for dead shrubs and was very good in assessing percentage of bare ground, litter and grasses; accuracy for litter and shrubs is questionable. The fixed wing system proved

Reliability Assessment for Low-cost Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Freeman, Paul Michael

Existing low-cost unmanned aerospace systems are unreliable, and engineers must blend reliability analysis with fault-tolerant control in novel ways. This dissertation introduces the University of Minnesota unmanned aerial vehicle flight research platform, a comprehensive simulation and flight test facility for reliability and fault-tolerance research. An industry-standard reliability assessment technique, the failure modes and effects analysis, is performed for an unmanned aircraft. Particular attention is afforded to the control surface and servo-actuation subsystem. Maintaining effector health is essential for safe flight; failures may lead to loss of control incidents. Failure likelihood, severity, and risk are qualitatively assessed for several effector failure modes. Design changes are recommended to improve aircraft reliability based on this analysis. Most notably, the control surfaces are split, providing independent actuation and dual-redundancy. The simulation models for control surface aerodynamic effects are updated to reflect the split surfaces using a first-principles geometric analysis. The failure modes and effects analysis is extended by using a high-fidelity nonlinear aircraft simulation. A trim state discovery is performed to identify the achievable steady, wings-level flight envelope of the healthy and damaged vehicle. Tolerance of elevator actuator failures is studied using familiar tools from linear systems analysis. This analysis reveals significant inherent performance limitations for candidate adaptive/reconfigurable control algorithms used for the vehicle. Moreover, it demonstrates how these tools can be applied in a design feedback loop to make safety-critical unmanned systems more reliable. Control surface impairments that do occur must be quickly and accurately detected. This dissertation also considers fault detection and identification for an unmanned aerial vehicle using model-based and model-free approaches and applies those

76 FR 61750 - Vehicle-Mounted Elevating and Rotating Work Platforms (Aerial Lifts); Extension of the Office of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-05

...] Vehicle-Mounted Elevating and Rotating Work Platforms (Aerial Lifts); Extension of the Office of... requirement contained in the Standard on Vehicle-Mounted Elevating and Rotating Work Platforms (Aerial Lifts... by ensuring that aerial lifts are in safe operating condition. DATES: Comments must be submitted...

Wageningen UR Unmanned Aerial Remote Sensing Facility - Overview of activities

NASA Astrophysics Data System (ADS)

Bartholomeus, Harm; Keesstra, Saskia; Kooistra, Lammert; Suomalainen, Juha; Mucher, Sander; Kramer, Henk; Franke, Jappe

2016-04-01

To support environmental management there is an increasing need for timely, accurate and detailed information on our land. Unmanned Aerial Systems (UAS) are increasingly used to monitor agricultural crop development, habitat quality or urban heat efficiency. An important reason is that UAS technology is maturing quickly while the flexible capabilities of UAS fill a gap between satellite based and ground based geo-sensing systems. In 2012, different groups within Wageningen University and Research Centre have established an Unmanned Airborne Remote Sensing Facility. The objective of this facility is threefold: a) To develop innovation in the field of remote sensing science by providing a platform for dedicated and high-quality experiments; b) To support high quality UAS services by providing calibration facilities and disseminating processing procedures to the UAS user community; and c) To promote and test the use of UAS in a broad range of application fields like habitat monitoring, precision agriculture and land degradation assessment. The facility is hosted by the Laboratory of Geo-Information Science and Remote Sensing (GRS) and the Department of Soil Physics and Land Management (SLM) of Wageningen University together with the team Earth Informatics (EI) of Alterra. The added value of the Unmanned Aerial Remote Sensing Facility is that compared to for example satellite based remote sensing more dedicated science experiments can be prepared. This includes for example higher frequent observations in time (e.g., diurnal observations), observations of an object under different observation angles for characterization of BRDF and flexibility in use of camera's and sensors types. In this way, laboratory type of set ups can be tested in a field situation and effects of up-scaling can be tested. In the last years we developed and implemented different camera systems (e.g. a hyperspectral pushbroom system, and multispectral frame cameras) which we operated in projects all

Thermal/structural/optical integrated design for optical sensor mounted on unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Zhang, Gaopeng; Yang, Hongtao; Mei, Chao; Wu, Dengshan; Shi, Kui

2016-01-01

With the rapid development of science and technology and the promotion of many local wars in the world, altitude optical sensor mounted on unmanned aerial vehicle is more widely applied in the airborne remote sensing, measurement and detection. In order to obtain high quality image of the aero optical remote sensor, it is important to analysis its thermal-optical performance on the condition of high speed and high altitude. Especially for the key imaging assembly, such as optical window, the temperature variation and temperature gradient can result in defocus and aberrations in optical system, which will lead to the poor quality image. In order to improve the optical performance of a high speed aerial camera optical window, the thermal/structural/optical integrated design method is developed. Firstly, the flight environment of optical window is analyzed. Based on the theory of aerodynamics and heat transfer, the convection heat transfer coefficient is calculated. The temperature distributing of optical window is simulated by the finite element analysis software. The maximum difference in temperature of the inside and outside of optical window is obtained. Then the deformation of optical window under the boundary condition of the maximum difference in temperature is calculated. The optical window surface deformation is fitted in Zernike polynomial as the interface, the calculated Zernike fitting coefficients is brought in and analyzed by CodeV Optical Software. At last, the transfer function diagrams of the optical system on temperature field are comparatively analyzed. By comparing and analyzing the result, it can be obtained that the optical path difference caused by thermal deformation of the optical window is 138.2 nm, which is under PV ≤1 4λ . The above study can be used as an important reference for other optical window designs.

Integrated remotely sensed datasets for disaster management

NASA Astrophysics Data System (ADS)

McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart

2008-10-01

Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.

Development of Bird-like Micro Aerial Vehicle with Flapping and Feathering Wing Motions

NASA Astrophysics Data System (ADS)

Maglasang, Jonathan; Goto, Norihiro; Isogai, Koji

To investigate the feasibility of a highly efficient flapping system capable of avian maneuvers, such as rapid takeoff, hover and gliding, a full scale bird-like (ornithopter) flapping-wing micro aerial vehicle (MAV) shaped and patterned after a typical pigeon (Columba livia) has been designed and constructed. Both numerical and experimental methods have been used in the development of this vehicle. This flapping-wing micro aerial vehicle utilizes both the flapping and feathering motions of an avian wing by employing a novel flapping-feathering mechanism, which has been synthesized and constructed so as to best describe the properly coordinated flapping and feathering wing motions at phase angle difference of 90° in a horizontal steady level flight condition. This design allows high flapping and feathering amplitudes and is configurable for asymmetric wing motions which are desirable in high-speed flapping flight and maneuvering. The preliminary results indicate its viability as a practical and an efficient flapping-wing micro aerial vehicle.

A remotely piloted aircraft system in major incident management: concept and pilot, feasibility study.

PubMed

Abrahamsen, Håkon B

2015-06-10

Major incidents are complex, dynamic and bewildering task environments characterised by simultaneous, rapidly changing events, uncertainty and ill-structured problems. Efficient management, communication, decision-making and allocation of scarce medical resources at the chaotic scene of a major incident is challenging and often relies on sparse information and data. Communication and information sharing is primarily voice-to-voice through phone or radio on specified radio frequencies. Visual cues are abundant and difficult to communicate between teams and team members that are not co-located. The aim was to assess the concept and feasibility of using a remotely piloted aircraft (RPA) system to support remote sensing in simulated major incident exercises. We carried out an experimental, pilot feasibility study. A custom-made, remotely controlled, multirotor unmanned aerial vehicle with vertical take-off and landing was equipped with digital colour- and thermal imaging cameras, a laser beam, a mechanical gripper arm and an avalanche transceiver. We collected data in five simulated exercises: 1) mass casualty traffic accident, 2) mountain rescue, 3) avalanche with buried victims, 4) fisherman through thin ice and 5) search for casualties in the dark. The unmanned aerial vehicle was remotely controlled, with high precision, in close proximity to air space obstacles at very low levels without compromising work on the ground. Payload capacity and tolerance to wind and turbulence were limited. Aerial video, shot from different altitudes, and remote aerial avalanche beacon search were streamed wirelessly in real time to a monitor at a ground base. Electromagnetic interference disturbed signal reception in the ground monitor. A small remotely piloted aircraft can be used as an effective tool carrier, although limited by its payload capacity, wind speed and flight endurance. Remote sensing using already existing remotely piloted aircraft technology in pre

Supporting Remote Sensing Research with Small Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Anderson, R. C.; Shanks, P. C.; Kritis, L. A.; Trani, M. G.

2014-11-01

We describe several remote sensing research projects supported with small Unmanned Aerial Systems (sUAS) operated by the NGA Basic and Applied Research Office. These sUAS collections provide data supporting Small Business Innovative Research (SBIR), NGA University Research Initiative (NURI), and Cooperative Research And Development Agreements (CRADA) efforts in addition to inhouse research. Some preliminary results related to 3D electro-optical point clouds are presented, and some research goals discussed. Additional details related to the autonomous operational mode of both our multi-rotor and fixed wing small Unmanned Aerial System (sUAS) platforms are presented.

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...

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.

Fixed-Wing Micro Aerial Vehicle for Accurate Corridor Mapping

NASA Astrophysics Data System (ADS)

Rehak, M.; Skaloud, J.

2015-08-01

In this study we present a Micro Aerial Vehicle (MAV) equipped with precise position and attitude sensors that together with a pre-calibrated camera enables accurate corridor mapping. The design of the platform is based on widely available model components to which we integrate an open-source autopilot, customized mass-market camera and navigation sensors. We adapt the concepts of system calibration from larger mapping platforms to MAV and evaluate them practically for their achievable accuracy. We present case studies for accurate mapping without ground control points: first for a block configuration, later for a narrow corridor. We evaluate the mapping accuracy with respect to checkpoints and digital terrain model. We show that while it is possible to achieve pixel (3-5 cm) mapping accuracy in both cases, precise aerial position control is sufficient for block configuration, the precise position and attitude control is required for corridor mapping.

Multiple vehicle tracking in aerial video sequence using driver behavior analysis and improved deterministic data association

NASA Astrophysics Data System (ADS)

Zhang, Xunxun; Xu, Hongke; Fang, Jianwu

2018-01-01

Along with the rapid development of the unmanned aerial vehicle technology, multiple vehicle tracking (MVT) in aerial video sequence has received widespread interest for providing the required traffic information. Due to the camera motion and complex background, MVT in aerial video sequence poses unique challenges. We propose an efficient MVT algorithm via driver behavior-based Kalman filter (DBKF) and an improved deterministic data association (IDDA) method. First, a hierarchical image registration method is put forward to compensate the camera motion. Afterward, to improve the accuracy of the state estimation, we propose the DBKF module by incorporating the driver behavior into the Kalman filter, where artificial potential field is introduced to reflect the driver behavior. Then, to implement the data association, a local optimization method is designed instead of global optimization. By introducing the adaptive operating strategy, the proposed IDDA method can also deal with the situation in which the vehicles suddenly appear or disappear. Finally, comprehensive experiments on the DARPA VIVID data set and KIT AIS data set demonstrate that the proposed algorithm can generate satisfactory and superior results.

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

Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

NASA Astrophysics Data System (ADS)

Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

2016-10-01

With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

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

The automation of remote vehicle control. [in Mars roving vehicles

NASA Technical Reports Server (NTRS)

Paine, G.

1977-01-01

The automation of remote vehicles is becoming necessary to overcome the requirement of having man present as a controller. By removing man, remote vehicles can be operated in areas where the environment is too hostile for man, his reaction times are too slow, time delays are too long, and where his presence is too costly, or where system performance can be improved. This paper addresses the development of automated remote vehicle control for nonspace and space tasks from warehouse vehicles to proposed Mars rovers. The state-of-the-art and the availability of new technology for implementing automated control are reviewed and the major problem areas are outlined. The control strategies are divided into those where the path is planned in advance or constrained, or where the system is a teleoperator, or where automation or robotics have been introduced.

The Sky Is the Limit: Reconstructing Physical Geography from an Aerial Perspective

ERIC Educational Resources Information Center

Williams, Richard D.; Tooth, Stephen; Gibson, Morgan

2017-01-01

In an era of rapid geographical data acquisition, interpretations of remote sensing products are an integral part of many undergraduate geography degree schemes but there are fewer opportunities for collection and processing of primary remote sensing data. Unmanned Aerial Vehicles (UAVs) provide a relatively inexpensive opportunity to introduce…

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.

Flexible Wing Base Micro Aerial Vehicles: Towards Flight Autonomy: Vision-Based Horizon Detection for Micro Air Vehicles

NASA Technical Reports Server (NTRS)

Nechyba, Michael C.; Ettinger, Scott M.; Ifju, Peter G.; Wazak, Martin

2002-01-01

Recently substantial progress has been made towards design building and testifying remotely piloted Micro Air Vehicles (MAVs). This progress in overcoming the aerodynamic obstacles to flight at very small scales has, unfortunately, not been matched by similar progress in autonomous MAV flight. Thus, we propose a robust, vision-based horizon detection algorithm as the first step towards autonomous MAVs. In this paper, we first motivate the use of computer vision for the horizon detection task by examining the flight of birds (biological MAVs) and considering other practical factors. We then describe our vision-based horizon detection algorithm, which has been demonstrated at 30 Hz with over 99.9% correct horizon identification, over terrain that includes roads, buildings large and small, meadows, wooded areas, and a lake. We conclude with some sample horizon detection results and preview a companion paper, where the work discussed here forms the core of a complete autonomous flight stability system.

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.

Use of micro unmanned aerial vehicles for roadside condition assessment

DOT National Transportation Integrated Search

2010-12-01

Micro unmanned aerial vehicles (MUAVs) that are equipped with digital imaging systems and global : positioning systems provide a potential opportunity for improving the effectiveness and safety of roadside : condition and inventory surveys. This stud...

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.

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

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

Toward autonomous avian-inspired grasping for micro aerial vehicles.

PubMed

Thomas, Justin; Loianno, Giuseppe; Polin, Joseph; Sreenath, Koushil; Kumar, Vijay

2014-06-01

Micro aerial vehicles, particularly quadrotors, have been used in a wide range of applications. However, the literature on aerial manipulation and grasping is limited and the work is based on quasi-static models. In this paper, we draw inspiration from agile, fast-moving birds such as raptors, that are able to capture moving prey on the ground or in water, and develop similar capabilities for quadrotors. We address dynamic grasping, an approach to prehensile grasping in which the dynamics of the robot and its gripper are significant and must be explicitly modeled and controlled for successful execution. Dynamic grasping is relevant for fast pick-and-place operations, transportation and delivery of objects, and placing or retrieving sensors. We show how this capability can be realized (a) using a motion capture system and (b) without external sensors relying only on onboard sensors. In both cases we describe the dynamic model, and trajectory planning and control algorithms. In particular, we present a methodology for flying and grasping a cylindrical object using feedback from a monocular camera and an inertial measurement unit onboard the aerial robot. This is accomplished by mapping the dynamics of the quadrotor to a level virtual image plane, which in turn enables dynamically-feasible trajectory planning for image features in the image space, and a vision-based controller with guaranteed convergence properties. We also present experimental results obtained with a quadrotor equipped with an articulated gripper to illustrate both approaches.

Aerial Vehicles to Detect Maximum Volume of Plume Material Associated with Habitable Areas in Extreme Environments

NASA Technical Reports Server (NTRS)

Gunasekara, Onalli; Wong, Uland Y.; Furlong, Michael P.; Dille, Michael

2017-01-01

Current technologies of exploring habitable areas of icy moons are limited to flybys of space probes. This research project addresses long-term navigation of icy moons by developing a MATLAB adjustable trajectory based on the volume of plume material observed. Plumes expose materials from the sub-surface without accessing the subsurface. Aerial vehicles capable of scouting vapor plumes and detecting maximum plume material volumes, which are considered potentially habitable in inhospitable environments, would enable future deep-space missions to search for extraterrestrial organisms on the surface of icy moons. Although this platform is still a prototype, it demonstrates the potential aerial vehicles can have in improving the capabilities of long-term space navigation and enabling technology for detecting life in extreme environments. Additionally, this work is developing the capabilities that could be utilized as a platform for space biology research. For example, aerial vehicles that are sent to map extreme environments of icy moons or the planet Mars, could also carry small payloads with automated cell-biology experiments, designed to probe the biological response of low-gravity and high-radiation planetary environments, serving as a pathfinder for future human missions.

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.

Remotely detected vehicle mass from engine torque-induced frame twisting

NASA Astrophysics Data System (ADS)

McKay, Troy R.; Salvaggio, Carl; Faulring, Jason W.; Sweeney, Glenn D.

2017-06-01

Determining the mass of a vehicle from ground-based passive sensor data is important for many traffic safety requirements. This work presents a method for calculating the mass of a vehicle using ground-based video and acoustic measurements. By assuming that no energy is lost in the conversion, the mass of a vehicle can be calculated from the rotational energy generated by the vehicle's engine and the linear acceleration of the vehicle over a period of time. The amount of rotational energy being output by the vehicle's engine can be calculated from its torque and angular velocity. This model relates remotely observed, engine torque-induced frame twist to engine torque output using the vehicle's suspension parameters and engine geometry. The angular velocity of the engine is extracted from the acoustic emission of the engine, and the linear acceleration of the vehicle is calculated by remotely observing the position of the vehicle over time. This method combines these three dynamic signals; engine induced-frame twist, engine angular velocity, and the vehicle's linear acceleration, and three vehicle specific scalar parameters, into an expression that describes the mass of the vehicle. This method was tested on a semitrailer truck, and the results demonstrate a correlation of 97.7% between calculated and true vehicle mass.

Virtual Machine Language Controls Remote Devices

NASA Technical Reports Server (NTRS)

2014-01-01

Kennedy Space Center worked with Blue Sun Enterprises, based in Boulder, Colorado, to enhance the company's virtual machine language (VML) to control the instruments on the Regolith and Environment Science and Oxygen and Lunar Volatiles Extraction mission. Now the NASA-improved VML is available for crewed and uncrewed spacecraft, and has potential applications on remote systems such as weather balloons, unmanned aerial vehicles, and submarines.

Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles

NASA Technical Reports Server (NTRS)

Brockers, Roland; Ma, Jeremy C.; Matthies, Larry H.; Bouffard, Patrick

2012-01-01

Micro aerial vehicles have limited sensor suites and computational power. For reconnaissance tasks and to conserve energy, these systems need the ability to autonomously land at vantage points or enter buildings (ingress). But for autonomous navigation, information is needed to identify and guide the vehicle to the target. Vision algorithms can provide egomotion estimation and target detection using input from cameras that are easy to include in miniature systems.

Navigation and Remote Sensing Payloads and Methods of the Sarvant Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Molina, P.; Fortuny, P.; Colomina, I.; Remy, M.; Macedo, K. A. C.; Zúnigo, Y. R. C.; Vaz, E.; Luebeck, D.; Moreira, J.; Blázquez, M.

2013-08-01

In a large number of scenarios and missions, the technical, operational and economical advantages of UAS-based photogrammetry and remote sensing over traditional airborne and satellite platforms are apparent. Airborne Synthetic Aperture Radar (SAR) or combined optical/SAR operation in remote areas might be a case of a typical "dull, dirty, dangerous" mission suitable for unmanned operation - in harsh environments such as for example rain forest areas in Brazil, topographic mapping of small to medium sparsely inhabited remote areas with UAS-based photogrammetry and remote sensing seems to be a reasonable paradigm. An example of such a system is the SARVANT platform, a fixed-wing aerial vehicle with a six-meter wingspan and a maximumtake- of-weight of 140 kilograms, able to carry a fifty-kilogram payload. SARVANT includes a multi-band (X and P) interferometric SAR payload, as the P-band enables the topographic mapping of densely tree-covered areas, providing terrain profile information. Moreover, the combination of X- and P-band measurements can be used to extract biomass estimations. Finally, long-term plan entails to incorporate surveying capabilities also at optical bands and deliver real-time imagery to a control station. This paper focuses on the remote-sensing concept in SARVANT, composed by the aforementioned SAR sensor and envisioning a double optical camera configuration to cover the visible and the near-infrared spectrum. The flexibility on the optical payload election, ranging from professional, medium-format cameras to mass-market, small-format cameras, is discussed as a driver in the SARVANT development. The paper also focuses on the navigation and orientation payloads, including the sensors (IMU and GNSS), the measurement acquisition system and the proposed navigation and orientation methods. The latter includes the Fast AT procedure, which performs close to traditional Integrated Sensor Orientation (ISO) and better than Direct Sensor Orientation (Di

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

PubMed

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

2016-09-01

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. 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. 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. 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.

Measurement of atmospheric surface layer turbulence using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bailey, Sean; Canter, Caleb

2017-11-01

We describe measurements of the turbulence within the atmospheric surface layer using highly instrumented and autonomous unmanned aerial vehicles (UAVs). Results from the CLOUDMAP measurement campaign in Stillwater Oklahoma are presented including turbulence statistics measured during the transition from stably stratified to convective conditions. The measurements were made using pre-fabricated fixed-wing remote-control aircraft adapted to fly autonomously and carry multi-hole pressure probes, pressure, temperature and humidity sensors. Two aircraft were flown simultaneously, with one flying a flight path intended to profile the boundary layer up to 100 m and the other flying at a constant fixed altitude of 50 m. The evolution of various turbulent statistics was determined from these flights, including Reynolds stresses, correlations, spectra and structure functions. These results were compared to those measured by a sonic anemometer located on a 7.5 m tower. This work was supported by the National Science Foundation through Grant #CBET-1351411 and by National Science Foundation award #1539070, Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics (CLOUDMAP).

Measurement of atmospheric surface layer turbulence using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Witte, Brandon; Smith, Lorli; Schlagenhauf, Cornelia; Bailey, Sean

2016-11-01

We describe measurements of the turbulence within the atmospheric surface layer using highly instrumented and autonomous unmanned aerial vehicles (UAVs). Results from the CLOUDMAP measurement campaign in Stillwater Oklahoma are presented including turbulence statistics measured during the transition from stably stratified to convective conditions. The measurements were made using pre-fabricated fixed-wing remote-control aircraft adapted to fly autonomously and carry multi-hole pressure probes, pressure, temperature and humidity sensors. Two aircraft were flown simultaneously, with one flying a flight path intended to profile the boundary layer up to 100 m and the other flying at a constant fixed altitude of 50 m. The evolution of various turbulent statistics was determined from these flights, including Reynolds stresses, correlations, spectra and structure functions. These results were compared to those measured by a sonic anemometer located on a 7.5 m tower. This work was supported by the National Science Foundation through Grant #CBET-1351411 and by National Science Foundation award #1539070, Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics (CLOUDMAP).

UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation

NASA Astrophysics Data System (ADS)

Qiu, Xiang; Dai, Ming; Yin, Chuan-li

2017-09-01

Unmanned aerial vehicle (UAV) remote imaging is affected by the bad weather, and the obtained images have the disadvantages of low contrast, complex texture and blurring. In this paper, we propose a blind deconvolution model based on multiple scattering atmosphere point spread function (APSF) estimation to recovery the remote sensing image. According to Narasimhan analytical theory, a new multiple scattering restoration model is established based on the improved dichromatic model. Then using the L0 norm sparse priors of gradient and dark channel to estimate APSF blur kernel, the fast Fourier transform is used to recover the original clear image by Wiener filtering. By comparing with other state-of-the-art methods, the proposed method can correctly estimate blur kernel, effectively remove the atmospheric degradation phenomena, preserve image detail information and increase the quality evaluation indexes.

Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery

NASA Astrophysics Data System (ADS)

Ma, Lei; Cheng, Liang; Li, Manchun; Liu, Yongxue; Ma, Xiaoxue

2015-04-01

Unmanned Aerial Vehicle (UAV) has been used increasingly for natural resource applications in recent years due to their greater availability and the miniaturization of sensors. In addition, Geographic Object-Based Image Analysis (GEOBIA) has received more attention as a novel paradigm for remote sensing earth observation data. However, GEOBIA generates some new problems compared with pixel-based methods. In this study, we developed a strategy for the semi-automatic optimization of object-based classification, which involves an area-based accuracy assessment that analyzes the relationship between scale and the training set size. We found that the Overall Accuracy (OA) increased as the training set ratio (proportion of the segmented objects used for training) increased when the Segmentation Scale Parameter (SSP) was fixed. The OA increased more slowly as the training set ratio became larger and a similar rule was obtained according to the pixel-based image analysis. The OA decreased as the SSP increased when the training set ratio was fixed. Consequently, the SSP should not be too large during classification using a small training set ratio. By contrast, a large training set ratio is required if classification is performed using a high SSP. In addition, we suggest that the optimal SSP for each class has a high positive correlation with the mean area obtained by manual interpretation, which can be summarized by a linear correlation equation. We expect that these results will be applicable to UAV imagery classification to determine the optimal SSP for each class.

Canadair CL-227 Remotely Piloted Vehicle

NASA Astrophysics Data System (ADS)

Clark, Andrew S.

1983-08-01

The Canadair CL-227 is a rotary winged Remotely Piloted Vehicle (RPV) intended initially as the air-vehicle for a medium range battlefield surveillance and target acquisition system. The concept on which this vehicle is based brings together in-house expertise as a designer and manufacturer of surveillance drones (AN-USD-50l -MIDGE-) with experience in rigid rotor technology from the CL-84 tilt wing VTOL program. The vehicle is essentially modular in design with a power module containing the engine, fuel and related systems, a rotor module containing the two counter-rotating rotors and control actuators, and a control module containing the autopilot, data link and sensor system. The vehicle is a true RPV (as opposed to a drone) as it is flown in real time by an operator on the ground and requires relatively little skill to pilot.

UFCN: a fully convolutional neural network for road extraction in RGB imagery acquired by remote sensing from an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Kestur, Ramesh; Farooq, Shariq; Abdal, Rameen; Mehraj, Emad; Narasipura, Omkar; Mudigere, Meenavathi

2018-01-01

Road extraction in imagery acquired by low altitude remote sensing (LARS) carried out using an unmanned aerial vehicle (UAV) is presented. LARS is carried out using a fixed wing UAV with a high spatial resolution vision spectrum (RGB) camera as the payload. Deep learning techniques, particularly fully convolutional network (FCN), are adopted to extract roads by dense semantic segmentation. The proposed model, UFCN (U-shaped FCN) is an FCN architecture, which is comprised of a stack of convolutions followed by corresponding stack of mirrored deconvolutions with the usage of skip connections in between for preserving the local information. The limited dataset (76 images and their ground truths) is subjected to real-time data augmentation during training phase to increase the size effectively. Classification performance is evaluated using precision, recall, accuracy, F1 score, and brier score parameters. The performance is compared with support vector machine (SVM) classifier, a one-dimensional convolutional neural network (1D-CNN) model, and a standard two-dimensional CNN (2D-CNN). The UFCN model outperforms the SVM, 1D-CNN, and 2D-CNN models across all the performance parameters. Further, the prediction time of the proposed UFCN model is comparable with SVM, 1D-CNN, and 2D-CNN models.

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.

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.

Mobile remote manipulator vehicle system

NASA Technical Reports Server (NTRS)

Bush, Harold G. (Inventor); Mikulas, Martin M., Jr. (Inventor); Wallsom, Richard E. (Inventor); Jensen, J. Kermit (Inventor)

1987-01-01

A mobile remote manipulator system is disclosed for assembly, repair and logistics transport on, around and about a space station square bay truss structure. The vehicle is supported by a square track arrangement supported by guide pins integral with the space station truss structure and located at each truss node. Propulsion is provided by a central push-pull drive mechanism that extends out from the vehicle one full structural bay over the truss and locks drive rods into the guide pins. The draw bar is now retracted and the mobile remote manipulator system is pulled onto the next adjacent structural bay. Thus, translation of the vehicle is inchworm style. The drive bar can be locked onto two guide pins while the extendable draw bar is within the vehicle and then push the vehicle away one bay providing bidirectional push-pull drive. The track switches allow the vehicle to travel in two orthogonal directions over the truss structure which coupled with the bidirectional drive, allow movement in four directions on one plane. The top layer of this trilayered vehicle is a logistics platform. This platform is capable of 369 degees of rotation and will have two astronaut foot restraint platforms and a space crane integral.

Cost and effectiveness analysis on unmanned aerial vehicle (UAV) use at border security

NASA Astrophysics Data System (ADS)

Yilmaz, Bahadır.

2013-06-01

Drones and Remotely Piloted Vehicles are types of Unmanned Aerial Vehicles. UAVs began to be used with the war of Vietnam, they had a great interest when Israel used them in Bekaa Valley Operations of 1982. UAVs have been used by different countries with different aims with the help of emerging technology and investments. In this article, in the context of areas of UAV usage in national security, benefits and disadvantages of UAVs are put forward. Particularly, it has been evaluated on the basis of cost-effectiveness by focusing the use of UAV in the border security. UAVs have been studied by taking cost analysis, procurement and operational costs into consideration. Analysis of effectiveness has been done with illegal passages of people and drugs from flight times of UAVs. Although the procurement cost of the medium-level UAVs is low, its operational costs are high. For this reason, the idea of less costly alternative systems have been revealed for the border security. As the costs are reduced to acceptable level involving national security and border security in future with high-technology products in their structure, it will continue to be used in an increasing proportion.

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.

Survey on the novel hybrid aquatic-aerial amphibious aircraft: Aquatic unmanned aerial vehicle (AquaUAV)

NASA Astrophysics Data System (ADS)

Yang, Xingbang; Wang, Tianmiao; Liang, Jianhong; Yao, Guocai; Liu, Miao

2015-04-01

The aquatic unmanned aerial vehicle (AquaUAV), a kind of vehicle that can operate both in the air and the water, has been regarded as a new breakthrough to broaden the application scenario of UAV. Wide application prospects in military and civil field are more than bright, therefore many institutions have focused on the development of such a vehicle. However, due to the significant difference of the physical properties between the air and the water, it is rather difficult to design a fully-featured AquaUAV. Until now, majority of partially-featured AquaUAVs have been developed and used to verify the feasibility of an aquatic-aerial vehicle. In the present work, we classify the current partially-featured AquaUAV into three categories from the scope of the whole UAV field, i.e., the seaplane UAV, the submarine-launched UAV, and the submersible UAV. Then the recent advancements and common characteristics of the three kinds of AquaUAVs are reviewed in detail respectively. Then the applications of bionics in the design of AquaUAV, the transition mode between the air and the water, the morphing wing structure for air-water adaptation, and the power source and the propulsion type are summarized and discussed. The tradeoff analyses for different transition methods between the air and the water are presented. Furthermore, it indicates that applying the bionics into the design and development of the AquaUAV will be essential and significant. Finally, the significant technical challenges for the AquaUAV to change from a conception to a practical prototype are indicated.

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.

A new framework for UAV-based remote sensing data processing and its application in almond water stress quantification

USDA-ARS?s Scientific Manuscript database

With the rapid development of small imaging sensors and unmanned aerial vehicles (UAVs), remote sensing is undergoing a revolution with greatly increased spatial and temporal resolutions. While more relevant detail becomes available, it is a challenge to analyze the large number of images to extract...

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.

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.

In situ Volcanic Plume Monitoring with small Unmanned Aerial Systems for Cal/Val of Satellite Remote Sensing Data: CARTA-UAV 2013 Mission (Invited)

NASA Astrophysics Data System (ADS)

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

2013-12-01

The development of small unmanned aerial systems (sUAS) with a variety of sensor packages, enables in situ and proximal remote sensing measurements of volcanic plumes. Using Costa Rican volcanoes as a Natural Laboratory, the University of Costa Rica as host institution, in collaboration with four NASA centers, have started an initiative to develop low-cost, field-deployable airborne platforms to perform volcanic gas & ash plume research, and in-situ volcanic monitoring in general, in conjunction with orbital assets and state-of-the-art models of plume transport and composition. Several gas sensors have been deployed into the active plume of Turrialba Volcano including a miniature mass spectrometer, and an electrochemical SO2 sensor system with temperature, pressure, relative humidity, and GPS sensors. Several different airborne platforms such as manned research aircraft, unmanned aerial vehicles, tethered balloons, as well as man-portable in-situ ground truth systems are being used for this research. Remote sensing data is also collected from the ASTER and OMI spaceborne instruments and compared with in situ data. The CARTA-UAV 2013 Mission deployment and follow up measurements successfully demonstrated a path to study and visualize gaseous volcanic emissions using mass spectrometer and gas sensor based instrumentation in harsh environment conditions to correlate in situ ground/airborne data with remote sensing satellite data for calibration and validation purposes. The deployment of such technology improves on our current capabilities to detect, analyze, monitor, model, and predict hazards presented to aircraft by volcanogenic ash clouds from active and impending volcanic eruptions.

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.

Transition aerodynamics for 20-percent-scale VTOL unmanned aerial vehicle

NASA Technical Reports Server (NTRS)

Kjerstad, Kevin J.; Paulson, John W., Jr.

1993-01-01

An investigation was conducted in the Langley 14- by 22-Foot Subsonic Tunnel to establish a transition data base for an unmanned aerial vehicle utilizing a powered-lift ejector system and to evaluate alterations to the ejector system for improved vehicle performance. The model used in this investigation was a 20-percent-scale, blended-body, arrow-wing configuration with integrated twin rectangular ejectors. The test was conducted from hover through transition conditions with variations in angle of attack, angle of sideslip, free-stream dynamic pressure, nozzle pressure ratio, and model ground height. Force and moment data along with extensive surface pressure data were obtained. A laser velocimeter technique for measuring inlet flow velocities was demonstrated at a single flow condition, and also a low order panel method was successfully used to numerically simulate the ejector inlet flow.

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.

Remotely Piloted Life-Saving Effort vehicles and emergency management: An analysis on revolutionizing humanitarian assistance in Pakistan.

PubMed

Nadeem, Ali Bin; Chandna, Ysa

The majority of the Pakistani public has known little of the unmanned aerial vehicles, also known for their onomatopoeically inspired name "drones," except the fact that it regularly rains Hellfire missiles in Pakistan, claiming the lives of many innocent Pakistanis settled in the western provinces. In actuality, in addition to their destructive capacities, these remotely piloted vehicles have been used since the turn of the century in a variety of live-saving and risk-reducing roles. This research article primarily addresses the third stage of Emergency management-response, with Pakistan being the primary region of research. This research article will first begin by diagnosing and accurately delineating the types of humanitarian crisis that grip Pakistan, devastating its land, exhausting its limited resources in its weak, and now almost archaic, disaster response strategy that results in the prolongation of its citizens' plight. Subsequently, this article will describe the history of the usage of unmanned vehicles, its multi-functional capacities, and its relevance in aiding humanitarian response efforts in disaster-stricken areas. Finally, this article will propose the introduction of Remotely Piloted Life-Saving Effort (RELIEF) vehicles in performing analysis and surveillance roles in Pakistan's disaster-prone and disaster-struck areas and its capacity to dramatically improve and expedite the existing relief supply delivery systems in place.

Sediment Sampling in Estuarine Mudflats with an Aerial-Ground Robotic Team

PubMed Central

Deusdado, Pedro; Guedes, Magno; Silva, André; Marques, Francisco; Pinto, Eduardo; Rodrigues, Paulo; Lourenço, André; Mendonça, Ricardo; Santana, Pedro; Corisco, José; Almeida, Susana Marta; Portugal, Luís; Caldeira, Raquel; Barata, José; Flores, Luis

2016-01-01

This paper presents a robotic team suited for bottom sediment sampling and retrieval in mudflats, targeting environmental monitoring tasks. The robotic team encompasses a four-wheel-steering ground vehicle, equipped with a drilling tool designed to be able to retain wet soil, and a multi-rotor aerial vehicle for dynamic aerial imagery acquisition. On-demand aerial imagery, properly fused on an aerial mosaic, is used by remote human operators for specifying the robotic mission and supervising its execution. This is crucial for the success of an environmental monitoring study, as often it depends on human expertise to ensure the statistical significance and accuracy of the sampling procedures. Although the literature is rich on environmental monitoring sampling procedures, in mudflats, there is a gap as regards including robotic elements. This paper closes this gap by also proposing a preliminary experimental protocol tailored to exploit the capabilities offered by the robotic system. Field trials in the south bank of the river Tagus’ estuary show the ability of the robotic system to successfully extract and transport bottom sediment samples for offline analysis. The results also show the efficiency of the extraction and the benefits when compared to (conventional) human-based sampling. PMID:27618060

Design and implementation of a remote UAV-based mobile health monitoring system

NASA Astrophysics Data System (ADS)

Li, Songwei; Wan, Yan; Fu, Shengli; Liu, Mushuang; Wu, H. Felix

2017-04-01

Unmanned aerial vehicles (UAVs) play increasing roles in structure health monitoring. With growing mobility in modern Internet-of-Things (IoT) applications, the health monitoring of mobile structures becomes an emerging application. In this paper, we develop a UAV-carried vision-based monitoring system that allows a UAV to continuously track and monitor a mobile infrastructure and transmit back the monitoring information in real- time from a remote location. The monitoring system uses a simple UAV-mounted camera and requires only a single feature located on the mobile infrastructure for target detection and tracking. The computation-effective vision-based tracking solution based on a single feature is an improvement over existing vision-based lead-follower tracking systems that either have poor tracking performance due to the use of a single feature, or have improved tracking performance at a cost of the usage of multiple features. In addition, a UAV-carried aerial networking infrastructure using directional antennas is used to enable robust real-time transmission of monitoring video streams over a long distance. Automatic heading control is used to self-align headings of directional antennas to enable robust communication in mobility. Compared to existing omni-communication systems, the directional communication solution significantly increases the operation range of remote monitoring systems. In this paper, we develop the integrated modeling framework of camera and mobile platforms, design the tracking algorithm, develop a testbed of UAVs and mobile platforms, and evaluate system performance through both simulation studies and field tests.

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.

AERIAL SHOWING COMPLETED REMOTE ANALYTICAL FACILITY (CPP627) ADJOINING FUEL PROCESSING ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

AERIAL SHOWING COMPLETED REMOTE ANALYTICAL FACILITY (CPP-627) ADJOINING FUEL PROCESSING BUILDING AND EXCAVATION FOR HOT PILOT PLANT TO RIGHT (CPP-640). INL PHOTO NUMBER NRTS-60-1221. J. Anderson, Photographer, 3/22/1960 - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

Multi-resource data-based research on remote sensing monitoring over the green tide in the Yellow Sea

NASA Astrophysics Data System (ADS)

Gao, Zhiqiang; Xu, Fuxiang; Song, Debin; Zheng, Xiangyu; Chen, Maosi

2017-09-01

This paper conducted dynamic monitoring over the green tide (large green alga—Ulva prolifera) occurred in the Yellow Sea in 2014 to 2016 by the use of multi-source remote sensing data, including GF-1 WFV, HJ-1A/1B CCD, CBERS-04 WFI, Landsat-7 ETM+ and Landsta-8 OLI, and by the combination of VB-FAH (index of Virtual-Baseline Floating macroAlgae Height) with manual assisted interpretation based on remote sensing and geographic information system technologies. The result shows that unmanned aerial vehicle (UAV) and shipborne platform could accurately monitor the distribution of Ulva prolifera in small spaces, and therefore provide validation data for the result of remote sensing monitoring over Ulva prolifera. The result of this research can provide effective information support for the prevention and control of Ulva prolifera.

Fuzzy C-Means Algorithm for Segmentation of Aerial Photography Data Obtained Using Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Akinin, M. V.; Akinina, N. V.; Klochkov, A. Y.; Nikiforov, M. B.; Sokolova, A. V.

2015-05-01

The report reviewed the algorithm fuzzy c-means, performs image segmentation, give an estimate of the quality of his work on the criterion of Xie-Beni, contain the results of experimental studies of the algorithm in the context of solving the problem of drawing up detailed two-dimensional maps with the use of unmanned aerial vehicles. According to the results of the experiment concluded that the possibility of applying the algorithm in problems of decoding images obtained as a result of aerial photography. The considered algorithm can significantly break the original image into a plurality of segments (clusters) in a relatively short period of time, which is achieved by modification of the original k-means algorithm to work in a fuzzy task.

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.

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

Remotely Accessed Vehicle Traffic Management System

NASA Astrophysics Data System (ADS)

Al-Alawi, Raida

2010-06-01

The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.

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

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.

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

Remotely detected vehicle mass from engine torque-induced frame twisting

DOE PAGES

McKay, Troy R.; Salvaggio, Carl; Faulring, Jason W.; ...

2017-06-08

Determining the mass of a vehicle from ground-based passive sensor data is important for many traffic safety requirements. This paper presents a method for calculating the mass of a vehicle using ground-based video and acoustic measurements. By assuming that no energy is lost in the conversion, the mass of a vehicle can be calculated from the rotational energy generated by the vehicle’s engine and the linear acceleration of the vehicle over a period of time. The amount of rotational energy being output by the vehicle’s engine can be calculated from its torque and angular velocity. This model relates remotely observed,more » engine torque-induced frame twist to engine torque output using the vehicle’s suspension parameters and engine geometry. The angular velocity of the engine is extracted from the acoustic emission of the engine, and the linear acceleration of the vehicle is calculated by remotely observing the position of the vehicle over time. This method combines these three dynamic signals; engine induced-frame twist, engine angular velocity, and the vehicle’s linear acceleration, and three vehicle specific scalar parameters, into an expression that describes the mass of the vehicle. Finally, this method was tested on a semitrailer truck, and the results demonstrate a correlation of 97.7% between calculated and true vehicle mass.« less

Remotely detected vehicle mass from engine torque-induced frame twisting

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

McKay, Troy R.; Salvaggio, Carl; Faulring, Jason W.

Determining the mass of a vehicle from ground-based passive sensor data is important for many traffic safety requirements. This paper presents a method for calculating the mass of a vehicle using ground-based video and acoustic measurements. By assuming that no energy is lost in the conversion, the mass of a vehicle can be calculated from the rotational energy generated by the vehicle’s engine and the linear acceleration of the vehicle over a period of time. The amount of rotational energy being output by the vehicle’s engine can be calculated from its torque and angular velocity. This model relates remotely observed,more » engine torque-induced frame twist to engine torque output using the vehicle’s suspension parameters and engine geometry. The angular velocity of the engine is extracted from the acoustic emission of the engine, and the linear acceleration of the vehicle is calculated by remotely observing the position of the vehicle over time. This method combines these three dynamic signals; engine induced-frame twist, engine angular velocity, and the vehicle’s linear acceleration, and three vehicle specific scalar parameters, into an expression that describes the mass of the vehicle. Finally, this method was tested on a semitrailer truck, and the results demonstrate a correlation of 97.7% between calculated and true vehicle mass.« less

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

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

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

Operator Selection for Unmanned Aerial Vehicle Operators: A Comparison of Video Game Players and Manned Aircraft Pilots

DTIC Science & Technology

2009-11-01

AFRL-RH-WP-TR-2010-0057 Operator Selection for Unmanned Aerial Vehicle Operators: A Comparison of Video Game Players and Manned Aircraft...Oct-2008 - 30-Nov-2009 4. TITLE AND SUBTITLE Operator Selection for Unmanned Aerial Vehicle Operators: A Comparison of Video Game Players...training regimens leading to a potential shortage of qualified UAS pilots. This study attempted to discover whether video game players (VGPs) possess

Quantitative extraction of the bedrock exposure rate based on unmanned aerial vehicle data and Landsat-8 OLI image in a karst environment

NASA Astrophysics Data System (ADS)

Wang, Hongyan; Li, Qiangzi; Du, Xin; Zhao, Longcai

2017-12-01

In the karst regions of southwest China, rocky desertification is one of the most serious problems in land degradation. The bedrock exposure rate is an important index to assess the degree of rocky desertification in karst regions. Because of the inherent merits of macro-scale, frequency, efficiency, and synthesis, remote sensing is a promising method to monitor and assess karst rocky desertification on a large scale. However, actual measurement of the bedrock exposure rate is difficult and existing remote-sensing methods cannot directly be exploited to extract the bedrock exposure rate owing to the high complexity and heterogeneity of karst environments. Therefore, using unmanned aerial vehicle (UAV) and Landsat-8 Operational Land Imager (OLI) data for Xingren County, Guizhou Province, quantitative extraction of the bedrock exposure rate based on multi-scale remote-sensing data was developed. Firstly, we used an object-oriented method to carry out accurate classification of UAVimages. From the results of rock extraction, the bedrock exposure rate was calculated at the 30 m grid scale. Parts of the calculated samples were used as training data; other data were used for model validation. Secondly, in each grid the band reflectivity of Landsat-8 OLI data was extracted and a variety of rock and vegetation indexes (e.g., NDVI and SAVI) were calculated. Finally, a network model was established to extract the bedrock exposure rate. The correlation coefficient of the network model was 0.855, that of the validation model was 0.677 and the root mean square error of the validation model was 0.073. This method is valuable for wide-scale estimation of bedrock exposure rate in karst environments. Using the quantitative inversion model, a distribution map of the bedrock exposure rate in Xingren County was obtained.

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.

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.

Development of wireless vehicle remote control for fuel lid operation

NASA Astrophysics Data System (ADS)

Sulaiman, N.; Jadin, M. S.; Najib, M. S.; Mustafa, M.; Azmi, S. N. F.

2018-04-01

Nowadays, the evolution of the vehicle technology had made the vehicle especially car to be equipped with a remote control to control the operation of the locking and unlocking system of the car’s door and rear’s bonnet. However, for the fuel or petrol lid, it merely can be opened from inside the car’s cabin by handling the fuel level inside the car’s cabin to open the fuel lid. The petrol lid can be closed by pushing the lid by hand. Due to the high usage of using fuel lever to open the fuel lid when refilling the fuel, the car driver might encounter the malfunction of fuel lid (fail to open) when pushing or pulling the fuel lever. Thus, the main aim of the research is to enhance the operation of an existing car remote control where the car fuel lid can be controlled using two techniques; remote control-based and smartphone-based. The remote control is constructed using Arduino microcontroller, wireless sensors and XCTU software to set the transmitting and receiving parameters. Meanwhile, the smartphone can control the operation of the fuel lid by communicating with Arduino microcontroller which is attached to the fuel lid using Bluetooth sensor to open the petrol lid. In order to avoid the conflict of instruction between wireless systems with the existing mechanical-based system, the servo motor will be employed to release the fuel lid merely after receiving the instruction from Arduino microcontroller and smartphone. As a conclusion, the prototype of the multipurpose vehicle remote control is successfully invented, constructed and tested. The car fuel lid can be opened either using remote control or smartphone in a sequential manner. Therefore, the outcome of the project can be used to serve as an alternative solution to solve the car fuel lid problem even though the problem rarely occurred.

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.

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.

Swarming Unmanned Aerial Vehicles (UAVS): Extending Marine Aviation Ground Task Force Communications Using UAVS

DTIC Science & Technology

2015-03-02

balloons , large UAVs, and satellite communications are all employed to mitigate LOS and OTH communication on the battlefield. The Marine Corps’ fleets...Phang, N. S. (2006). Tethered operation of autonomous aerial vehicles to provide extended fields of view for autonomous ground vehicles (Master’s

Micro-aerial vehicle type wall-climbing robot mechanism for structural health monitoring

NASA Astrophysics Data System (ADS)

Shin, Jae-Uk; Kim, Donghoon; Kim, Jong-Heon; Myung, Hyun

2013-04-01

Currently, the maintenance or inspection of large structures is labor-intensive, so it has a problem of the large cost due to the staffing professionals and the risk for hard to reach areas. To solve the problem, the needs of wall-climbing robot are emerged. Infra-based wall-climbing robots to maintain an outer wall of building have high payload and safety. However, the infrastructure for the robot must be equipped on the target structure and the infrastructure isn't preferred by the architects since it can injure the exterior of the structure. These are the reasons of why the infra-based wall-climbing robot is avoided. In case of the non-infra-based wall-climbing robot, it is researched to overcome the aforementioned problems. However, most of the technologies are in the laboratory level since the payload, safety and maneuverability are not satisfactory. For this reason, aerial vehicle type wall-climbing robot is researched. It is a flying possible wallclimbing robot based on a quadrotor. It is a famous aerial vehicle robot using four rotors to make a thrust for flying. This wall-climbing robot can stick to a vertical wall using the thrust. After sticking to the wall, it can move with four wheels installed on the robot. As a result, it has high maneuverability and safety since it can restore the position to the wall even if it is detached from the wall by unexpected disturbance while climbing the wall. The feasibility of the main concept was verified through simulations and experiments using a prototype.

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

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.

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.

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.

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.

Remote operated vehicle with carbon dioxide blasting (ROVCO{sub 2})

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

Resnick, A.M.

The Remote Operated Vehicle with Carbon Dioxide Blasting (ROVCO{sub 2}), as shown in a front view, is a six-wheeled remote land vehicle used to decontaminate concrete floors. The remote vehicle has a high pressure Cryogenesis blasting subsystem, Oceaneering Technologies (OTECH) developed a CO{sub 2} xY Orthogonal Translational End Effector (COYOTEE) subsystem, and a vacuum/filtration and containment subsystem. Figure 2 shows a block diagram with the various subsystems labeled.

Flexible Wing Base Micro Aerial Vehicles: Vision-Guided Flight Stability and Autonomy for Micro Air Vehicles

NASA Technical Reports Server (NTRS)

Ettinger, Scott M.; Nechyba, Michael C.; Ifju, Peter G.; Wazak, Martin

2002-01-01

Substantial progress has been made recently towards design building and test-flying remotely piloted Micro Air Vehicle's (MAVs). We seek to complement this progress in overcoming the aerodynamic obstacles to.flight at very small scales with a vision stability and autonomy system. The developed system based on a robust horizon detection algorithm which we discuss in greater detail in a companion paper. In this paper, we first motivate the use of computer vision for MAV autonomy arguing that given current sensor technology, vision may he the only practical approach to the problem. We then briefly review our statistical vision-based horizon detection algorithm, which has been demonstrated at 30Hz with over 99.9% correct horizon identification. Next we develop robust schemes for the detection of extreme MAV attitudes, where no horizon is visible, and for the detection of horizon estimation errors, due to external factors such as video transmission noise. Finally, we discuss our feed-back controller for self-stabilized flight, and report results on vision autonomous flights of duration exceeding ten minutes.

The DAST-1 remotely piloted research vehicle development and initial flight testing

NASA Technical Reports Server (NTRS)

Kotsabasis, A.

1981-01-01

The development and initial flight testing of the DAST (drones for aerodynamic and structural testing) remotely piloted research vehicle, fitted with the first aeroelastic research wing ARW-I are presented. The ARW-I is a swept supercritical wing, designed to exhibit flutter within the vehicle's flight envelope. An active flutter suppression system (FSS) designed to increase the ARW-I flutter boundary speed by 20 percent is described. The development of the FSS was based on prediction techniques of structural and unsteady aerodynamic characteristics. A description of the supporting ground facilities and aircraft systems involved in the remotely piloted research vehicle (RPRV) flight test technique is given. The design, specification, and testing of the remotely augmented vehicle system are presented. A summary of the preflight and flight test procedures associated with the RPRV operation is given. An evaluation of the blue streak test flight and the first and second ARW-I test flights is presented.

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

Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

NASA Astrophysics Data System (ADS)

Booth, D. Terrance; Cox, Samuel E.; Meikle, Tim; Zuuring, Hans R.

2008-12-01

Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than 3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.

The hybrid bio-inspired aerial vehicle: Concept and SIMSCAPE flight simulation.

PubMed

Tao Zhang; Su, Steven; Nguyen, Hung T

2016-08-01

This paper introduces a Silver Gull-inspired hybrid aerial vehicle, the Super Sydney Silver Gull (SSSG), which is able to vary its structure, under different manoeuvre requirements, to implement three flight modes: the flapping wing flight, the fixed wing flight, and the quadcopter flight (the rotary wing flight of Unmanned Air Vehicle). Specifically, through proper mechanism design and flight mode transition, the SSSG can imitate the Silver Gull's flight gesture during flapping flight, save power consuming by switching to the fixed wing flight mode during long-range cruising, and hover at targeted area when transferring to quadcopter flight mode. Based on the aerodynamic models, the Simscape, a product of MathWorks, is used to simulate and analyse the performance of the SSSG's flight modes. The entity simulation results indicate that the created SSSG's 3D model is feasible and ready to be manufactured for further flight tests.

Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor.

PubMed

Nguyen, Phong Ha; Kim, Ki Wan; Lee, Young Won; Park, Kang Ryoung

2017-08-30

Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.

Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor

PubMed Central

Nguyen, Phong Ha; Kim, Ki Wan; Lee, Young Won; Park, Kang Ryoung

2017-01-01

Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments. PMID:28867775

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.

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.

Search and Pursuit with Unmanned Aerial Vehicles in Road Networks

DTIC Science & Technology

2013-11-01

production volume in each area for use in consumer electronics. Simultaneously, a shift in defense strategy towards unmanned vehicles, particularly...Vöcking. Randomized pursuit-evasion in graphs. Combinatorics, Probability and Computing, 12:225–244, May 2003. [3] AeroVironment Inc. Raven Product Data...Ali and Mubarak Shah. COCOA - tracking in aerial imagery. In SPIE Airborne Intelligence, Surveillance, Reconnaissance Systems and Applications, 2006

Spatiotemporal Local-Remote Senor Fusion (ST-LRSF) for Cooperative Vehicle Positioning.

PubMed

Jeong, Han-You; Nguyen, Hoa-Hung; Bhawiyuga, Adhitya

2018-04-04

Vehicle positioning plays an important role in the design of protocols, algorithms, and applications in the intelligent transport systems. In this paper, we present a new framework of spatiotemporal local-remote sensor fusion (ST-LRSF) that cooperatively improves the accuracy of absolute vehicle positioning based on two state estimates of a vehicle in the vicinity: a local sensing estimate, measured by the on-board exteroceptive sensors, and a remote sensing estimate, received from neighbor vehicles via vehicle-to-everything communications. Given both estimates of vehicle state, the ST-LRSF scheme identifies the set of vehicles in the vicinity, determines the reference vehicle state, proposes a spatiotemporal dissimilarity metric between two reference vehicle states, and presents a greedy algorithm to compute a minimal weighted matching (MWM) between them. Given the outcome of MWM, the theoretical position uncertainty of the proposed refinement algorithm is proven to be inversely proportional to the square root of matching size. To further reduce the positioning uncertainty, we also develop an extended Kalman filter model with the refined position of ST-LRSF as one of the measurement inputs. The numerical results demonstrate that the proposed ST-LRSF framework can achieve high positioning accuracy for many different scenarios of cooperative vehicle positioning.

Spatiotemporal Local-Remote Senor Fusion (ST-LRSF) for Cooperative Vehicle Positioning

PubMed Central

Bhawiyuga, Adhitya

2018-01-01

Vehicle positioning plays an important role in the design of protocols, algorithms, and applications in the intelligent transport systems. In this paper, we present a new framework of spatiotemporal local-remote sensor fusion (ST-LRSF) that cooperatively improves the accuracy of absolute vehicle positioning based on two state estimates of a vehicle in the vicinity: a local sensing estimate, measured by the on-board exteroceptive sensors, and a remote sensing estimate, received from neighbor vehicles via vehicle-to-everything communications. Given both estimates of vehicle state, the ST-LRSF scheme identifies the set of vehicles in the vicinity, determines the reference vehicle state, proposes a spatiotemporal dissimilarity metric between two reference vehicle states, and presents a greedy algorithm to compute a minimal weighted matching (MWM) between them. Given the outcome of MWM, the theoretical position uncertainty of the proposed refinement algorithm is proven to be inversely proportional to the square root of matching size. To further reduce the positioning uncertainty, we also develop an extended Kalman filter model with the refined position of ST-LRSF as one of the measurement inputs. The numerical results demonstrate that the proposed ST-LRSF framework can achieve high positioning accuracy for many different scenarios of cooperative vehicle positioning. PMID:29617341

Melon yield prediction using small unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Zhao, Tiebiao; Wang, Zhongdao; Yang, Qi; Chen, YangQuan

2017-05-01

Thanks to the development of camera technologies, small unmanned aerial systems (sUAS), it is possible to collect aerial images of field with more flexible visit, higher resolution and much lower cost. Furthermore, the performance of objection detection based on deeply trained convolutional neural networks (CNNs) has been improved significantly. In this study, we applied these technologies in the melon production, where high-resolution aerial images were used to count melons in the field and predict the yield. CNN-based object detection framework-Faster R-CNN is applied in the melon classification. Our results showed that sUAS plus CNNs were able to detect melons accurately in the late harvest season.

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.

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

PubMed Central

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. PMID:26393926

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

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.

Applicability of New Approaches of Sensor Orientation to Micro Aerial Vehicles

NASA Astrophysics Data System (ADS)

Rehak, M.; Skaloud, J.

2016-06-01

This study highlights the benefits of precise aerial position and attitude control in the context of mapping with Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline inspections or mapping of large areas with homogeneous surface structure, e.g. forests or agricultural fields. There, accurate aerial control plays a major role in successful terrain reconstruction and artifact-free ortophoto generation. The presented experiments focus on new approaches of aerial control. We confirm practically that the relative aerial position and attitude control can improve accuracy in difficult mapping scenarios. Indeed, the relative orientation method represents an attractive alternative in the context of MAVs for two reasons. First, the procedure is somewhat simplified, e.g. the angular misalignment, so called boresight, between the camera and the inertial measurement unit (IMU) does not have to be determined and, second, the effect of possible systematic errors in satellite positioning (e.g. due to multipath and/or incorrect recovery of differential carrier-phase ambiguities) is mitigated. First, we present a typical mapping project over an agricultural field and second, we perform a corridor road mapping. We evaluate the proposed methods in scenarios with and without automated image observations. We investigate a recently proposed concept where adjustment is performed using image observations limited to ground control and check points, so called fast aerial triangulation (Fast AT). In this context we show that accurate aerial control (absolute or relative) together with a few image observations can deliver accurate results comparable to classical aerial triangulation with thousands of image measurements. This procedure in turns reduces the demands on processing time and the requirements on the existence of surface texture. Finally, we compare the above mentioned procedures with direct sensor

Aerial Explorers

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Greg; Ippolito, Corey

2005-01-01

This paper presents recent results from a mission architecture study of planetary aerial explorers. In this study, several mission scenarios were developed in simulation and evaluated on success in meeting mission goals. This aerial explorer mission architecture study is unique in comparison with previous Mars airplane research activities. The study examines how aerial vehicles can find and gain access to otherwise inaccessible terrain features of interest. The aerial explorer also engages in a high-level of (indirect) surface interaction, despite not typically being able to takeoff and land or to engage in multiple flights/sorties. To achieve this goal, a new mission paradigm is proposed: aerial explorers should be considered as an additional element in the overall Entry, Descent, Landing System (EDLS) process. Further, aerial vehicles should be considered primarily as carrier/utility platforms whose purpose is to deliver air-deployed sensors and robotic devices, or symbiotes, to those high-value terrain features of interest.

Monitoring the Invasion of Spartina alterniflora Using Very High Resolution Unmanned Aerial Vehicle Imagery in Beihai, Guangxi (China)

PubMed Central

Wan, Huawei; Wang, Qiao; Jiang, Dong; Yang, Yipeng; Liu, Xiaoman

2014-01-01

Spartina alterniflora was introduced to Beihai, Guangxi (China), for ecological engineering purposes in 1979. However, the exceptional adaptability and reproductive ability of this species have led to its extensive dispersal into other habitats, where it has had a negative impact on native species and threatens the local mangrove and mudflat ecosystems. To obtain the distribution and spread of Spartina alterniflora, we collected HJ-1 CCD imagery from 2009 and 2011 and very high resolution (VHR) imagery from the unmanned aerial vehicle (UAV). The invasion area of Spartina alterniflora was 357.2 ha in 2011, which increased by 19.07% compared with the area in 2009. A field survey was conducted for verification and the total accuracy was 94.0%. The results of this paper show that VHR imagery can provide details on distribution, progress, and early detection of Spartina alterniflora invasion. OBIA, object based image analysis for remote sensing (RS) detection method, can enable control measures to be more effective, accurate, and less expensive than a field survey of the invasive population. PMID:24892066

Monitoring the invasion of Spartina alterniflora using very high resolution unmanned aerial vehicle imagery in Beihai, Guangxi (China).

PubMed

Wan, Huawei; Wang, Qiao; Jiang, Dong; Fu, Jingying; Yang, Yipeng; Liu, Xiaoman

2014-01-01

Spartina alterniflora was introduced to Beihai, Guangxi (China), for ecological engineering purposes in 1979. However, the exceptional adaptability and reproductive ability of this species have led to its extensive dispersal into other habitats, where it has had a negative impact on native species and threatens the local mangrove and mudflat ecosystems. To obtain the distribution and spread of Spartina alterniflora, we collected HJ-1 CCD imagery from 2009 and 2011 and very high resolution (VHR) imagery from the unmanned aerial vehicle (UAV). The invasion area of Spartina alterniflora was 357.2 ha in 2011, which increased by 19.07% compared with the area in 2009. A field survey was conducted for verification and the total accuracy was 94.0%. The results of this paper show that VHR imagery can provide details on distribution, progress, and early detection of Spartina alterniflora invasion. OBIA, object based image analysis for remote sensing (RS) detection method, can enable control measures to be more effective, accurate, and less expensive than a field survey of the invasive population.

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.

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.

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.

Using Unmanned Aerial Vehicles (UAVs) to Modeling Tornado Impacts

NASA Astrophysics Data System (ADS)

Wagner, M.; Doe, R. K.

2017-12-01

Using Unmanned Aerial Vehicles (UAVs) to assess storm damage is a useful research tool. Benefits include their ability to access remote or impassable areas post-storm, identify unknown damages and assist with more detailed site investigations and rescue efforts. Technological advancement of UAVs mean that they can capture high resolution images often at an affordable price. These images can be used to create 3D environments to better interpret and delineate damages from large areas that would have been difficult in ground surveys. This research presents the results of a rapid response site investigation of the 29 April 2017 Canton, Texas, USA, tornado using low cost UAVs. This was a multiple, high impact tornado event measuring EF4 at maximum. Rural farmland was chosen as a challenging location to test both equipment and methodology. Such locations provide multiple impacts at a variety of scales including structural and vegetation damage and even animal fatalities. The 3D impact models allow for a more comprehensive study prior to clean-up. The results show previously unseen damages and better quantify damage impacts at the local level. 3D digital track swaths were created allowing for a more accurate track width determination. These results demonstrate how effective the use of low cost UAVs can be for rapid response storm damage assessments, the high quality of data they can achieve, and how they can help us better visualize tornado site investigations.

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...

Fusion of pixel and object-based features for weed mapping using unmanned aerial vehicle imagery

NASA Astrophysics Data System (ADS)

Gao, Junfeng; Liao, Wenzhi; Nuyttens, David; Lootens, Peter; Vangeyte, Jürgen; Pižurica, Aleksandra; He, Yong; Pieters, Jan G.

2018-05-01

The developments in the use of unmanned aerial vehicles (UAVs) and advanced imaging sensors provide new opportunities for ultra-high resolution (e.g., less than a 10 cm ground sampling distance (GSD)) crop field monitoring and mapping in precision agriculture applications. In this study, we developed a strategy for inter- and intra-row weed detection in early season maize fields from aerial visual imagery. More specifically, the Hough transform algorithm (HT) was applied to the orthomosaicked images for inter-row weed detection. A semi-automatic Object-Based Image Analysis (OBIA) procedure was developed with Random Forests (RF) combined with feature selection techniques to classify soil, weeds and maize. Furthermore, the two binary weed masks generated from HT and OBIA were fused for accurate binary weed image. The developed RF classifier was evaluated by 5-fold cross validation, and it obtained an overall accuracy of 0.945, and Kappa value of 0.912. Finally, the relationship of detected weeds and their ground truth densities was quantified by a fitted linear model with a coefficient of determination of 0.895 and a root mean square error of 0.026. Besides, the importance of input features was evaluated, and it was found that the ratio of vegetation length and width was the most significant feature for the classification model. Overall, our approach can yield a satisfactory weed map, and we expect that the obtained accurate and timely weed map from UAV imagery will be applicable to realize site-specific weed management (SSWM) in early season crop fields for reducing spraying non-selective herbicides and costs.

Pipeline monitoring with unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kochetkova, L. I.

2018-05-01

Pipeline leakage during transportation of combustible substances leads to explosion and fire thus causing death of people and destruction of production and accommodation facilities. Continuous pipeline monitoring allows identifying leaks in due time and quickly taking measures for their elimination. The paper describes the solution of identification of pipeline leakage using unmanned aerial vehicles. It is recommended to apply the spectral analysis with input RGB signal to identify pipeline damages. The application of multi-zone digital images allows defining potential spill of oil hydrocarbons as well as possible soil pollution. The method of multi-temporal digital images within the visible region makes it possible to define changes in soil morphology for its subsequent analysis. The given solution is cost efficient and reliable thus allowing reducing timing and labor resources in comparison with other methods of pipeline monitoring.

Passive stability and actuation of micro aerial vehicles

NASA Astrophysics Data System (ADS)

Piccoli, Matthew

Micro Aerial Vehicles (MAVs) have increased in popularity in recent years. The most common platform, the quadrotor, has surpassed other MAVs like traditional helicopters and ornithopters in popularity mainly due to their simplicity. Yet the quadrotor design is a century old and was intended to carry people. We set out to design a MAV that is designed specifically to be a MAV, i.e. a vehicle not intended to carry humans as a payload. With this constraint lifted the vehicle can continuously rotate, which would dizzy a human, can sustain larger forces, which would damage a human, or can take advantage of scaling properties, where it may not work at human scale. Furthermore, we aim for simplicity by removing vehicle controllers and reducing the number of actuators, such that the vehicle can be made cost effective, if not disposable. We begin by studying general equations of motion for hovering MAVs. We search for vehicle configurations that exhibit passive stability, allowing the MAV to operate without a controller or actuators to apply control, ideally a single actuator. The analysis suggests two distinct types of passively stabilized MAVs and we create test vehicles for both. With simple hovering achieved, we concentrate on controlled motion with an emphasis on doing so without adding actuators. We find we can attain three degree of freedom control using separation of time scales with our actuator via low frequency for control in the vertical direction and high frequency for control in the horizontal plane. We explore techniques for achieving high frequency actuator control, which also allow the compensation of motor defects, specifically cogging torque. We combine passive stability with the motion control into two vehicles, UNO and Piccolissimo. UNO, the Underactuated-propeller Naturally-stabilized One-motor vehicle, demonstrates the capabilities of simple vehicles by performing maneuvers like conventional quadrotors. Piccolissimo, Italian for very little

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.

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…

LIDAR Remote Sensing of Particulate Matter Emissions from On-Road Vehicles

NASA Astrophysics Data System (ADS)

Keislar, R. E.; Kuhns, H.; Mazzoleni, C.; Moosmuller, H.; Watson, J.

2002-12-01

DRI has developed a remote sensing method for on-road particulate matter emissions from gasoline-powered and diesel-powered vehicles called the Vehicle Emissions Remote Sensing System (VERSS). Remote sensing of gaseous pollutants in vehicle exhaust is a well-established, economical way to determine on-road emissions for thousands of vehicles per day. The VERSS adds a particulate matter channel to complement gaseous pollutant measurements. The VERSS uses 266-nm ultraviolet laser light to achieve greater sensitivity than visible light to sub-micrometer particles, where the greatest mass fraction has been reported. The VERSS system integrates the lidar channel with a commercial remote sensing device (RSD) for gaseous pollutants, and the RSD CO2 measurement can be used to estimate fuel-based particle mass emissions. We describe the interpretation and processing of lidar returns from field measurements taken by the combined VERSS during the Southern Nevada Air Quality Study (SNAQS), conducted in the Las Vegas area. With suitable assumptions regarding size distribution and particle composition, the lidar backscatter signal and the RSD yield three basic measurements of particulate matter in the exhaust plume. For each passing vehicle, these three channels are: 1) Columnar extinction in the infrared (IR at 3.9 micrometers) 2) Columnar extinction in the ultraviolet (UV at 266 nm) 3) Range-resolved backscatter at 266 nm (horizontal spatial resolution of 20-25 cm) The 3.9-micrometer channel is a good surrogate for absorption by elemental carbon (EC) in tailpipe emissions and has been utilized in previous studies. Opacity measurements at 266 nm provide optical extinction due to scattering from tailpipe organic carbon (OC) and EC emissions.

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

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.

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.

Comparison of Aerial and Terrestrial Remote Sensing Techniques for Quantifying Forest Canopy Structural Complexity and Estimating Net Primary Productivity

NASA Astrophysics Data System (ADS)

Fahey, R. T.; Tallant, J.; Gough, C. M.; Hardiman, B. S.; Atkins, J.; Scheuermann, C. M.

2016-12-01

Canopy structure can be an important driver of forest ecosystem functioning - affecting factors such as radiative transfer and light use efficiency, and consequently net primary production (NPP). Both above- (aerial) and below-canopy (terrestrial) remote sensing techniques are used to assess canopy structure and each has advantages and disadvantages. Aerial techniques can cover large geographical areas and provide detailed information on canopy surface and canopy height, but are generally unable to quantitatively assess interior canopy structure. Terrestrial methods provide high resolution information on interior canopy structure and can be cost-effectively repeated, but are limited to very small footprints. Although these methods are often utilized to derive similar metrics (e.g., rugosity, LAI) and to address equivalent ecological questions and relationships (e.g., link between LAI and productivity), rarely are inter-comparisons made between techniques. Our objective is to compare methods for deriving canopy structural complexity (CSC) metrics and to assess the capacity of commonly available aerial remote sensing products (and combinations) to match terrestrially-sensed data. We also assess the potential to combine CSC metrics with image-based analysis to predict plot-based NPP measurements in forests of different ages and different levels of complexity. We use combinations of data from drone-based imagery (RGB, NIR, Red Edge), aerial LiDAR (commonly available medium-density leaf-off), terrestrial scanning LiDAR, portable canopy LiDAR, and a permanent plot network - all collected at the University of Michigan Biological Station. Our results will highlight the potential for deriving functionally meaningful CSC metrics from aerial imagery, LiDAR, and combinations of data sources. We will also present results of modeling focused on predicting plot-level NPP from combinations of image-based vegetation indices (e.g., NDVI, EVI) with LiDAR- or image-derived metrics of

Flexible micro flow sensor for micro aerial vehicles

NASA Astrophysics Data System (ADS)

Zhu, Rong; Que, Ruiyi; Liu, Peng

2017-12-01

This article summarizes our studies on micro flow sensors fabricated on a flexible polyimide circuit board by a low-cost hybrid process of thin-film deposition and circuit printing. The micro flow sensor has merits of flexibility, structural simplicity, easy integrability with circuits, and good sensing performance. The sensor, which adheres to an object surface, can detect the surface flow around the object. In our study, we install the fabricated micro flow sensors on micro aerial vehicles (MAVs) to detect the surface flow variation around the aircraft wing and deduce the aerodynamic parameters of the MAVs in flight. Wind tunnel experiments using the sensors integrated with the MAVs are also conducted.

Online Aerial Terrain Mapping for Ground Robot Navigation.

PubMed

Peterson, John; Chaudhry, Haseeb; Abdelatty, Karim; Bird, John; Kochersberger, Kevin

2018-02-20

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle's overhead view to inform the ground vehicle's path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles.

Remote Sensing-based Models of Soil Vulnerability to Compaction and Erosion from Off-highway Vehicles

NASA Astrophysics Data System (ADS)

Villarreal, M. L.; Webb, R. H.; Norman, L.; Psillas, J.; Rosenberg, A.; Carmichael, S.; Petrakis, R.; Sparks, P.

2014-12-01

Intensive off-road vehicle use for immigration, smuggling, and security of the United States-Mexico border has prompted concerns about long-term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from vehicle disturbances, we developed a series of erosion potential models based on factors from the Revised Universal Soil Loss Equation (RUSLE), with particular focus on the management factor (P-factor) and vegetation cover (C-factor). To better express the vulnerability of soils to human disturbances, a soil compaction index (applied as the P-factor) was calculated as the difference in saturated hydrologic conductivity (Ks) between disturbed and undisturbed soils, which was then scaled up to remote sensing-based maps of vehicle tracks and digital soils maps. The C-factor was improved using a satellite-based vegetation index, which was better correlated with estimated ground cover (r2 = 0.77) than data derived from regional land cover maps (r2 = 0.06). RUSLE factors were normalized to give equal weight to all contributing factors, which provided more management-specific information on vulnerable areas where vehicle compaction of sensitive soils intersects with steep slopes and low vegetation cover. Resulting spatial data on vulnerability and erosion potential provide land managers with information to identify critically disturbed areas and potential restoration sites where off-road driving should be restricted to reduce further degradation.

Aerial remote sensing survey of Fusarium wilt of cotton in New Mexico and Texas

USDA-ARS?s Scientific Manuscript database

Fusarium wilt of cotton, caused by the fungus Fusarium oxysporum f. sp. vasinfectum (FOV), is a widespread cotton disease, but the more virulent FOV race 4 (FOV4) has recently been identified in the New Mexico-Texas border area near El Paso, Texas. A preliminary aerial remote sensing survey was cond...

Experimental evaluation of HJB optimal controllers for the attitude dynamics of a multirotor aerial vehicle.

PubMed

Prado, Igor Afonso Acampora; Pereira, Mateus de Freitas Virgílio; de Castro, Davi Ferreira; Dos Santos, Davi Antônio; Balthazar, Jose Manoel

2018-06-01

The present paper is concerned with the design and experimental evaluation of optimal control laws for the nonlinear attitude dynamics of a multirotor aerial vehicle. Three design methods based on Hamilton-Jacobi-Bellman equation are taken into account. The first one is a linear control with guarantee of stability for nonlinear systems. The second and third are a nonlinear suboptimal control techniques. These techniques are based on an optimal control design approach that takes into account the nonlinearities present in the vehicle dynamics. The stability Proof of the closed-loop system is presented. The performance of the control system designed is evaluated via simulations and also via an experimental scheme using the Quanser 3-DOF Hover. The experiments show the effectiveness of the linear control method over the nonlinear strategy. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Human Systems Integration and Automation Issues in Small Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

McCauley, Michael E.; Matsangas, Panagiotis

2004-01-01

The goal of this report is to identify Human System Integration (HSI) and automation issues that contribute to improved effectiveness and efficiency in the operation of U.S. military Small Unmanned Aerial Vehicles (SUAVs). HSI issues relevant to SUAV operations are reviewed and observations from field trials are summarized. Short-term improvements are suggested research issues are identified and an overview is provided of automation technologies applicable to future SUAV design.

Possible methods for distinguishing icebergs from ships by aerial remote sensing

NASA Technical Reports Server (NTRS)

Howes, W. L.

1979-01-01

The simplest methods for aerial remote sensing which are least affected by atmospheric opacities are summarized. Radar is preferred for targets off the flight path, and microwave radiometry for targets along the flight path. Radar methods are classified by ability to resolve targets. Techniques which do not require target resolution are preferred. Among these techniques, polarization methods appear most promising, specifically those which differentiate the expected relatively greater depolarization by icebergs from that by ships or which detect doubly-reversed circular polarization.

Optimization of the choice of unmanned aerial vehicles used to monitor the implementation of selected construction projects

NASA Astrophysics Data System (ADS)

Skorupka, Dariusz; Duchaczek, Artur; Waniewska, Agnieszka; Kowacka, Magdalena

2017-07-01

Due to their properties unmanned aerial vehicles have huge number of possibilities for application in construction engineering. The nature and extent of construction works performedmakes the decision to purchase the right equipment significant for the possibility for its further use while monitoring the implementation of these works. Technical factors, such as the accuracy and quality of the applied measurement instruments are especially important when monitoring the realization of construction projects. The paper presents the optimization of the choice of unmanned aerial vehicles using the Bellinger method. The decision-making analysis takes into account criteria that are particularly crucial by virtue of the range of monitoring of ongoing construction works.

Online Aerial Terrain Mapping for Ground Robot Navigation

PubMed Central

Peterson, John; Chaudhry, Haseeb; Abdelatty, Karim; Bird, John; Kochersberger, Kevin

2018-01-01

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle’s overhead view to inform the ground vehicle’s path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles. PMID:29461496

Aerial surveillance based on hierarchical object classification for ground target detection

NASA Astrophysics Data System (ADS)

Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

2015-03-01

Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

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.

Unmanned Aerial Mass Spectrometer Systems for In-Situ Volcanic Plume Analysis

NASA Astrophysics Data System (ADS)

Diaz, Jorge Andres; Pieri, David; Wright, Kenneth; Sorensen, Paul; Kline-Shoder, Robert; Arkin, C. Richard; Fladeland, Matthew; Bland, Geoff; Buongiorno, Maria Fabrizia; Ramirez, Carlos; Corrales, Ernesto; Alan, Alfredo; Alegria, Oscar; Diaz, David; Linick, Justin

2015-02-01

Technology advances in the field of small, unmanned aerial vehicles and their integration with a variety of sensor packages and instruments, such as miniature mass spectrometers, have enhanced the possibilities and applications of what are now called unmanned aerial systems (UAS). With such technology, in situ and proximal remote sensing measurements of volcanic plumes are now possible without risking the lives of scientists and personnel in charge of close monitoring of volcanic activity. These methods provide unprecedented, and otherwise unobtainable, data very close in space and time to eruptions, to better understand the role of gas volatiles in magma and subsequent eruption products. Small mass spectrometers, together with the world's smallest turbo molecular pump, have being integrated into NASA and University of Costa Rica UAS platforms to be field-tested for in situ volcanic plume analysis, and in support of the calibration and validation of satellite-based remote sensing data. These new UAS-MS systems are combined with existing UAS flight-tested payloads and assets, such as temperature, pressure, relative humidity, SO2, H2S, CO2, GPS sensors, on-board data storage, and telemetry. Such payloads are capable of generating real time 3D concentration maps of the Turrialba volcano active plume in Costa Rica, while remote sensing data are simultaneously collected from the ASTER and OMI space-borne instruments for comparison. The primary goal is to improve the understanding of the chemical and physical properties of emissions for mitigation of local volcanic hazards, for the validation of species detection and abundance of retrievals based on remote sensing, and to validate transport models.

Unmanned aerial mass spectrometer systems for in-situ volcanic plume analysis.

PubMed

Diaz, Jorge Andres; Pieri, David; Wright, Kenneth; Sorensen, Paul; Kline-Shoder, Robert; Arkin, C Richard; Fladeland, Matthew; Bland, Geoff; Buongiorno, Maria Fabrizia; Ramirez, Carlos; Corrales, Ernesto; Alan, Alfredo; Alegria, Oscar; Diaz, David; Linick, Justin

2015-02-01

Technology advances in the field of small, unmanned aerial vehicles and their integration with a variety of sensor packages and instruments, such as miniature mass spectrometers, have enhanced the possibilities and applications of what are now called unmanned aerial systems (UAS). With such technology, in situ and proximal remote sensing measurements of volcanic plumes are now possible without risking the lives of scientists and personnel in charge of close monitoring of volcanic activity. These methods provide unprecedented, and otherwise unobtainable, data very close in space and time to eruptions, to better understand the role of gas volatiles in magma and subsequent eruption products. Small mass spectrometers, together with the world's smallest turbo molecular pump, have being integrated into NASA and University of Costa Rica UAS platforms to be field-tested for in situ volcanic plume analysis, and in support of the calibration and validation of satellite-based remote sensing data. These new UAS-MS systems are combined with existing UAS flight-tested payloads and assets, such as temperature, pressure, relative humidity, SO2, H2S, CO2, GPS sensors, on-board data storage, and telemetry. Such payloads are capable of generating real time 3D concentration maps of the Turrialba volcano active plume in Costa Rica, while remote sensing data are simultaneously collected from the ASTER and OMI space-borne instruments for comparison. The primary goal is to improve the understanding of the chemical and physical properties of emissions for mitigation of local volcanic hazards, for the validation of species detection and abundance of retrievals based on remote sensing, and to validate transport models.

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

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.

Some technical notes on using UAV-based remote sensing for post disaster assessment

NASA Astrophysics Data System (ADS)

Rokhmana, Catur Aries; Andaru, Ruli

2017-07-01

Indonesia is located in an area prone to disasters, which are various kinds of natural disasters happen. In disaster management, the geoinformation data are needed to be able to evaluate the impact area. The UAV (Unmanned Aerial Vehicle)-Based remote sensing technology is a good choice to produce a high spatial resolution of less than 15 cm, while the current resolution of the satellite imagery is still greater than 50 cm. This paper shows some technical notes that should be considered when using UAV-Based remote sensing system in post disaster for rapid assessment. Some cases are Aceh Earthquake in years 2013 for seeing infrastructure damages, Banjarnegara landslide in year 2014 for seeing the impact; and Kelud volcano eruption in year 2014 for seeing the impact and volumetric material calculation. The UAV-Based remote sensing system should be able to produce the Orthophoto image that can provide capabilities for visual interpretation the individual damage objects, and the changes situation. Meanwhile the DEM (digital Elevation model) product can derive terrain topography, and volumetric calculation with accuracy 3-5 pixel or sub-meter also. The UAV platform should be able for working remotely and autonomously in dangerous area and limited infrastructures. In mountainous or volcano area, an unconventional flight plan should implemented. Unfortunately, not all impact can be seen from above such as wall crack, some parcel boundaries, and many objects that covered by others higher object. The previous existing geoinformation data are also needed to be able to evaluate the change detection automatically.

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...

Investigation of Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Yang, S.; Talbot, R. W.; Frish, M. B.; Golston, L.; Aubut, N. F.; Zondlo, M. A.

2017-12-01

The U.S is now the world's largest natural gas producer, of which methane (CH4) is the main component. About 2% of the CH4 is lost through fugitive leaks. This research is under the DOE Methane Observation Networks with Innovative Technology to Obtain Reductions (MONITOR) program of ARPA-E. Our sentry measurement system is composed of four state-of-the-art technologies centered around the RMLDTM (Remote Methane Leak Detector). An open path RMLDTM measures column-integrated CH4 concentration that incorporates fluctuations in the vertical CH4 distribution. Based on Backscatter Tunable Diode Laser Absorption Spectroscopy and Small Unmanned Aerial Vehicles, the sentry system can autonomously, consistently and cost-effectively monitor and quantify CH4 leakage from sites associated with natural gas production. This system provides an advanced capability in detecting leaks at hard-to-access sites (e.g., wellheads) compared to traditional manual methods. Automated leak detecting and reporting algorithms combined with wireless data link implement real-time leak information reporting. Early data were gathered to set up and test the prototype system, and to optimize the leak localization and calculation strategies. The flight pattern is based on a raster scan which can generate interpolated CH4 concentration maps. The localization and quantification algorithms can be derived from the plume images combined with wind vectors. Currently, the accuracy of localization algorithm can reach 2 m and the calculation algorithm has a factor of 2 accuracy. This study places particular emphasis on flux quantification. The data collected at Colorado and Houston test fields were processed, and the correlation between flux and other parameters analyzed. Higher wind speeds and lower wind variation are preferred to optimize flux estimation. Eventually, this system will supply an enhanced detection capability to significantly reduce fugitive CH4 emissions in the natural gas industry.

Rangeland remote sensing applications with unmanned aerial systems (UAS) in the national airspace: challenges and experiences

USDA-ARS?s Scientific Manuscript database

In recent years, civilian applications of unmanned aerial systems (UAS) have increased considerably due to their greater availability and the miniaturization of sensors, GPS, inertial measurement units, and other hardware. UAS are well suited for rangeland remote sensing applications, because of the...

UNMANNED AERIAL VEHICLE (UAV) HYPERSPECTRAL REMOTE SENSING FOR DRYLAND VEGETATION MONITORING

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

Nancy F. Glenn; Jessica J. Mitchell; Matthew O. Anderson

2012-06-01

UAV-based hyperspectral remote sensing capabilities developed by the Idaho National Lab and Idaho State University, Boise Center Aerospace Lab, were recently tested via demonstration flights that explored the influence of altitude on geometric error, image mosaicking, and dryland vegetation classification. The test flights successfully acquired usable flightline data capable of supporting classifiable composite images. Unsupervised classification results support vegetation management objectives that rely on mapping shrub cover and distribution patterns. Overall, supervised classifications performed poorly despite spectral separability in the image-derived endmember pixels. Future mapping efforts that leverage ground reference data, ultra-high spatial resolution photos and time series analysis shouldmore » be able to effectively distinguish native grasses such as Sandberg bluegrass (Poa secunda), from invasives such as burr buttercup (Ranunculus testiculatus) and cheatgrass (Bromus tectorum).« less

Real-time Accurate Surface Reconstruction Pipeline for Vision Guided Planetary Exploration Using Unmanned Ground and Aerial Vehicles

NASA Technical Reports Server (NTRS)

Almeida, Eduardo DeBrito

2012-01-01

This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL), California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.

Theme issue ;State-of-the-art in photogrammetry, remote sensing and spatial information science;

NASA Astrophysics Data System (ADS)

Heipke, Christian; Madden, Marguerite; Li, Zhilin; Dowman, Ian

2016-05-01

Over the past few years, photogrammetry, remote sensing and spatial information science have witnessed great changes in virtually every stage of information from imagery. Indeed, we have seen, for example, a sharply increased interest in unmanned aerial vehicles,

Field determination of multipollutant, open area combustion source emission factors with a hexacopter unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Aurell, J.; Mitchell, W.; Chirayath, V.; Jonsson, J.; Tabor, D.; Gullett, B.

2017-10-01

An emission sensor/sampler system was coupled to a National Aeronautics and Space Administration (NASA) hexacopter unmanned aerial vehicle (UAV) to characterize gases and particles in the plumes emitted from open burning of military ordnance. The UAV/sampler was tested at two field sites with test and sampling flights spanning over 16 h of flight time. The battery-operated UAV was remotely maneuvered into the plumes at distances from the pilot of over 600 m and at altitudes of up to 122 m above ground level. While the flight duration could be affected by sampler payload (3.2-4.6 kg) and meteorological conditions, the 57 sampling flights, ranging from 4 to 12 min, were typically terminated when the plume concentrations of CO2 were diluted to near ambient levels. Two sensor/sampler systems, termed ;Kolibri,; were variously configured to measure particulate matter, metals, chloride, perchlorate, volatile organic compounds, chlorinated dioxins/furans, and nitrogen-based organics for determination of emission factors. Gas sensors were selected based on their applicable concentration range, light weight, freedom from interferents, and response/recovery times. Samplers were designed, constructed, and operated based on U.S. Environmental Protection Agency (EPA) methods and quality control criteria. Results show agreement with published emission factors and good reproducibility (e.g., 26% relative standard deviation for PM2.5). The UAV/Kolibri represents a significant advance in multipollutant emission characterization capabilities for open area sources, safely and effectively making measurements heretofore deemed too hazardous for personnel or beyond the reach of land-based samplers.

Applicability of Unmanned Aerial Vehicles in Research on Aeolian Processes

NASA Astrophysics Data System (ADS)

Algimantas, Česnulevičius; Artūras, Bautrėnas; Linas, Bevainis; Donatas, Ovodas; Kęstutis, Papšys

2018-02-01

Surface dynamics and instabilities are characteristic of aeolian formation. The method of surface comparison is regarded as the most appropriate one for evaluation of the intensity of aeolian processes and the amount of transported sand. The data for surface comparison can be collected by topographic survey measurements and using unmanned aerial vehicles. Time cost for relief microform fixation and measurement executing topographic survey are very high. The method of unmanned aircraft aerial photographs fixation also encounters difficulties because there are no stable clear objects and contours that enable to link aerial photographs, to determine the boundaries of captured territory and to ensure the accuracy of surface measurements. Creation of stationary anchor points is irrational due to intense sand accumulation and deflation in different climate seasons. In September 2015 and in April 2016 the combined methodology was applied for evaluation of intensity of aeolian processes in the Curonian Spit. Temporary signs (marks) were installed on the surface, coordinates of the marks were fixed using GPS and then flight of unmanned aircraft was conducted. The fixed coordinates of marks ensure the accuracy of measuring aerial imagery and the ability to calculate the possible corrections. This method was used to track and measure very small (micro-rank) relief forms (5-10 cm height and 10-20 cm length). Using this method morphometric indicators of micro-terraces caused by sand dunes pressure to gytia layer were measured in a non-contact way. An additional advantage of the method is the ability to accurately link the repeated measurements. The comparison of 3D terrain models showed sand deflation and accumulation areas and quantitative changes in the terrain very clearly.

Remote sensing of on-road vehicle emissions: Mechanism, applications and a case study from Hong Kong

NASA Astrophysics Data System (ADS)

Huang, Yuhan; Organ, Bruce; Zhou, John L.; Surawski, Nic C.; Hong, Guang; Chan, Edward F. C.; Yam, Yat Shing

2018-06-01

Vehicle emissions are a major contributor to air pollution in cities and have serious health impacts to their inhabitants. On-road remote sensing is an effective and economic tool to monitor and control vehicle emissions. In this review, the mechanism, accuracy, advantages and limitations of remote sensing were introduced. Then the applications and major findings of remote sensing were critically reviewed. It was revealed that the emission distribution of on-road vehicles was highly skewed so that the dirtiest 10% vehicles accounted for over half of the total fleet emissions. Such findings highlighted the importance and effectiveness of using remote sensing for in situ identification of high-emitting vehicles for further inspection and maintenance programs. However, the accuracy and number of vehicles affected by screening programs were greatly dependent on the screening criteria. Remote sensing studies showed that the emissions of gasoline and diesel vehicles were significantly reduced in recent years, with the exception of NOx emissions of diesel vehicles in spite of greatly tightened automotive emission regulations. Thirdly, the experience and issues of using remote sensing for identifying high-emitting vehicles in Hong Kong (where remote sensing is a legislative instrument for enforcement purposes) were reported. That was followed by the first time ever identification and discussion of the issue of frequent false detection of diesel high-emitters using remote sensing. Finally, the challenges and future research directions of on-road remote sensing were elaborated.

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 spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision and hobbyist unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Dandois, J. P.; Ellis, E. C.

2013-12-01

High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing system enabling routine and inexpensive aerial 3D measurements of canopy structure and spectral attributes, with properties similar to those of LIDAR, but with RGB (red-green-blue) spectral attributes for each point, enabling high frequency observations within a single growing season. This 'Ecosynth' methodology applies photogrammetric ''Structure from Motion'' computer vision algorithms to large sets of highly overlapping low altitude (< 130 m) aerial photographs acquired using off-the-shelf digital cameras mounted on an inexpensive (< USD$4000), lightweight (< 2 kg), hobbyist-grade unmanned aerial system (UAS). Ecosynth 3D point clouds with densities of 30 - 67 points m-2 were produced using commercial computer vision software from digital photographs acquired repeatedly by UAS over three 6.25 ha (250 m x 250 m) Temperate Deciduous forest sites in Maryland USA. Ecosynth canopy height maps (CHMs) were strong predictors of field-measured tree heights (R2 0.63 to 0.84) and were highly correlated with a LIDAR CHM (R 0.87) acquired 4 days earlier, though Ecosynth-based estimates of aboveground biomass densities included significant errors (31 - 36% of field-based estimates). Repeated scanning of a 0.25 ha forested area at six different times across a 16 month period revealed ecologically significant dynamics in canopy color at different heights and a structural shift upward in canopy density, as demonstrated by changes in vertical height profiles of point density and relative RGB brightness. Changes in canopy relative greenness were highly correlated (R2 = 0.88) with MODIS NDVI time series for the same

Flight-test experience in digital control of a remotely piloted vehicle.

NASA Technical Reports Server (NTRS)

Edwards, J. W.

1972-01-01

The development of a remotely piloted vehicle system consisting of a remote pilot cockpit and a ground-based digital computer coupled to the aircraft through telemetry data links is described. The feedback control laws are implemented in a FORTRAN program. Flight-test experience involving high feedback gain limits for attitude and attitude rate feedback variables, filtering of sampled data, and system operation during intermittent telemetry data link loss is discussed. Comparisons of closed-loop flight tests with analytical calculations, and pilot comments on system operation are included.

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.

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.

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.

Research of aerial imaging spectrometer data acquisition technology based on USB 3.0

NASA Astrophysics Data System (ADS)

Huang, Junze; Wang, Yueming; He, Daogang; Yu, Yanan

2016-11-01

With the emergence of UAV (unmanned aerial vehicle) platform for aerial imaging spectrometer, research of aerial imaging spectrometer DAS(data acquisition system) faces new challenges. Due to the limitation of platform and other factors, the aerial imaging spectrometer DAS requires small-light, low-cost and universal. Traditional aerial imaging spectrometer DAS system is expensive, bulky, non-universal and unsupported plug-and-play based on PCIe. So that has been unable to meet promotion and application of the aerial imaging spectrometer. In order to solve these problems, the new data acquisition scheme bases on USB3.0 interface.USB3.0 can provide guarantee of small-light, low-cost and universal relying on the forward-looking technology advantage. USB3.0 transmission theory is up to 5Gbps.And the GPIF programming interface achieves 3.2Gbps of the effective theoretical data bandwidth.USB3.0 can fully meet the needs of the aerial imaging spectrometer data transmission rate. The scheme uses the slave FIFO asynchronous data transmission mode between FPGA and USB3014 interface chip. Firstly system collects spectral data from TLK2711 of high-speed serial interface chip. Then FPGA receives data in DDR2 cache after ping-pong data processing. Finally USB3014 interface chip transmits data via automatic-dma approach and uploads to PC by USB3.0 cable. During the manufacture of aerial imaging spectrometer, the DAS can achieve image acquisition, transmission, storage and display. All functions can provide the necessary test detection for aerial imaging spectrometer. The test shows that system performs stable and no data lose. Average transmission speed and storage speed of writing SSD can stabilize at 1.28Gbps. Consequently ,this data acquisition system can meet application requirements for aerial imaging spectrometer.

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

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

Benefits of Using Remotely Operated Vehicles to Inspect USACE Navigation Structures

DTIC Science & Technology

2007-03-01

ER D C/ CR R EL T R -0 7 -4 Benefits of Using Remotely Operated Vehicles to Inspect USACE Navigation Structures James H. Lever, Gary E...release; distribution is unlimited. ERDC/CRREL TR-07-4 March 2007 Benefits of Using Remotely Operated Vehicles to Inspect USACE Navigation...with inspections using divers or dewatering. In each case, benefits from reduced labor costs, shipping delays, and lost power production far exceed

Monitoring Spatial Variability and Temporal Dynamics of Phragmites Using Unmanned Aerial Vehicles

PubMed Central

Tóth, Viktor R.

2018-01-01

Littoral zones of freshwater lakes are exposed to environmental impacts from both terrestrial and aquatic sides, while substantial anthropogenic pressure also affects the high spatial, and temporal variability of the ecotone. In this study, the possibility of monitoring seasonal and spatial changes in reed (Phragmites australis) stands using an unmanned aerial vehicle (UAV) based remote sensing technique was examined. Stands in eutrophic and mesotrophic parts of Lake Balaton including not deteriorating (stable) and deteriorating (die-back) patches, were tracked throughout the growing season using a UAV equipped with a Normalized Difference Vegetation Index (NDVI) camera. Photophysiological parameters of P. australis were also measured with amplitude modulated fluorescence. Parameters characterizing the dynamics of seasonal changes in NDVI data were used for phenological comparison of eutrophic and mesotrophic, stable and die-back, terrestrial and aquatic, mowed and not-mowed patches of reed. It was shown that stable Phragmites plants from the eutrophic part of the lake reached specific phenological stages up to 3.5 days earlier than plants from the mesotrophic part of the lake. The phenological changes correlated with trophic (total and nitrate-nitrite nitrogen) and physical (organic C and clay content) properties of the sediment, while only minor relationships with air and water temperature were found. Phenological differences between the stable and die-back stands were even more pronounced, with ~34% higher rates of NDVI increase in stable than die-back patches, while the period of NDVI increase was 16 days longer. Aquatic and terrestrial parts of reed stands showed no phenological differences, although intermediate areas (shallow water parts of stands) were found to be less vigorous. Winter mowing of dried Phragmites sped up sprouting and growth of reed in the spring. This study showed that remote sensing-derived photophysiological and phenological variability

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.

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.

Hierarchical Motion Planning for Autonomous Aerial and Terrestrial Vehicles

NASA Astrophysics Data System (ADS)

Cowlagi, Raghvendra V.

Autonomous mobile robots---both aerial and terrestrial vehicles---have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical decomposition suffers a serious drawback: the geometric path planner has no information of the kinematical and dynamical constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates the geometric planner altogether by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption

Methods for In-Flight Wing Shape Predictions of Highly Flexible Unmanned Aerial Vehicles: Formulation of Ko Displacement Theory

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2010-01-01

The Ko displacement theory is formulated for a cantilever tubular wing spar under bending, torsion, and combined bending and torsion loading. The Ko displacement equations are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. The bending and distortion strain data can then be input to the displacement equations to calculate slopes, deflections, and cross-sectional twist angles of the wing spar at the strain-sensing stations for generating the deformed shapes of flexible aircraft wing spars. The displacement equations have been successfully validated for accuracy by finite-element analysis. The Ko displacement theory that has been formulated could also be applied to calculate the deformed shape of simple and tapered beams, plates, and tapered cantilever wing boxes. The Ko displacement theory and associated strain-sensing system (such as fiber optic sensors) form a powerful tool for in-flight deformation monitoring of flexible wings and tails, such as those often employed on unmanned aerial vehicles. Ultimately, the calculated displacement data can be visually displayed in real time to the ground-based pilot for monitoring the deformed shape of unmanned aerial vehicles during flight.

Computational analysis of unmanned aerial vehicle (UAV)

NASA Astrophysics Data System (ADS)

Abudarag, Sakhr; Yagoub, Rashid; Elfatih, Hassan; Filipovic, Zoran

2017-01-01

A computational analysis has been performed to verify the aerodynamics properties of Unmanned Aerial Vehicle (UAV). The UAV-SUST has been designed and fabricated at the Department of Aeronautical Engineering at Sudan University of Science and Technology in order to meet the specifications required for surveillance and reconnaissance mission. It is classified as a medium range and medium endurance UAV. A commercial CFD solver is used to simulate steady and unsteady aerodynamics characteristics of the entire UAV. In addition to Lift Coefficient (CL), Drag Coefficient (CD), Pitching Moment Coefficient (CM) and Yawing Moment Coefficient (CN), the pressure and velocity contours are illustrated. The aerodynamics parameters are represented a very good agreement with the design consideration at angle of attack ranging from zero to 26 degrees. Moreover, the visualization of the velocity field and static pressure contours is indicated a satisfactory agreement with the proposed design. The turbulence is predicted by enhancing K-ω SST turbulence model within the computational fluid dynamics code.

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.

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).

Optimizing Optics For Remotely Controlled Underwater Vehicles

NASA Astrophysics Data System (ADS)

Billet, A. B.

1984-09-01

The past decade has shown a dramatic increase in the use of unmanned tethered vehicles in worldwide marine fields. These vehicles are used for inspection, debris removal and object retrieval. With advanced robotic technology, remotely operated vehicles (ROVs) are now able to perform a variety of jobs previously accomplished only by divers. The ROVs can be used at greater depths and for riskier jobs, and safety to the diver is increased, freeing him for safer, more cost-effective tasks requiring human capabilities. Secondly, the ROV operation becomes more cost effective to use as work depth increases. At 1000 feet a diver's 10 minutes of work can cost over $100,000 including support personnel, while an ROV operational cost might be 1/20 of the diver cost per day, based on the condition that the cost for ROV operation does not change with depth, as it does for divers. In the ROV operation the television lens must be as good as the human eye, with better light gathering capability than the human eye. The RCV-150 system is an example of these advanced technology vehicles. With the requirements of manueuverability and unusual inspection, a responsive, high performance, compact vehicle was developed. The RCV-150 viewing subsystem consists of a television camera, lights, and topside monitors. The vehicle uses a low light level Newvicon television camera. The camera is equipped with a power-down iris that closes for burn protection when the power is off. The camera can pan f 50 degrees and tilt f 85 degrees on command from the surface. Four independently controlled 250 watt quartz halogen flood lamps illuminate the viewing area as required; in addition, two 250 watt spotlights are fitted. A controlled nine inch CRT monitor provides real time camera pictures for the operator. The RCV-150 vehicle component system consists of the vehicle structure, the vehicle electronics, and hydraulic system which powers the thruster assemblies and the manipulator. For this vehicle, a light

Remote sensing of biomass and annual net aerial primary productivity of a salt marsh

NASA Technical Reports Server (NTRS)

Hardisky, M. A.; Klemas, V.; Daiber, F. C.; Roman, C. T.

1984-01-01

Net aerial primary productivity is the rate of storage of organic matter in above-ground plant issues exceeding the respiratory use by the plants during the period of measurement. It is pointed out that this plant tissue represents the fixed carbon available for transfer to and consumption by the heterotrophic organisms in a salt marsh or the estuary. One method of estimating annual net aerial primary productivity (NAPP) required multiple harvesting of the marsh vegetation. A rapid nondestructive remote sensing technique for estimating biomass and NAPP would, therefore, be a significant asset. The present investigation was designed to employ simple regression models, equating spectral radiance indices with Spartina alterniflora biomass to nondestructively estimate salt marsh biomass. The results of the study showed that the considered approach can be successfully used to estimate salt marsh biomass.

Insect-Inspired Flight Control for Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Thakoor, Sarita; Stange, G.; Srinivasan, M.; Chahl, Javaan; Hine, Butler; Zornetzer, Steven

2005-01-01

Flight-control and navigation systems inspired by the structure and function of the visual system and brain of insects have been proposed for a class of developmental miniature robotic aircraft called "biomorphic flyers" described earlier in "Development of Biomorphic Flyers" (NPO-30554), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 54. These form a subset of biomorphic explorers, which, as reported in several articles in past issues of NASA Tech Briefs ["Biomorphic Explorers" (NPO-20142), Vol. 22, No. 9 (September 1998), page 71; "Bio-Inspired Engineering of Exploration Systems" (NPO-21142), Vol. 27, No. 5 (May 2003), page 54; and "Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration" (NPO-30286), Vol. 28, No. 5 (May 2004), page 36], are proposed small robots, equipped with microsensors and communication systems, that would incorporate crucial functions of mobility, adaptability, and even cooperative behavior. These functions are inherent to biological organisms but are challenging frontiers for technical systems. Biomorphic flyers could be used on Earth or remote planets to explore otherwise difficult or impossible to reach sites. An example of an exploratory task of search/surveillance functions currently being tested is to obtain high-resolution aerial imagery, using a variety of miniaturized electronic cameras. The control functions to be implemented by the systems in development include holding altitude, avoiding hazards, following terrain, navigation by reference to recognizable terrain features, stabilization of flight, and smooth landing. Flying insects perform these and other functions remarkably well, even though insect brains contains fewer than 10(exp -4) as many neurons as does the human brain. Although most insects have immobile, fixed-focus eyes and lack stereoscopy (and hence cannot perceive depth directly), they utilize a number of ingenious strategies for perceiving, and navigating in, three dimensions. Despite

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.

AVIATR—Aerial Vehicle for In-situ and Airborne Titan Reconnaissance. A Titan airplane mission concept

NASA Astrophysics Data System (ADS)

Barnes, Jason W.; Lemke, Lawrence; Foch, Rick; McKay, Christopher P.; Beyer, Ross A.; Radebaugh, Jani; Atkinson, David H.; Lorenz, Ralph D.; Le Mouélic, Stéphane; Rodriguez, Sebastien; Gundlach, Jay; Giannini, Francesco; Bain, Sean; Flasar, F. Michael; Hurford, Terry; Anderson, Carrie M.; Merrison, Jon; Ádámkovics, Máté; Kattenhorn, Simon A.; Mitchell, Jonathan; Burr, Devon M.; Colaprete, Anthony; Schaller, Emily; Friedson, A. James; Edgett, Kenneth S.; Coradini, Angioletta; Adriani, Alberto; Sayanagi, Kunio M.; Malaska, Michael J.; Morabito, David; Reh, Kim

2012-03-01

We describe a mission concept for a stand-alone Titan airplane mission: Aerial Vehicle for In-situ and Airborne Titan Reconnaissance (AVIATR). With independent delivery and direct-to-Earth communications, AVIATR could contribute to Titan science either alone or as part of a sustained Titan Exploration Program. As a focused mission, AVIATR as we have envisioned it would concentrate on the science that an airplane can do best: exploration of Titan's global diversity. We focus on surface geology/hydrology and lower-atmospheric structure and dynamics. With a carefully chosen set of seven instruments—2 near-IR cameras, 1 near-IR spectrometer, a RADAR altimeter, an atmospheric structure suite, a haze sensor, and a raindrop detector—AVIATR could accomplish a significant subset of the scientific objectives of the aerial element of flagship studies. The AVIATR spacecraft stack is composed of a Space Vehicle (SV) for cruise, an Entry Vehicle (EV) for entry and descent, and the Air Vehicle (AV) to fly in Titan's atmosphere. Using an Earth-Jupiter gravity assist trajectory delivers the spacecraft to Titan in 7.5 years, after which the AVIATR AV would operate for a 1-Earth-year nominal mission. We propose a novel `gravity battery' climb-then-glide strategy to store energy for optimal use during telecommunications sessions. We would optimize our science by using the flexibility of the airplane platform, generating context data and stereo pairs by flying and banking the AV instead of using gimbaled cameras. AVIATR would climb up to 14 km altitude and descend down to 3.5 km altitude once per Earth day, allowing for repeated atmospheric structure and wind measurements all over the globe. An initial Team-X run at JPL priced the AVIATR mission at FY10 715M based on the rules stipulated in the recent Discovery announcement of opportunity. Hence we find that a standalone Titan airplane mission can achieve important science building on Cassini's discoveries and can likely do so

AVIATR - Aerial Vehicle for In-situ and Airborne Titan Reconnaissance A Titan Airplane Mission Concept

NASA Technical Reports Server (NTRS)

Barnes, Jason W.; Lemke, Lawrence; Foch, Rick; McKay, Christopher P.; Beyer, Ross A.; Radebaugh, Jani; Atkinson, David H.; Lorenz, Ralph D.; LeMouelic, Stephane; Rodriguez, Sebastien;

Use of Unmanned Aerial Vehicles for Improving Farm Scale Agricultural Water Management in Agriculture at a Farm Scale. A case study for field crops in the California's Central Valley

NASA Astrophysics Data System (ADS)

Medellin-Azuara, J.; Morande, J. A.; Jin, Y.; Chen, Y.; Paw U, K. T.; Viers, J. H.

2016-12-01

Traditional methods for estimating consumptive water use as evapotranspiration (ET) for agriculture in areas with water limitations such as California have always been a challenge for farmers, water managers, researchers and government agencies. Direct measurement of evapotranspiration (ET) and crop water stress in agriculture can be a cumbersome and costly task. Furthermore, spatial variability of applied water and irrigation and stress level in crops, due to inherent heterogeneity in soil conditions, topography, management practices, and lack of uniformity in water applications may affect estimates water use efficiency and water balances. This situation difficult long-term management of agroecosystems. This paper presents a case study for various areas in California's Central Valley using Unmanned Aerial Vehicles (UAVs) for a late portion of the 2016 irrigation season These estimates are compared those obtained by direct measurement (from previously deployed stations), and energy balance approaches with remotely sensed data in a selection of field crop parcels. This research improves information on water use and site conditions in agriculture by enhancing remote sensing-based estimations through the use of higher resolution multi-spectral and thermal imagery captured by UAV. We assess whether more frequent information at higher spatial resolution from UAVs can improve estimations of overall ET through energy balance and imagery. Stress levels and ET are characterized spatially to examine irrigation practices and their performance to improve water use in the agroecosystem. Ground based data such as air and crop temperature and stem water potential is collected to validate UAV aerial measurements. Preliminary results show the potential of UAV technology to improve timing, resolution and accuracy in the ET estimation and assessment of crop stress at a farm scales. Side to side comparison with ground level stations employing surface renewal, eddy covariance and

Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar.

PubMed

Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

2017-01-19

Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass ( R ² = 0.340, root-mean-square error (RMSE) = 81.89 g·m -2 , and relative error of 14.1%). The improvement of multiple regressions to the R ² and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns.

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.

Experimental aerodynamic and static elastic deformation characterization of low aspect ratio flexible fixed wings applied to micro aerial vehicles

NASA Astrophysics Data System (ADS)

Albertani, Roberto

The concept of micro aerial vehicles (MAVs) is for a small, inexpensive and sometimes expendable platform, flying by remote pilot, in the field or autonomously. Because of the requirement to be flown either by almost inexperienced pilots or by autonomous control, they need to have very reliable and benevolent flying characteristics drive the design guidelines. A class of vehicles designed by the University of Florida adopts a flexible-wing concept, featuring a carbon fiber skeleton and a thin extensible latex membrane skin. Another typical feature of MAVs is a wingspan to propeller diameter ratio of two or less, generating a substantial influence on the vehicle aerodynamics. The main objectives of this research are to elucidate and document the static elastic flow-structure interactions in terms of measurements of the aerodynamic coefficients and wings' deformation as well as to substantiate the proposed inferences regarding the influence of the wings' structural flexibility on their performance; furthermore the research will provide experimental data to support the validation of CFD and FEA numerical models. A unique facility was developed at the University of Florida to implement a combination of a low speed wind tunnel and a visual image correlation system. The models tested in the wind tunnel were fabricated at the University MAV lab and consisted of a series of ten models with an identical geometry but differing in levels of structural flexibility and deformation characteristics. Results in terms of full-field displacements and aerodynamic coefficients from wind tunnel tests for various wind velocities and angles of attack are presented to demonstrate the deformation of the wing under steady aerodynamic load. The steady state effects of the propeller slipstream on the flexible wing's shape and its performance are also investigated. Analytical models of the aerodynamic and propulsion characteristics are proposed based on a multi dimensional linear regression

Integration of aerial imaging and variable-rate technology for site-specific aerial herbicide application

USDA-ARS?s Scientific Manuscript database

As remote sensing and variable rate technology are becoming more available for aerial applicators, practical methodologies on effective integration of these technologies are needed for site-specific aerial applications of crop production and protection materials. The objectives of this study were to...

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.

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.

Method of transmission of dynamic multibit digital images from micro-unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Petrov, E. P.; Kharina, N. L.

2018-01-01

In connection with successful usage of nanotechnologies in remote sensing great attention is paid to the systems in micro-unmanned aerial vehicles (MUAVs) capable to provide high spatial resolution of dynamic multibit digital images (MDI). Limited energy resources on board the MUAV do not allow transferring a large amount of video information in the shortest possible time. It keeps back the broad development of MUAV. The search for methods to shorten the transmission time of dynamic MDIs from MUAV over the radio channel leads to the methods of MDI compression without computational operations onboard the MUAV. The known compression codecs of video information can not be applied because of the limited energy resources. In this paper we propose a method for reducing the transmission time of dynamic MDIs without computational operations and distortions onboard the MUAV. To develop the method a mathematical apparatus of the theory of conditional Markov processes with discrete arguments was used. On its basis a mathematical model for the transformation of the MDI represented by binary images (BI) in the MDI, consisting of groups of neighboring BIs (GBI) transmitted by multiphase (MP) signals, is constructed. The algorithm for multidimensional nonlinear filtering of MP signals is synthesized, realizing the statistical redundancy of the MDI to compensate for the noise stability losses caused by the use of MP signals.

High clearance phenotyping systems for season-long measurement of corn, sorghum and other row crops to complement unmanned aerial vehicle systems

NASA Astrophysics Data System (ADS)

Murray, Seth C.; Knox, Leighton; Hartley, Brandon; Méndez-Dorado, Mario A.; Richardson, Grant; Thomasson, J. Alex; Shi, Yeyin; Rajan, Nithya; Neely, Haly; Bagavathiannan, Muthukumar; Dong, Xuejun; Rooney, William L.

2016-05-01

The next generation of plant breeding progress requires accurately estimating plant growth and development parameters to be made over routine intervals within large field experiments. Hand measurements are laborious and time consuming and the most promising tools under development are sensors carried by ground vehicles or unmanned aerial vehicles, with each specific vehicle having unique limitations. Previously available ground vehicles have primarily been restricted to monitoring shorter crops or early growth in corn and sorghum, since plants taller than a meter could be damaged by a tractor or spray rig passing over them. Here we have designed two and already constructed one of these self-propelled ground vehicles with adjustable heights that can clear mature corn and sorghum without damage (over three meters of clearance), which will work for shorter row crops as well. In addition to regular RGB image capture, sensor suites are incorporated to estimate plant height, vegetation indices, canopy temperature and photosynthetically active solar radiation, all referenced using RTK GPS to individual plots. These ground vehicles will be useful to validate data collected from unmanned aerial vehicles and support hand measurements taken on plots.

Overview of recent endeavors on personal aerial vehicles: A focus on the US and Europe led research activities

NASA Astrophysics Data System (ADS)

Liu, Yaolong; Kreimeier, Michael; Stumpf, Eike; Zhou, Yaoming; Liu, Hu

2017-05-01

Personal aerial vehicles, an innovative transport mode to bridge the niche between scheduled airliners and ground transport, are seen by aviation researchers and engineers as a solution to provide fast urban on-demand mobility. This paper reviews recent research efforts on the personal aerial vehicle (PAV), with a focus on the US and Europe led research activities. As an extension of the programmatic level overview, several enabling technologies, such as vertical/short take-off and landing (V/STOL), automation, distributed electric propulsion, which might promote the deployment of PAVs, are introduced and discussed. Despite the dramatic innovation in PAV concept development and related technologies, some challenging issues remain, especially safety, infrastructure and public acceptance. As such, further efforts by many stakeholders are required to enable the real implementation and application of PAVs.

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.

The Defense Airborne Reconnaissance Office Unmanned Aerial Vehicle (UAV) Annual Report FY 1996.

DTIC Science & Technology

1996-11-06

i>’ ’" UAV Annual Report FY1996 6 November 1996 L DEFENSE MRBOBNEiSCONNAGSAHCEC UAVANNUAL REPORT OUR SECOND UNMANNED AERIAL VEHICLE (UAV...ANNUAL REPORT provides an overview of the Defense Department’s UAV program activities for fiscal year (FY) 1996 . The Defense Airborne Reconnaissance...significant accomplishments that UAVs have achieved this past year, FY 1996 . Simply stated, UAVs are moving from words to deeds. They are being recognized in

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.

Aerial Explorers and Robotic Ecosystems

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Greg

2004-01-01

A unique bio-inspired approach to autonomous aerial vehicle, a.k.a. aerial explorer technology is discussed. The work is focused on defining and studying aerial explorer mission concepts, both as an individual robotic system and as a member of a small robotic "ecosystem." Members of this robotic ecosystem include the aerial explorer, air-deployed sensors and robotic symbiotes, and other assets such as rovers, landers, and orbiters.

From Antarctica to space: Use of telepresence and virtual reality in control of remote vehicles

NASA Technical Reports Server (NTRS)

Stoker, Carol; Hine, Butler P., III; Sims, Michael; Rasmussen, Daryl; Hontalas, Phil; Fong, Terrence W.; Steele, Jay; Barch, Don; Andersen, Dale; Miles, Eric

1994-01-01

In the Fall of 1993, NASA Ames deployed a modified Phantom S2 Remotely-Operated underwater Vehicle (ROV) into an ice-covered sea environment near McMurdo Science Station, Antarctica. This deployment was part of the antarctic Space Analog Program, a joint program between NASA and the National Science Foundation to demonstrate technologies relevant for space exploration in realistic field setting in the Antarctic. The goal of the mission was to operationally test the use of telepresence and virtual reality technology in the operator interface to a remote vehicle, while performing a benthic ecology study. The vehicle was operated both locally, from above a dive hole in the ice through which it was launched, and remotely over a satellite communications link from a control room at NASA's Ames Research Center. Local control of the vehicle was accomplished using the standard Phantom control box containing joysticks and switches, with the operator viewing stereo video camera images on a stereo display monitor. Remote control of the vehicle over the satellite link was accomplished using the Virtual Environment Vehicle Interface (VEVI) control software developed at NASA Ames. The remote operator interface included either a stereo display monitor similar to that used locally or a stereo head-mounted head-tracked display. The compressed video signal from the vehicle was transmitted to NASA Ames over a 768 Kbps satellite channel. Another channel was used to provide a bi-directional Internet link to the vehicle control computer through which the command and telemetry signals traveled, along with a bi-directional telephone service. In addition to the live stereo video from the satellite link, the operator could view a computer-generated graphic representation of the underwater terrain, modeled from the vehicle's sensors. The virtual environment contained an animate graphic model of the vehicle which reflected the state of the actual vehicle, along with ancillary information such

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

DoD Comprehensive Military Unmanned Aerial Vehicle Smart Device Ground Control Station Threat Model

DTIC Science & Technology

2015-04-01

design , imple- mentation, and test evaluation were interviewed to evaluate the existing gaps in the DoD processes for cybersecurity. This group exposed...such as antenna design and signal reception have made satellite communication networks a viable solution for smart devices on the battlefield...DoD Comprehensive Military Unmanned AERIAL VEHICLE SMART DEVICE GROUND CONTROL STATION THREAT MODEL  Image designed by Diane Fleischer Report

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.

Outlier and target detection in aerial hyperspectral imagery: a comparison of traditional and percentage occupancy hit or miss transform techniques

NASA Astrophysics Data System (ADS)

Young, Andrew; Marshall, Stephen; Gray, Alison

2016-05-01

The use of aerial hyperspectral imagery for the purpose of remote sensing is a rapidly growing research area. Currently, targets are generally detected by looking for distinct spectral features of the objects under surveillance. For example, a camouflaged vehicle, deliberately designed to blend into background trees and grass in the visible spectrum, can be revealed using spectral features in the near-infrared spectrum. This work aims to develop improved target detection methods, using a two-stage approach, firstly by development of a physics-based atmospheric correction algorithm to convert radiance into re ectance hyperspectral image data and secondly by use of improved outlier detection techniques. In this paper the use of the Percentage Occupancy Hit or Miss Transform is explored to provide an automated method for target detection in aerial hyperspectral imagery.

Integrated consensus-based frameworks for unmanned vehicle routing and targeting assignment

NASA Astrophysics Data System (ADS)

Barnawi, Waleed T.

Unmanned aerial vehicles (UAVs) are increasingly deployed in complex and dynamic environments to perform multiple tasks cooperatively with other UAVs that contribute to overarching mission effectiveness. Studies by the Department of Defense (DoD) indicate future operations may include anti-access/area-denial (A2AD) environments which limit human teleoperator decision-making and control. This research addresses the problem of decentralized vehicle re-routing and task reassignments through consensus-based UAV decision-making. An Integrated Consensus-Based Framework (ICF) is formulated as a solution to the combined single task assignment problem and vehicle routing problem. The multiple assignment and vehicle routing problem is solved with the Integrated Consensus-Based Bundle Framework (ICBF). The frameworks are hierarchically decomposed into two levels. The bottom layer utilizes the renowned Dijkstra's Algorithm. The top layer addresses task assignment with two methods. The single assignment approach is called the Caravan Auction Algorithm (CarA) Algorithm. This technique extends the Consensus-Based Auction Algorithm (CBAA) to provide awareness for task completion by agents and adopt abandoned tasks. The multiple assignment approach called the Caravan Auction Bundle Algorithm (CarAB) extends the Consensus-Based Bundle Algorithm (CBBA) by providing awareness for lost resources, prioritizing remaining tasks, and adopting abandoned tasks. Research questions are investigated regarding the novelty and performance of the proposed frameworks. Conclusions regarding the research questions will be provided through hypothesis testing. Monte Carlo simulations will provide evidence to support conclusions regarding the research hypotheses for the proposed frameworks. The approach provided in this research addresses current and future military operations for unmanned aerial vehicles. However, the general framework implied by the proposed research is adaptable to any unmanned

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.

Orbital Maneuvering Vehicle (OMV) remote servicing kit

NASA Technical Reports Server (NTRS)

Brown, Norman S.

1988-01-01

With the design and development of the Orbital Maneuvering Vehicle (OMV) progressing toward an early 1990 initial operating capability (IOC), a new era in remote space operations will evolve. The logical progression to OMV front end kits would make available in situ satellite servicing, repair, and consummables resupply to the satellite community. Several conceptual design study efforts are defining representative kits (propellant tanks, debris recovery, module servicers); additional focus must also be placed on an efficient combination module servicer and consummables resupply kit. A remote servicer kit of this type would be designed to perform many of the early maintenance/resupply tasks in both nominal and high inclination orbits. The kit would have the capability to exchange Orbital Replacement Units (ORUs), exchange propellant tanks, and/or connect fluid transfer umbilicals. Necessary transportation system functions/support could be provided by interfaces with the OMV, Shuttle (STS), or Expendable Launch Vehicle (ELV). Specific remote servicer kit designs, as well as ground and flight demonstrations of servicer technology are necessary to prepare for the potential overwhelming need. Ground test plans should adhere to the component/system/breadboard test philosophy to assure maximum capability of one-g testing. The flight demonstration(s) would most likely be a short duration, Shuttle-bay experiment to validate servicer components requiring a micro-g environment.

Multi-Mode Estimation for Small Fixed Wing Unmanned Aerial Vehicle Localization Based on a Linear Matrix Inequality Approach

PubMed Central

Elzoghby, Mostafa; Li, Fu; Arafa, Ibrahim. I.; Arif, Usman

2017-01-01

Information fusion from multiple sensors ensures the accuracy and robustness of a navigation system, especially in the absence of global positioning system (GPS) data which gets degraded in many cases. A way to deal with multi-mode estimation for a small fixed wing unmanned aerial vehicle (UAV) localization framework is proposed, which depends on utilizing a Luenberger observer-based linear matrix inequality (LMI) approach. The proposed estimation technique relies on the interaction between multiple measurement modes and a continuous observer. The state estimation is performed in a switching environment between multiple active sensors to exploit the available information as much as possible, especially in GPS-denied environments. Luenberger observer-based projection is implemented as a continuous observer to optimize the estimation performance. The observer gain might be chosen by solving a Lyapunov equation by means of a LMI algorithm. Convergence is achieved by utilizing the linear matrix inequality (LMI), based on Lyapunov stability which keeps the dynamic estimation error bounded by selecting the observer gain matrix (L). Simulation results are presented for a small UAV fixed wing localization problem. The results obtained using the proposed approach are compared with a single mode Extended Kalman Filter (EKF). Simulation results are presented to demonstrate the viability of the proposed strategy. PMID:28420214

Characterization of Vegetation using the UC Davis Remote Sensing Testbed

NASA Astrophysics Data System (ADS)

Falk, M.; Hart, Q. J.; Bowen, K. S.; Ustin, S. L.

2006-12-01

Remote sensing provides information about the dynamics of the terrestrial biosphere with continuous spatial and temporal coverage on many different scales. We present the design and construction of a suite of instrument modules and network infrastructure with size, weight and power constraints suitable for small scale vehicles, anticipating vigorous growth in unmanned aerial vehicles (UAV) and other mobile platforms. Our approach provides the rapid deployment and low cost acquisition of high aerial imagery for applications requiring high spatial resolution and revisits. The testbed supports a wide range of applications, encourages remote sensing solutions in new disciplines and demonstrates the complete range of engineering knowledge required for the successful deployment of remote sensing instruments. The initial testbed is deployed on a Sig Kadet Senior remote controlled plane. It includes an onboard computer with wireless radio, GPS, inertia measurement unit, 3-axis electronic compass and digital cameras. The onboard camera is either a RGB digital camera or a modified digital camera with red and NIR channels. Cameras were calibrated using selective light sources, an integrating spheres and a spectrometer, allowing for the computation of vegetation indices such as the NDVI. Field tests to date have investigated technical challenges in wireless communication bandwidth limits, automated image geolocation, and user interfaces; as well as image applications such as environmental landscape mapping focusing on Sudden Oak Death and invasive species detection, studies on the impact of bird colonies on tree canopies, and precision agriculture.

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

The First Government Sanctioned Delivery of Medical Supplies by Remotely Controlled Unmanned Aerial System (UAS)

NASA Technical Reports Server (NTRS)

Howell, Charles T., III; Jones, Frank; Thorson, Taylor; Grube, Richard; Mellanson, Cecil; Joyce, Lee; Coggin, John; Kennedy, Jack

2016-01-01

The first government sanctioned delivery of medical supplies by UAS occurred at Wise, Virginia, on July 17, 2015. The "Let's Fly Wisely" event was a demonstration of the humanitarian use of UAS to facilitate delivery of medical supplies to remote or otherwise difficult-to-reach areas. The event was the result of coordinated efforts by a partnership which included the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC), Virginia Polytechnic Institute, the Mid-Atlantic Aviation Partnership (MAAP), Flirtey Corporation, Lonesome Pine Airport, Remote Area Medical (RAM), Health Wagon, SEESPAN Aerial Interactive, Rx Partnership, and Wise County, Virginia. The historic event occurred during the annual Remote Area Medical clinic at the Wise County Fairgrounds. The medical supplies in small packages were delivered to the Wise County Fairgrounds from the Lonesome Pine Airport by UAS operated by Firtey. A larger supply of medical supplies were delivered to the Lonesome Pine Airport from the Tazewell County Airport by NASA Langley's SR22 UAS Surrogate Research aircraft. The UAS Surrogate aircraft was remotely controlled for most of the flight by a UAS Ground Control Station located at the Lonesome Pine Airport. The medical supplies were delivered from the UAS Surrogate to Flirtey for final delivery by Hex Multi-Rotor UAS in smaller packages and multiple trips to the fairgrounds. A Certificate of Authorization (COA) issued by the Federal Aviation Administration (FAA) designated the site as an authorized UAS test site. The paper will present additional details of the historic delivery of pharmaceuticals by UAS during the "Let's Fly Wisely" event. The paper will also provide details of NASA's SR22 UAS Surrogate Research aircraft. The UAS Surrogate was designed to investigate the procedures, aircraft sensors and other systems that may be required to allow Unmanned Aerial Systems (UAS) to safely operate with manned aircraft in the National Airspace

Titan AVIATR - Aerial Vehicle for In Situ and Airborne Titan Reconnaissance

NASA Astrophysics Data System (ADS)

Kattenhorn, Simon A.; Barnes, J. W.; McKay, C. P.; Lemke, L.; Beyer, R. A.; Radebaugh, J.; Adamkovics, M.; Atkinson, D. H.; Burr, D. M.; Colaprete, T.; Foch, R.; Le Mouélic, S.; Merrison, J.; Mitchell, J.; Rodriguez, S.; Schaller, E.

2010-10-01

Titan AVIATR - Aerial Vehicle for In Situ and Airborne Titan Reconnaissance - is a small (120 kg), nuclear-powered Titan airplane in the Discovery/New Frontiers class based on the concept of Lemke (2008 IPPW). The scientific goals of the mission are designed around the unique flexibility offered by an airborne platform: to explore Titan's diversity of surface landforms, processes, and compositions, as well as to study and measure the atmospheric circulation, aerosols, and humidity. AVIATR would address and surpass many of the science goals of hot-air balloons in Titan flagship studies. The strawman instrument payload is narrowly focused on the stated scientific objectives. The optical remote sensing suite comprises three instruments - an off-nadir high-resolution 2-micron camera, a horizon-looking 5-micron imager, and a 1-6 micron pushbroom near-infrared spectrometer. The in situ instruments include atmospheric structure, a methane humidity sensor, and a raindrop detector. An airplane has operational advantages over a balloon. Its piloted nature allows a go-to capability to image locations of interest in real time, thereby allowing for directed exploration of many features of primary geologic interest: Titan's sand dunes, mountains, craters, channels, and lakes. Subsequent imaging can capture changes in these features during the primary mission. AVIATR can fly predesigned routes, building up large context mosaics of areas of interest before swooping down to low altitude to acquire high-resolution images at 30-cm spatial sampling, similar to that of HiRISE at Mars. The elevation flexibility of the airplane allows us to acquire atmospheric profiles as a function of altitude at any desired location. Although limited by the direct-to-Earth downlink bandwidth, the total scientific data return from AVIATR will be >40 times that returned from Huygens. To maximize the science per bit, novel data storage and downlink techniques will be employed, including lossy compression

Design of Omni Directional Remotely Operated Vehicle (ROV)

NASA Astrophysics Data System (ADS)

Rahimuddin; Hasan, Hasnawiya; Rivai, Haryanti A.; Iskandar, Yanu; Claudio, P.

2018-02-01

Nowadays, underwater activities are increased with the increase of oil resources finding. The gap between demand and supply of oil and gas cause engineers to find oil and gas resources in deep water. In other side, high risk of working in deep underwater environment can cause a dangerous situation for human. Therefore, many research activities are developing an underwater vehicle to replace the human’s work such as ROV or Remotely Operated Vehicles. The vehicle operated using tether to transport the signals and electric power from the surface vehicle. Arrangements of weight, buoyancy, and the propeller placements are significant aspect in designing the vehicle’s performance. This paper presents design concept of ROV for survey and observation the underwater objects with interaction vectored propellers used for vehicle’s motions.

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.

Intelligent model-based diagnostics for vehicle health management

NASA Astrophysics Data System (ADS)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

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.

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.

An Empirical Study on Operator Interface Design for Handheld Devices to Control Micro Aerial Vehicles

DTIC Science & Technology

2010-10-01

An Empirical Study on Operator Interface Design for Handheld Devices to Control Micro Aerial Vehicles Ming Hou...Report DRDC Toronto TR 2010-075 October 2010 An Empirical Study on Operator Interface Design for Handheld Devices to...drives the need for a small and light controller which will not hinder a soldier carrying it. This requirement brings an issue of designing an

Flexible Wing Base Micro Aerial Vehicles: Composite Materials for Micro Air Vehicles

NASA Technical Reports Server (NTRS)

Ifju, Peter G.; Ettinger, Scott; Jenkins, David; Martinez, Luis

2002-01-01

This paper will discuss the development of the University of Florida's Micro Air Vehicle concept. A series of flexible wing based aircraft that possess highly desirable flight characteristics were developed. Since computational methods to accurately model flight at the low Reynolds numbers associated with this scale are still under development, our effort has relied heavily on trial and error. Hence a time efficient method was developed to rapidly produce prototype designs. The airframe and wings are fabricated using a unique process that incorporates carbon fiber composite construction. Prototypes can be fabricated in around five man-hours, allowing many design revisions to be tested in a short period of time. The resulting aircraft are far more durable, yet lighter, than their conventional counterparts. This process allows for thorough testing of each design in order to determine what changes were required on the next prototype. The use of carbon fiber allows for wing flexibility without sacrificing durability. The construction methods developed for this project were the enabling technology that allowed us to implement our designs. The resulting aircraft were the winning entries in the International Micro Air Vehicle Competition for the past two years. Details of the construction method are provided in this paper along with a background on our flexible wing concept.

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.

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

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.

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 (...

Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar

PubMed Central

Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

2017-01-01

Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns. PMID:28106819

Remote software upload techniques in future vehicles and their performance analysis

NASA Astrophysics Data System (ADS)

Hossain, Irina

Updating software in vehicle Electronic Control Units (ECUs) will become a mandatory requirement for a variety of reasons, for examples, to update/fix functionality of an existing system, add new functionality, remove software bugs and to cope up with ITS infrastructure. Software modules of advanced vehicles can be updated using Remote Software Upload (RSU) technique. The RSU employs infrastructure-based wireless communication technique where the software supplier sends the software to the targeted vehicle via a roadside Base Station (BS). However, security is critically important in RSU to avoid any disasters due to malfunctions of the vehicle or to protect the proprietary algorithms from hackers, competitors or people with malicious intent. In this thesis, a mechanism of secure software upload in advanced vehicles is presented which employs mutual authentication of the software provider and the vehicle using a pre-shared authentication key before sending the software. The software packets are sent encrypted with a secret key along with the Message Digest (MD). In order to increase the security level, it is proposed the vehicle to receive more than one copy of the software along with the MD in each copy. The vehicle will install the new software only when it receives more than one identical copies of the software. In order to validate the proposition, analytical expressions of average number of packet transmissions for successful software update is determined. Different cases are investigated depending on the vehicle's buffer size and verification methods. The analytical and simulation results show that it is sufficient to send two copies of the software to the vehicle to thwart any security attack while uploading the software. The above mentioned unicast method for RSU is suitable when software needs to be uploaded to a single vehicle. Since multicasting is the most efficient method of group communication, updating software in an ECU of a large number of vehicles

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.

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

Unmanned aerial systems for forest reclamation monitoring: throwing balloons in the air

NASA Astrophysics Data System (ADS)

Andrade, Rita; Vaz, Eric; Panagopoulos, Thomas; Guerrero, Carlos

2014-05-01

Wildfires are a recurrent phenomenon in Mediterranean landscapes, deteriorating environment and ecosystems, calling out for adequate land management. Monitoring burned areas enhances our abilities to reclaim them. Remote sensing has become an increasingly important tool for environmental assessment and land management. It is fast, non-intrusive, and provides continuous spatial coverage. This paper reviews remote sensing methods, based on space-borne, airborne or ground-based multispectral imagery, for monitoring the biophysical properties of forest areas for site specific management. The usage of satellite imagery for land use management has been frequent in the last decades, it is of great use to determine plants health and crop conditions, allowing a synergy between the complexity of environment, anthropogenic landscapes and multi-temporal understanding of spatial dynamics. Aerial photography increments on spatial resolution, nevertheless it is heavily dependent on airborne availability as well as cost. Both these methods are required for wide areas management and policy planning. Comprising an active and high resolution imagery source, that can be brought at a specific instance, reducing cost while maintaining locational flexibility is of utmost importance for local management. In this sense, unmanned aerial vehicles provide maximum flexibility with image collection, they can incorporate thermal and multispectral sensors, however payload and engine operation time limit flight time. Balloon remote sensing is becoming increasingly sought after for site specific management, catering rapid digital analysis, permitting greater control of the spatial resolution as well as of datasets collection in a given time. Different wavelength sensors may be used to map spectral variations in plant growth, monitor water and nutrient stress, assess yield and plant vitality during different stages of development. Proximity could be an asset when monitoring forest plants vitality

Laser Doppler velocimeter aerial spray measurements

NASA Technical Reports Server (NTRS)

Zalay, A. D.; Eberle, W. R.; Howle, R. E.; Shrider, K. R.

1978-01-01

An experimental research program for measuring the location, spatial extent, and relative concentration of airborne spray clouds generated by agricultural aircraft is described. The measurements were conducted with a ground-based laser Doppler velocimeter. The remote sensing instrumentation, experimental tests, and the results of the flight tests are discussed. The cross section of the aerial spray cloud and the observed location, extent, and relative concentration of the airborne particulates are presented. It is feasible to use a mobile laser Doppler velocimeter to track and monitor the transport and dispersion of aerial spray generated by an agricultural aircraft.

Quantifying Aerial Concentrations of Maize Pollen in the Atmospheric Surface Layer Using Remote-Piloted Airplanes and Lagrangian Stochastic Modeling

NASA Astrophysics Data System (ADS)

Aylor, Donald E.; Boehm, Matthew T.; Shields, Elson J.

2006-07-01

The extensive adoption of genetically modified crops has led to a need to understand better the dispersal of pollen in the atmosphere because of the potential for unwanted movement of genetic traits via pollen flow in the environment. The aerial dispersal of maize pollen was studied by comparing the results of a Lagrangian stochastic (LS) model with pollen concentration measurements made over cornfields using a combination of tower-based rotorod samplers and airborne radio-controlled remote-piloted vehicles (RPVs) outfitted with remotely operated pollen samplers. The comparison between model and measurements was conducted in two steps. In the first step, the LS model was used in combination with the rotorod samplers to estimate the pollen release rate Q for each sampling period. In the second step, a modeled value for the concentration Cmodel, corresponding to each RPV measured value Cmeasure, was calculated by simulating the RPV flight path through the LS model pollen plume corresponding to the atmospheric conditions, field geometry, wind direction, and source strength. The geometric mean and geometric standard deviation of the ratio Cmodel/Cmeasure over all of the sampling periods, except those determined to be upwind of the field, were 1.42 and 4.53, respectively, and the lognormal distribution corresponding to these values was found to fit closely the PDF of Cmodel/Cmeasure. Model output was sensitive to the turbulence parameters, with a factor-of-100 difference in the average value of Cmodel over the range of values encountered during the experiment. In comparison with this large potential variability, it is concluded that the average factor of 1.4 between Cmodel and Cmeasure found here indicates that the LS model is capable of accurately predicting, on average, concentrations over a range of atmospheric conditions.

The MEDEA/JASON remotely operated vehicle system

NASA Astrophysics Data System (ADS)

Ballard, Robert D.

1993-08-01

The remotely operated vehicle (ROV) system MEDEA/JASON has been under development for the last decade. Adter a number of engineering test cruises, including the discovery of the R.M.S. Titanic and the German Battleship Bismarck, this ROV system is now being implemented in oceanographic investigations. This paper explains its development history and its unique ability to carry out a broad range of scientific research.

Unmanned aerial vehicles (UAVs) for surveying marine fauna: a dugong case study.

PubMed

Hodgson, Amanda; Kelly, Natalie; Peel, David

2013-01-01

Aerial surveys of marine mammals are routinely conducted to assess and monitor species' habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km(2) area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as 'certain' (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys.

Unmanned Aerial Vehicles (UAVs) for Surveying Marine Fauna: A Dugong Case Study

PubMed Central

Hodgson, Amanda; Kelly, Natalie; Peel, David

2013-01-01

Aerial surveys of marine mammals are routinely conducted to assess and monitor species’ habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km2 area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as ‘certain’ (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys. PMID:24223967

A potential remote sensor of CO in vehicle exhausts using 2.3 µm diode lasers

NASA Astrophysics Data System (ADS)

Wang, Jian; Maiorov, Mikhail; Jeffries, Jay B.; Garbuzov, Dmitri Z.; Connolly, John C.; Hanson, Ronald K.

2000-11-01

The potential for on-road remote sensing of vehicle exhausts using 2.3 µm diode-laser-absorption-based CO sensors is examined. Using a wavelength-modulation- spectroscopy (WMS) technique, 20 ppm sensitivity with a detection bandwidth of ≃1.5 kHz is demonstrated in laboratory experiments, which implies the ability to monitor CO emissions from even the cleanest combustion-powered vehicles. The influence of the temperature and composition of the exhaust gas on the inferred CO concentration through both linestrength and linewidth is also investigated and we propose a novel approach to reduce these effects to ±3% in the typical exhaust temperature range of 300-700 K. Thus, sensitive and remote measurements of vehicular CO effluent are possible without knowing the exact temperature or composition of the exhaust. This influence of temperature is further exploited to suggest a two-line CO2-absorption thermometry method with a large temperature sensitivity to identify cold-start vehicles.

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.

Remotely piloted vehicle: Application of the GRASP analysis method

NASA Technical Reports Server (NTRS)

Andre, W. L.; Morris, J. B.

1981-01-01

The application of General Reliability Analysis Simulation Program (GRASP) to the remotely piloted vehicle (RPV) system is discussed. The model simulates the field operation of the RPV system. By using individual component reliabilities, the overall reliability of the RPV system is determined. The results of the simulations are given in operational days. The model represented is only a basis from which more detailed work could progress. The RPV system in this model is based on preliminary specifications and estimated values. The use of GRASP from basic system definition, to model input, and to model verification is demonstrated.

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote

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.

Aerial detection surveys in the United States

Treesearch

E. W. Johnson; D. Wittwer

2006-01-01

Aerial detection surveys, also known as aerial sketchmapping, is a remote sensing technique of observing forest change events from an aircraft and documenting them manually onto a map. Data from aerial surveys have become an important component of the Forest Health Monitoring, a national program designed to determine the status, changes, and trends in indicators of...

Remote sensing and image interpretation

NASA Technical Reports Server (NTRS)

Lillesand, T. M.; Kiefer, R. W. (Principal Investigator)

1979-01-01

A textbook prepared primarily for use in introductory courses in remote sensing is presented. Topics covered include concepts and foundations of remote sensing; elements of photographic systems; introduction to airphoto interpretation; airphoto interpretation for terrain evaluation; photogrammetry; radiometric characteristics of aerial photographs; aerial thermography; multispectral scanning and spectral pattern recognition; microwave sensing; and remote sensing from space.

Feasibility of an Extended-Duration Aerial Platform Using Autonomous Multi-Rotor Vehicle Swapping and Battery Management

DTIC Science & Technology

2017-12-01

AN EXTENDED-DURATION AERIAL PLATFORM USING AUTONOMOUS MULTI-ROTOR VEHICLE SWAPPING AND BATTERY MANAGEMENT by Alexander G. Williams December...Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time...of information . Send comments regarding this burden estimate or any other aspect of this collection of information , including suggestions for

Unmanned aerial survey of fallen trees in a deciduous broadleaved forest in eastern Japan.

PubMed

Inoue, Tomoharu; Nagai, Shin; Yamashita, Satoshi; Fadaei, Hadi; Ishii, Reiichiro; Okabe, Kimiko; Taki, Hisatomo; Honda, Yoshiaki; Kajiwara, Koji; Suzuki, Rikie

2014-01-01

Since fallen trees are a key factor in biodiversity and biogeochemical cycling, information about their spatial distribution is of use in determining species distribution and nutrient and carbon cycling in forest ecosystems. Ground-based surveys are both time consuming and labour intensive. Remote-sensing technology can reduce these costs. Here, we used high-spatial-resolution aerial photographs (0.5-1.0 cm per pixel) taken from an unmanned aerial vehicle (UAV) to survey fallen trees in a deciduous broadleaved forest in eastern Japan. In nine sub-plots we found a total of 44 fallen trees by ground survey. From the aerial photographs, we identified 80% to 90% of fallen trees that were >30 cm in diameter or >10 m in length, but missed many that were narrower or shorter. This failure may be due to the similarity of fallen trees to trunks and branches of standing trees or masking by standing trees. Views of the same point from different angles may improve the detection rate because they would provide more opportunity to detect fallen trees hidden by standing trees. Our results suggest that UAV surveys will make it possible to monitor the spatial and temporal variations in forest structure and function at lower cost.

Unmanned Aerial Survey of Fallen Trees in a Deciduous Broadleaved Forest in Eastern Japan

PubMed Central

Inoue, Tomoharu; Nagai, Shin; Yamashita, Satoshi; Fadaei, Hadi; Ishii, Reiichiro; Okabe, Kimiko; Taki, Hisatomo; Honda, Yoshiaki; Kajiwara, Koji; Suzuki, Rikie

2014-01-01

Since fallen trees are a key factor in biodiversity and biogeochemical cycling, information about their spatial distribution is of use in determining species distribution and nutrient and carbon cycling in forest ecosystems. Ground-based surveys are both time consuming and labour intensive. Remote-sensing technology can reduce these costs. Here, we used high-spatial-resolution aerial photographs (0.5–1.0 cm per pixel) taken from an unmanned aerial vehicle (UAV) to survey fallen trees in a deciduous broadleaved forest in eastern Japan. In nine sub-plots we found a total of 44 fallen trees by ground survey. From the aerial photographs, we identified 80% to 90% of fallen trees that were >30 cm in diameter or >10 m in length, but missed many that were narrower or shorter. This failure may be due to the similarity of fallen trees to trunks and branches of standing trees or masking by standing trees. Views of the same point from different angles may improve the detection rate because they would provide more opportunity to detect fallen trees hidden by standing trees. Our results suggest that UAV surveys will make it possible to monitor the spatial and temporal variations in forest structure and function at lower cost. PMID:25279817

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.

The development of the DAST I remotely piloted research vehicle for flight testing an active flutter suppression control system. Ph.D. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Grose, D. L.

1979-01-01

The development of the DAST I (drones for aerodynamic and structural testing) remotely piloted research vehicle is described. The DAST I is a highly modified BQM-34E/F Firebee II Supersonic Aerial Target incorporating a swept supercritical wing designed to flutter within the vehicle's flight envelope. The predicted flutter and rigid body characteristics are presented. A description of the analysis and design of an active flutter suppression control system (FSS) designed to increase the flutter boundary of the DAST wing (ARW-1) by a factor of 20% is given. The design and development of the digital remotely augmented primary flight control system and on-board analog backup control system is presented. An evaluation of the near real-time flight flutter testing methods is made by comparing results of five flutter testing techniques on simulated DAST I flutter data. The development of the DAST ARW-1 state variable model used to generate time histories of simulated accelerometer responses is presented. This model uses control surface commands and a Dryden model gust as inputs. The feasibility of the concept of extracting open loop flutter characteristics from closed loop FSS responses was examined. It was shown that open loop characteristics can be determined very well from closed loop subcritical responses.

A new tool for the rapid remote detection of leaks from subsea pipelines during remotely operated vehicle inspections

NASA Astrophysics Data System (ADS)

McStay, D.; McIlroy, J.; Forte, A.; Lunney, F.; Greenway, T.; Thabeth, K.; Dean, G.

2005-06-01

A new 2000 m depth rated subsea sensor that can effectively, rapidly and remotely detect leaks of fluorescein dye, leak detection chemicals and hydraulic fluids from underwater structures is reported. The system utilizes ultra-bright LED technology to project a structured beam of light, at a wavelength suitable to excite the fluorescence of the target material, into the water column. The resultant fluorescence is collected and digital signal processing used to extract the intensity. The system is capable of detecting ppm concentrations of fluorescein at a range of 2.5 m in water in real time. The ability to stand-off from subsea structures, while rapidly detecting the chemicals makes the system highly suited to subsea leak inspections with remotely operated vehicles or autonomous underwater vehicles, as it allows the vehicles to be flown quickly and safely over the structure to be inspected. This increases both the speed and effectiveness of the inspection. The remote detection capability is also highly effective for probing complex underwater structures. The system has been successfully used in real subsea survey applications and has been found to be effective, user friendly and to dramatically reduce inspection times and hence costs.

Remote Sensing

ERIC Educational Resources Information Center

Williams, Richard S., Jr.; Kover, Allan W.

1978-01-01

The steady growth of the Landsat image data base continues to make this kind of remotely sensed data second only to aerial photographs in use by geoscientists who employ image data in their research. Article reviews data uses, meetings and symposia, publications, problems, and future trends. (Author/MA)

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.

Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots

PubMed Central

Lelong, Camille C. D.; Burger, Philippe; Jubelin, Guillaume; Roux, Bruno; Labbé, Sylvain; Baret, Frédéric

2008-01-01

This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In 2005, these instruments were fitted to powered glider and parachute, and flown at six dates staggered over the crop season. We monitored ten varieties of wheat, grown in trial micro-plots in the South-West of France. For each date, we acquired multiple views in four spectral bands corresponding to blue, green, red, and near-infrared. We then performed accurate corrections of image vignetting, geometric distortions, and radiometric bidirectional effects. Afterwards, we derived for each experimental micro-plot several vegetation indexes relevant for vegetation analyses. Finally, we sought relationships between these indexes and field-measured biophysical parameters, both generic and date-specific. Therefore, we established a robust and stable generic relationship between, in one hand, leaf area index and NDVI and, in the other hand, nitrogen uptake and GNDVI. Due to a high amount of noise in the data, it was not possible to obtain a more accurate model for each date independently. A validation protocol showed that we could expect a precision level of 15% in the biophysical parameters estimation while using these relationships. PMID:27879893

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 ...

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.

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.

An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

PubMed

Li, Bai; Gong, Li-gang; Yang, Wen-lun

2014-01-01

Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

On Board Data Acquisition System with Intelligent Transducers for Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Rochala, Zdzisław

2012-02-01

This report presents conclusions from research project no. ON50900363 conducted at the Mechatronics Department, Military University of Technology in the years 2007-2010. As the main object of the study involved the preparation of a concept and the implementation of an avionics data acquisition system intended for research during flight of unmanned aerial vehicles of the mini class, this article presents a design of an avionics system and describes equipment solutions of a distributed measurement system intended for data acquisition consisting of intelligent transducers. The data collected during a flight controlled by an operator confirmed proper operation of the individual components of the data acquisition system.

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.

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).

NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and

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.

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.

A methodology for dam inventory and inspection with remotely sensed data

NASA Technical Reports Server (NTRS)

Berger, J. P.; Philipson, W. R.; Liang, T.

1979-01-01

A methodology is presented to increase the efficiency and accuracy of dam inspection by incorporating remote sensing techniques into field-based monitoring programs. The methodology focuses on New York State and places emphasis on readily available remotely sensed data aerial photographs and Landsat data. Aerial photographs are employed in establishing a state-wide data base, referenced on county highway and U.S. Geological Survey 1:24,000 scale, topographic maps. Data base updates are conducted by county or region, using aerial photographs or Landsat as a primary source of information. Field investigations are generally limited to high-hazard or special problem dams, or to dams which cannot be assessed adequately with aerial photographs. Although emphasis is placed on available data, parameters for acquiring new aircraft data for assessing dam condition are outlined. Large scale (1:10,000) vertical, stereoscopic, color-infrared photography, flown during the spring or fall, is recommended.

GPS Remote Sensing Measurements Using Aerosonde UAV

NASA Technical Reports Server (NTRS)

Grant, Michael S.; Katzberg, Stephen J.; Lawrence, R. W.

2005-01-01

In February 2004, a NASA-Langley GPS Remote Sensor (GPSRS) unit was flown on an Aerosonde unmanned aerial vehicle (UAV) from the Wallops Flight Facility (WFF) in Virginia. Using direct and surface-reflected 1.575 GHz coarse acquisition (C/A) coded GPS signals, remote sensing measurements were obtained over land and portions of open water. The strength of the surface-reflected GPS signal is proportional to the amount of moisture in the surface, and is also influenced by surface roughness. Amplitude and other characteristics of the reflected signal allow an estimate of wind speed over open water. In this paper we provide a synopsis of the instrument accommodation requirements, installation procedures, and preliminary results from what is likely the first-ever flight of a GPS remote sensing instrument on a UAV. The correct operation of the GPSRS unit on this flight indicates that Aerosonde-like UAV's can serve as platforms for future GPS remote sensing science missions.

FluidCam 1&2 - UAV-based Fluid Lensing Instruments for High-Resolution 3D Subaqueous Imaging and Automated Remote Biosphere Assessment of Reef Ecosystems

NASA Astrophysics Data System (ADS)

Chirayath, V.; Instrella, R.

2016-02-01

We present NASA ESTO FluidCam 1 & 2, Visible and NIR Fluid-Lensing-enabled imaging payloads for Unmanned Aerial Vehicles (UAVs). Developed as part of a focused 2014 earth science technology grant, FluidCam 1&2 are Fluid-Lensing-based computational optical imagers designed for automated 3D mapping and remote sensing of underwater coastal targets from airborne platforms. Fluid Lensing has been used to map underwater reefs in 3D in American Samoa and Hamelin Pool, Australia from UAV platforms at sub-cm scale, which has proven a valuable tool in modern marine research for marine biosphere assessment and conservation. We share FluidCam 1&2 instrument validation and testing results as well as preliminary processed data from field campaigns. Petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk reefs demonstrate broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to improving bathymetry data for physical oceanographic models and understanding climate change's impact on coastal zones, global oxygen production, carbon sequestration.

FluidCam 1&2 - UAV-Based Fluid Lensing Instruments for High-Resolution 3D Subaqueous Imaging and Automated Remote Biosphere Assessment of Reef Ecosystems

NASA Astrophysics Data System (ADS)

Chirayath, V.

2015-12-01

We present NASA ESTO FluidCam 1 & 2, Visible and NIR Fluid-Lensing-enabled imaging payloads for Unmanned Aerial Vehicles (UAVs). Developed as part of a focused 2014 earth science technology grant, FluidCam 1&2 are Fluid-Lensing-based computational optical imagers designed for automated 3D mapping and remote sensing of underwater coastal targets from airborne platforms. Fluid Lensing has been used to map underwater reefs in 3D in American Samoa and Hamelin Pool, Australia from UAV platforms at sub-cm scale, which has proven a valuable tool in modern marine research for marine biosphere assessment and conservation. We share FluidCam 1&2 instrument validation and testing results as well as preliminary processed data from field campaigns. Petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk reefs demonstrate broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to improving bathymetry data for physical oceanographic models and understanding climate change's impact on coastal zones, global oxygen production, carbon sequestration.

Hydrology with unmanned aerial vehicles (UAVs)

USDA-ARS?s Scientific Manuscript database

Hydrologic remote sensing currently depends on expensive and infrequent aircraft observations for validation of operational satellite products, typically conducted during field campaigns that also include ground-based measurements. With the advent of new, hydrologically-relevant satellite missions, ...

High Resolution Stratigraphic Mapping in Complex Terrain: A Comparison of Traditional Remote Sensing Techniques with Unmanned Aerial Vehicle - Structure from Motion Photogrammetry

NASA Astrophysics Data System (ADS)

Nesbit, P. R.; Hugenholtz, C.; Durkin, P.; Hubbard, S. M.; Kucharczyk, M.; Barchyn, T.

2016-12-01

Remote sensing and digital mapping have started to revolutionize geologic mapping in recent years as a result of their realized potential to provide high resolution 3D models of outcrops to assist with interpretation, visualization, and obtaining accurate measurements of inaccessible areas. However, in stratigraphic mapping applications in complex terrain, it is difficult to acquire information with sufficient detail at a wide spatial coverage with conventional techniques. We demonstrate the potential of a UAV and Structure from Motion (SfM) photogrammetric approach for improving 3D stratigraphic mapping applications within a complex badland topography. Our case study is performed in Dinosaur Provincial Park (Alberta, Canada), mapping late Cretaceous fluvial meander belt deposits of the Dinosaur Park formation amidst a succession of steeply sloping hills and abundant drainages - creating a challenge for stratigraphic mapping. The UAV-SfM dataset (2 cm spatial resolution) is compared directly with a combined satellite and aerial LiDAR dataset (30 cm spatial resolution) to reveal advantages and limitations of each dataset before presenting a unique workflow that utilizes the dense point cloud from the UAV-SfM dataset for analysis. The UAV-SfM dense point cloud minimizes distortion, preserves 3D structure, and records an RGB attribute - adding potential value in future studies. The proposed UAV-SfM workflow allows for high spatial resolution remote sensing of stratigraphy in complex topographic environments. This extended capability can add value to field observations and has the potential to be integrated with subsurface petroleum models.

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

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.

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.

Detection of Tree Crowns Based on Reclassification Using Aerial Images and LIDAR Data

NASA Astrophysics Data System (ADS)

Talebi, S.; Zarea, A.; Sadeghian, S.; Arefi, H.

2013-09-01

Tree detection using aerial sensors in early decades was focused by many researchers in different fields including Remote Sensing and Photogrammetry. This paper is intended to detect trees in complex city areas using aerial imagery and laser scanning data. Our methodology is a hierarchal unsupervised method consists of some primitive operations. This method could be divided into three sections, in which, first section uses aerial imagery and both second and third sections use laser scanners data. In the first section a vegetation cover mask is created in both sunny and shadowed areas. In the second section Rate of Slope Change (RSC) is used to eliminate grasses. In the third section a Digital Terrain Model (DTM) is obtained from LiDAR data. By using DTM and Digital Surface Model (DSM) we would get to Normalized Digital Surface Model (nDSM). Then objects which are lower than a specific height are eliminated. Now there are three result layers from three sections. At the end multiplication operation is used to get final result layer. This layer will be smoothed by morphological operations. The result layer is sent to WG III/4 to evaluate. The evaluation result shows that our method has a good rank in comparing to other participants' methods in ISPRS WG III/4, when assessed in terms of 5 indices including area base completeness, area base correctness, object base completeness, object base correctness and boundary RMS. With regarding of being unsupervised and automatic, this method is improvable and could be integrate with other methods to get best results.

The sky is the limit: reconstructing physical geography fieldwork from an aerial perspective

NASA Astrophysics Data System (ADS)

Williams, R.; Tooth, S.; Gibson, M.; Barrett, B.

2017-12-01

In an era of rapid geographical data acquisition, interpretations of remote sensing products (e.g. aerial photographs, satellite images, digital elevation models) are an integral part of many undergraduate geography degree schemes but there are fewer opportunities for collection and processing of primary remote sensing data. Unmanned aerial vehicles (UAVs) provide a relatively cheap opportunity to introduce the principles and practice of airborne remote sensing into fieldcourses, enabling students to learn about image acquisition, data processing and interpretation of derived products. Three case studies illustrate how a low cost DJI Phantom UAV can be used by students to acquire images that can be processed using off the shelf Structure-from-Motion photogrammetry software. Two case studies are drawn from an international fieldcourse that takes students to field sites that are the focus of current funded research whilst a third case study is from a course in topographic mapping. Results from a student questionnaire and analysis of assessed student reports showed that using UAVs in fieldwork enhanced student engagement with themes on their fieldcourse and equipped them with data processing skills. The derivation of bespoke orthophotos and Digital Elevation Models also provided students with opportunities to gain insight into the various data quality issues that are associated with aerial imagery acquisition and topographic reconstruction, although additional training is required to maximise this potential. Recognition of the successes and limitations of this teaching intervention provides scope for improving exercises that use UAVs and other technologies in future fieldcourses. UAVs are enabling both a reconstruction of how we measure the Earth's surface and a reconstruction of how students do fieldwork.

Analyzing the threat of unmanned aerial vehicles (UAV) to nuclear facilities

DOE PAGES

Solodov, Alexander; Williams, Adam; Al Hanaei, Sara; ...

2017-04-18

Unmanned aerial vehicles (UAV) are among the major growing technologies that have many beneficial applications, yet they can also pose a significant threat. Recently, several incidents occurred with UAVs violating privacy of the public and security of sensitive facilities, including several nuclear power plants in France. The threat of UAVs to the security of nuclear facilities is of great importance and is the focus of this work. This paper presents an overview of UAV technology and classification, as well as its applications and potential threats. We show several examples of recent security incidents involving UAVs in France, USA, and Unitedmore » Arab Emirates. Further, the potential threats to nuclear facilities and measures to prevent them are evaluated. The importance of measures for detection, delay, and response (neutralization) of UAVs at nuclear facilities are discussed. An overview of existing technologies along with their strength and weaknesses are shown. Finally, the results of a gap analysis in existing approaches and technologies is presented in the form of potential technological and procedural areas for research and development. Furthermore based on this analysis, directions for future work in the field can be devised and prioritized.« less

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.

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

A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments

PubMed Central

López, Elena; García, Sergio; Barea, Rafael; Bergasa, Luis M.; Molinos, Eduardo J.; Arroyo, Roberto; Romera, Eduardo; Pardo, Samuel

2017-01-01

One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory configuration of the aerial robot, by integrating different state-of-the art SLAM methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF). To do this, a minimum onboard sensory configuration is supposed, consisting of a monocular camera, an Inertial Measurement Unit (IMU) and an altimeter. It allows to improve the results of well-known monocular visual SLAM methods (LSD-SLAM and ORB-SLAM are tested and compared in this work) by solving scale ambiguity and providing additional information to the EKF. When payload and computational capabilities permit, a 2D laser sensor can be easily incorporated to the SLAM system, obtaining a local 2.5D map and a footprint estimation of the robot position that improves the 6D pose estimation through the EKF. We present some experimental results with two different commercial platforms, and validate the system by applying it to their position control. PMID:28397758

Introduction and Testing of a Monitoring and Colony-Mapping Method for Waterbird Populations That Uses High-Speed and Ultra-Detailed Aerial Remote Sensing

PubMed Central

Bakó, Gábor; Tolnai, Márton; Takács, Ádám

2014-01-01

Remote sensing is a method that collects data of the Earth's surface without causing disturbances. Thus, it is worthwhile to use remote sensing methods to survey endangered ecosystems, as the studied species will behave naturally while undisturbed. The latest passive optical remote sensing solutions permit surveys from long distances. State-of-the-art highly sensitive sensor systems allow high spatial resolution image acquisition at high altitudes and at high flying speeds, even in low-visibility conditions. As the aerial imagery captured by an airplane covers the entire study area, all the animals present in that area can be recorded. A population assessment is conducted by visual interpretations of an ortho image map. The basic objective of this study is to determine whether small- and medium-sized bird species are recognizable in the ortho images by using high spatial resolution aerial cameras. The spatial resolution needed for identifying the bird species in the ortho image map was studied. The survey was adjusted to determine the number of birds in a colony at a given time. PMID:25046012

Small Moving Vehicle Detection in a Satellite Video of an Urban Area

PubMed Central

Yang, Tao; Wang, Xiwen; Yao, Bowei; Li, Jing; Zhang, Yanning; He, Zhannan; Duan, Wencheng

2016-01-01

Vehicle surveillance of a wide area allows us to learn much about the daily activities and traffic information. With the rapid development of remote sensing, satellite video has become an important data source for vehicle detection, which provides a broader field of surveillance. The achieved work generally focuses on aerial video with moderately-sized objects based on feature extraction. However, the moving vehicles in satellite video imagery range from just a few pixels to dozens of pixels and exhibit low contrast with respect to the background, which makes it hard to get available appearance or shape information. In this paper, we look into the problem of moving vehicle detection in satellite imagery. To the best of our knowledge, it is the first time to deal with moving vehicle detection from satellite videos. Our approach consists of two stages: first, through foreground motion segmentation and trajectory accumulation, the scene motion heat map is dynamically built. Following this, a novel saliency based background model which intensifies moving objects is presented to segment the vehicles in the hot regions. Qualitative and quantitative experiments on sequence from a recent Skybox satellite video dataset demonstrates that our approach achieves a high detection rate and low false alarm simultaneously. PMID:27657091

Method of radiometric quality assessment of NIR images acquired with a custom sensor mounted on an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Wierzbicki, Damian; Fryskowska, Anna; Kedzierski, Michal; Wojtkowska, Michalina; Delis, Paulina

2018-01-01

Unmanned aerial vehicles are suited to various photogrammetry and remote sensing missions. Such platforms are equipped with various optoelectronic sensors imaging in the visible and infrared spectral ranges and also thermal sensors. Nowadays, near-infrared (NIR) images acquired from low altitudes are often used for producing orthophoto maps for precision agriculture among other things. One major problem results from the application of low-cost custom and compact NIR cameras with wide-angle lenses introducing vignetting. In numerous cases, such cameras acquire low radiometric quality images depending on the lighting conditions. The paper presents a method of radiometric quality assessment of low-altitude NIR imagery data from a custom sensor. The method utilizes statistical analysis of NIR images. The data used for the analyses were acquired from various altitudes in various weather and lighting conditions. An objective NIR imagery quality index was determined as a result of the research. The results obtained using this index enabled the classification of images into three categories: good, medium, and low radiometric quality. The classification makes it possible to determine the a priori error of the acquired images and assess whether a rerun of the photogrammetric flight is necessary.

A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

PubMed Central

Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

2015-01-01

It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. PMID:26076404

Operational Use of Remote Sensing within USDA

NASA Technical Reports Server (NTRS)

Bethel, Glenn R.

2007-01-01

A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.

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

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

PubMed

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

Remote sensing for vineyard management

NASA Technical Reports Server (NTRS)

Philipson, W. R.; Erb, T. L.; Fernandez, D.; Mcleester, J. N.

1980-01-01

Cornell's Remote Sensing Program has been involved in a continuing investigation to assess the value of remote sensing for vineyard management. Program staff members have conducted a series of site and crop analysis studies. These include: (1) panchromatic aerial photography for planning artificial drainage in a new vineyard; (2) color infrared aerial photography for assessing crop vigor/health; and (3) color infrared aerial photography and aircraft multispectral scanner data for evaluating yield related factors. These studies and their findings are reviewed.

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.

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

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

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

Usability of aerial video footage for 3-D scene reconstruction and structural damage assessment

NASA Astrophysics Data System (ADS)

Cusicanqui, Johnny; Kerle, Norman; Nex, Francesco

2018-06-01

Remote sensing has evolved into the most efficient approach to assess post-disaster structural damage, in extensively affected areas through the use of spaceborne data. For smaller, and in particular, complex urban disaster scenes, multi-perspective aerial imagery obtained with unmanned aerial vehicles and derived dense color 3-D models are increasingly being used. These type of data allow the direct and automated recognition of damage-related features, supporting an effective post-disaster structural damage assessment. However, the rapid collection and sharing of multi-perspective aerial imagery is still limited due to tight or lacking regulations and legal frameworks. A potential alternative is aerial video footage, which is typically acquired and shared by civil protection institutions or news media and which tends to be the first type of airborne data available. Nevertheless, inherent artifacts and the lack of suitable processing means have long limited its potential use in structural damage assessment and other post-disaster activities. In this research the usability of modern aerial video data was evaluated based on a comparative quality and application analysis of video data and multi-perspective imagery (photos), and their derivative 3-D point clouds created using current photogrammetric techniques. Additionally, the effects of external factors, such as topography and the presence of smoke and moving objects, were determined by analyzing two different earthquake-affected sites: Tainan (Taiwan) and Pescara del Tronto (Italy). Results demonstrated similar usabilities for video and photos. This is shown by the short 2 cm of difference between the accuracies of video- and photo-based 3-D point clouds. Despite the low video resolution, the usability of these data was compensated for by a small ground sampling distance. Instead of video characteristics, low quality and application resulted from non-data-related factors, such as changes in the scene, lack of

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.

Control of a Quadcopter Aerial Robot Using Optic Flow Sensing

NASA Astrophysics Data System (ADS)

Hurd, Michael Brandon

This thesis focuses on the motion control of a custom-built quadcopter aerial robot using optic flow sensing. Optic flow sensing is a vision-based approach that can provide a robot the ability to fly in global positioning system (GPS) denied environments, such as indoor environments. In this work, optic flow sensors are used to stabilize the motion of quadcopter robot, where an optic flow algorithm is applied to provide odometry measurements to the quadcopter's central processing unit to monitor the flight heading. The optic-flow sensor and algorithm are capable of gathering and processing the images at 250 frames/sec, and the sensor package weighs 2.5 g and has a footprint of 6 cm2 in area. The odometry value from the optic flow sensor is then used a feedback information in a simple proportional-integral-derivative (PID) controller on the quadcopter. Experimental results are presented to demonstrate the effectiveness of using optic flow for controlling the motion of the quadcopter aerial robot. The technique presented herein can be applied to different types of aerial robotic systems or unmanned aerial vehicles (UAVs), as well as unmanned ground vehicles (UGV).

A Biomimetic Algorithm for Flight Stabilization in Airborne Vehicles, Based on Dragonfly Ocellar Vision

DTIC Science & Technology

2006-07-27

9 10 Technical horizon sensors Over the past few years, a remarkable proliferation of designs for micro-aerial vehicles (MAVs) has occurred... photodiode Fig. 15 Fig. 14 Sky scans with a GaP UV pho to dio de a lo ng three vert ical paths. A ngle o f v iew 30 degrees, 50% clo ud co ver, sun at...Australia Email: gert.stange@anu.edu.au A biomimetic algorithm for flight stabilization in airborne vehicles , based on dragonfly ocellar vision

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

Model-Based Building Detection from Low-Cost Optical Sensors Onboard Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Karantzalos, K.; Koutsourakis, P.; Kalisperakis, I.; Grammatikopoulos, L.

2015-08-01

The automated and cost-effective building detection in ultra high spatial resolution is of major importance for various engineering and smart city applications. To this end, in this paper, a model-based building detection technique has been developed able to extract and reconstruct buildings from UAV aerial imagery and low-cost imaging sensors. In particular, the developed approach through advanced structure from motion, bundle adjustment and dense image matching computes a DSM and a true orthomosaic from the numerous GoPro images which are characterised by important geometric distortions and fish-eye effect. An unsupervised multi-region, graphcut segmentation and a rule-based classification is responsible for delivering the initial multi-class classification map. The DTM is then calculated based on inpaininting and mathematical morphology process. A data fusion process between the detected building from the DSM/DTM and the classification map feeds a grammar-based building reconstruction and scene building are extracted and reconstructed. Preliminary experimental results appear quite promising with the quantitative evaluation indicating detection rates at object level of 88% regarding the correctness and above 75% regarding the detection completeness.

Field Experiments using Telepresence and Virtual Reality to Control Remote Vehicles: Application to Mars Rover Missions

NASA Technical Reports Server (NTRS)

Stoker, Carol

1994-01-01

This paper will describe a series of field experiments to develop and demonstrate file use of Telepresence and Virtual Reality systems for controlling rover vehicles on planetary surfaces. In 1993, NASA Ames deployed a Telepresence-Controlled Remotely Operated underwater Vehicle (TROV) into an ice-covered sea environment in Antarctica. The goal of the mission was to perform scientific exploration of an unknown environment using a remote vehicle with telepresence and virtual reality as a user interface. The vehicle was operated both locally, from above a dive hole in the ice through which it was launched, and remotely over a satellite communications link from a control room at NASA's Ames Research center, for over two months. Remote control used a bidirectional Internet link to the vehicle control computer. The operator viewed live stereo video from the TROV along with a computer-gene rated graphic representation of the underwater terrain showing file vehicle state and other related information. Tile actual vehicle could be driven either from within the virtual environment or through a telepresence interface. In March 1994, a second field experiment was performed in which [lie remote control system developed for the Antarctic TROV mission was used to control the Russian Marsokhod Rover, an advanced planetary surface rover intended for launch in 1998. Marsokhod consists of a 6-wheel chassis and is capable of traversing several kilometers of terrain each day, The rover can be controlled remotely, but is also capable of performing autonomous traverses. The rover was outfitted with a manipulator arm capable of deploying a small instrument, collecting soil samples, etc. The Marsokhod rover was deployed at Amboy Crater in the Mojave desert, a Mars analog site, and controlled remotely from Los Angeles. in two operating modes: (1) a Mars rover mission simulation with long time delay and (2) a Lunar rover mission simulation with live action video. A team of planetary

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.

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.

Vehicle detection and orientation estimation using the radon transform

NASA Astrophysics Data System (ADS)

Pelapur, Rengarajan; Bunyak, Filiz; Palaniappan, Kannappan; Seetharaman, Gunasekaran

2013-05-01

Determining the location and orientation of vehicles in satellite and airborne imagery is a challenging task given the density of cars and other vehicles and complexity of the environment in urban scenes almost anywhere in the world. We have developed a robust and accurate method for detecting vehicles using a template-based directional chamfer matching, combined with vehicle orientation estimation based on a refined segmentation, followed by a Radon transform based profile variance peak analysis approach. The same algorithm was applied to both high resolution satellite imagery and wide area aerial imagery and initial results show robustness to illumination changes and geometric appearance distortions. Nearly 80% of the orientation angle estimates for 1585 vehicles across both satellite and aerial imagery were accurate to within 15? of the ground truth. In the case of satellite imagery alone, nearly 90% of the objects have an estimated error within +/-1.0° of the ground truth.

Approaching morphing wing concepts on the basis of micro aerial vehicles

NASA Astrophysics Data System (ADS)

Boller, C.; Kuo, C.-M.; Qin, N.

2007-04-01

Morphing wings have been discussed since the early days of smart structures. Concepts and demonstrations started mainly in the context of real existing fixed wing aircraft. The complexity of existing aircraft and the limitations in terms of energy required and thus resulting cost made morphing wings mainly impossible to be successfully integrated into existing aircraft designs. Going however to smaller scaled aircraft where designs are less or possibly even not defined at all makes demonstration of morphing wings much more feasible. This paper will therefore discuss some morphing wing issues for micro aerial vehicle (MAV) designs where an MAV is considered to be an air vehicle of around 30 to 50 cm in span and a weight of less than 250 grams. At first the aerodynamics in terms of different wing shapes for such a small type of aircraft will be discussed followed by a design procedure on how to successfully design and analyse a morphing wing MAV. A more detailed description will then be given with regard to adaptively changing a wing's thickness where the actuation principles applied will be outlined in terms of conventional mechanical as well as smart structural solutions. Experimental results achieved in real flight tests will be described and discussed.

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.

Estimating plant distance in maize using Unmanned Aerial Vehicle (UAV).

PubMed

Zhang, Jinshui; Basso, Bruno; Price, Richard F; Putman, Gregory; Shuai, Guanyuan

2018-01-01

Distance between rows and plants are essential parameters that affect the final grain yield in row crops. This paper presents the results of research intended to develop a novel method to quantify the distance between maize plants at field scale using an Unmanned Aerial Vehicle (UAV). Using this method, we can recognize maize plants as objects and calculate the distance between plants. We initially developed our method by training an algorithm in an indoor facility with plastic corn plants. Then, the method was scaled up and tested in a farmer's field with maize plant spacing that exhibited natural variation. The results of this study demonstrate that it is possible to precisely quantify the distance between maize plants. We found that accuracy of the measurement of the distance between maize plants depended on the height above ground level at which UAV imagery was taken. This study provides an innovative approach to quantify plant-to-plant variability and, thereby final crop yield estimates.

Individual tree detection from Unmanned Aerial Vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest

Treesearch

Midhun Mohan; Carlos Alberto Silva; Carine Klauberg; Prahlad Jat; Glenn Catts; Adrian Cardil; Andrew Thomas Hudak; Mahendra Dia

2017-01-01

Advances in Unmanned Aerial Vehicle (UAV) technology and data processing capabilities have made it feasible to obtain high-resolution imagery and three dimensional (3D) data which can be used for forest monitoring and assessing tree attributes. This study evaluates the applicability of low consumer grade cameras attached to UAVs and structure-from-motion (SfM)...

Volumetric calculation using low cost unmanned aerial vehicle (UAV) approach

NASA Astrophysics Data System (ADS)

Rahman, A. A. Ab; Maulud, K. N. Abdul; Mohd, F. A.; Jaafar, O.; Tahar, K. N.

2017-12-01

Unmanned Aerial Vehicles (UAV) technology has evolved dramatically in the 21st century. It is used by both military and general public for recreational purposes and mapping work. Operating cost for UAV is much cheaper compared to that of normal aircraft and it does not require a large work space. The UAV systems have similar functions with the LIDAR and satellite images technologies. These systems require a huge cost, labour and time consumption to produce elevation and dimension data. Measurement of difficult objects such as water tank can also be done by using UAV. The purpose of this paper is to show the capability of UAV to compute the volume of water tank based on a different number of images and control points. The results were compared with the actual volume of the tank to validate the measurement. In this study, the image acquisition was done using Phantom 3 Professional, which is a low cost UAV. The analysis in this study is based on different volume computations using two and four control points with variety set of UAV images. The results show that more images will provide a better quality measurement. With 95 images and four GCP, the error percentage to the actual volume is about 5%. Four controls are enough to get good results but more images are needed, estimated about 115 until 220 images. All in all, it can be concluded that the low cost UAV has a potential to be used for volume of water and dimension measurement.

Whitecap coverage from aerial photography

NASA Technical Reports Server (NTRS)

Austin, R. W.

1970-01-01

A program for determining the feasibility of deriving sea surface wind speeds by remotely sensing ocean surface radiances in the nonglitter regions is discussed. With a knowledge of the duration and geographical extent of the wind field, information about the conventional sea state may be derived. The use of optical techniques for determining sea state has obvious limitations. For example, such means can be used only in daylight and only when a clear path of sight is available between the sensor and the surface. However, sensors and vehicles capable of providing the data needed for such techniques are planned for the near future; therefore, a secondary or backup capability can be provided with little added effort. The information currently being sought regarding white water coverage is also of direct interest to those working with passive microwave systems, the study of energy transfer between winds and ocean currents, the aerial estimation of wind speeds, and many others.

Human machine interface to manually drive rhombic like vehicles in remote handling operations

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

Lopes, Pedro; Vale, Alberto; Ventura, Rodrigo

2015-07-01

In the thermonuclear experimental reactor ITER, a vehicle named CTS is designed to transport a container with activated components inside the buildings. In nominal operations, the CTS is autonomously guided under supervision. However, in some unexpected situations, such as in rescue and recovery operations, the autonomous mode must be overridden and the CTS must be remotely guided by an operator. The CTS is a rhombic-like vehicle, with two drivable and steerable wheels along its longitudinal axis, providing omni-directional capabilities. The rhombic kinematics correspond to four control variables, which are difficult to manage in manual mode operation. This paper proposes amore » Human Machine Interface (HMI) to remotely guide the vehicle in manual mode. The proposed solution is implemented using a HMI with an encoder connected to a micro-controller and an analog 2-axis joystick. Experimental results were obtained comparing the proposed solution with other controller devices in different scenarios and using a software platform that simulates the kinematics and dynamics of the vehicle. (authors)« less

Design and testing of shape memory alloy actuation mechanism for flapping wing micro unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kamaruzaman, N. F.; Abdullah, E. J.

2017-12-01

Shape memory alloy (SMA) actuator offers great solution for aerospace applications with low weight being its most attractive feature. A SMA actuation mechanism for the flapping micro unmanned aerial vehicle (MAV) is proposed in this study, where SMA material is the primary system that provides the flapping motion to the wings. Based on several established design criteria, a design prototype has been fabricated to validate the design. As a proof of concept, an experiment is performed using an electrical circuit to power the SMA actuator to evaluate the flapping angle. During testing, several problems have been observed and their solutions for future development are proposed. Based on the experiment, the average recorded flapping wing angle is 14.33° for upward deflection and 12.12° for downward deflection. This meets the required design criteria and objective set forth for this design. The results prove the feasibility of employing SMA actuators in flapping wing MAV.

Remote Video Monitor of Vehicles in Cooperative Information Platform

NASA Astrophysics Data System (ADS)

Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

Unmanned aerial vehicles (UAVs) in pest management: Progress in the development of a UAV-deployed mating disruption system for Wisconsin cranberries

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) represent a powerful new tool for agriculture. Currently, UAVs are used almost exclusively as crop reconnaissance devices (“eyes in the sky”), not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Lu...

Unmanned aerial vehicles (UAVs) in pest management: Progress in the development of a UAV-deployed mating disruption system for Wisconsin cranberries

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) hold significant promise for agriculture. Currently, UAVs are being employed for various reconnaissance purposes (“eyes in the sky”), but not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Luck La...

Comparative aerial- and ground-based high-throughput phenotyping for the genetic dissection of NDVI as a proxy for drought-adaptive traits in durum wheat

USDA-ARS?s Scientific Manuscript database

High-throughput phenotyping platforms (HTPPs) provide novel opportunities to more effectively dissect the genetic basis of drought-adaptive traits. This genome-wide association study (GWAS) compares the results obtained with two Unmanned Aerial Vehicles (UAVs) and a ground-based platform used to mea...

Mechanical Harvesting Effectively Controls Young Typha spp. Invasion and Unmanned Aerial Vehicle Data Enhances Post-treatment Monitoring

PubMed Central

Lishawa, Shane C.; Carson, Brendan D.; Brandt, Jodi S.; Tallant, Jason M.; Reo, Nicholas J.; Albert, Dennis A.; Monks, Andrew M.; Lautenbach, Joseph M.; Clark, Eric

2017-01-01

The ecological impacts of invasive plants increase dramatically with time since invasion. Targeting young populations for treatment is therefore an economically and ecologically effective management approach, especially when linked to post-treatment monitoring to evaluate the efficacy of management. However, collecting detailed field-based post-treatment data is prohibitively expensive, typically resulting in inadequate documentation of the ecological effects of invasive plant management. Alternative approaches, such as remote detection with unmanned aerial vehicles (UAV), provide an opportunity to advance the science and practice of restoration ecology. In this study, we sought to determine the plant community response to different mechanical removal treatments to a dominant invasive wetland macrophyte (Typha spp.) along an age-gradient within a Great Lakes coastal wetland. We assessed the post-treatment responses with both intensive field vegetation and UAV data. Prior to treatment, the oldest Typha stands had the lowest plant diversity, lowest native sedge (Carex spp.) cover, and the greatest Typha cover. Following treatment, plots that were mechanically harvested below the surface of the water differed from unharvested control and above-water harvested plots for several plant community measures, including lower Typha dominance, lower native plant cover, and greater floating and submerged aquatic species cover. Repeated-measures analysis revealed that above-water cutting increased plant diversity and aquatic species cover across all ages, and maintained native Carex spp. cover in the youngest portions of Typha stands. UAV data revealed significant post-treatment differences in normalized difference vegetation index (NDVI) scores, blue band reflectance, and vegetation height, and these remotely collected measures corresponded to field observations. Our findings suggest that both mechanically harvesting the above-water biomass of young Typha stands and harvesting

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.

A study of atmospheric mixing of trace gases by aerial sampling with a multi-rotor drone

NASA Astrophysics Data System (ADS)

Chang, Chih-Chung; Chang, Chih-Yuan; Wang, Jia-Lin; Lin, Ming-Ren; Ou-Yang, Chang-Feng; Pan, Hsiang-Hsu; Chen, Yen-Chen

2018-07-01

We exploited a novel sampling vehicle, a multi-rotor drone carrying a remote-controlled whole air sampling device, to collect aerial samples with high sample integrity and preservation conditions. An array of 106 volatile organic compounds (VOCs), CO, CH4, and CO2 were analyzed and compared between the aerial samples (300-m height) and the ground-level samples in pairs to inspect for vertical mixing of the trace gases at a coastal site under three different meteorological conditions of local circulation, frontal passage, and high-pressure peripheral circulation. A rather homogeneous composition was observed for the sample pairs immediately after the frontal passage, indicating a well-mixed condition below 300 m. In contrast, inhomogeneous mixing was observed for the sample pairs under the other two conditions (local circulation and high-pressure peripheral circulation), suggesting different layers of air masses. Furthermore, information of unique source markers, composition profiles, and lifetimes of compounds were used to differentiate the origins of the air masses aloft and at the surface to substantiate the observed inhomogeneity. The study demonstrates that, with the availability of the near-surface aerial sampling coupling with in-laboratory analysis, detailed compositions of trace gases can now be readily obtained with superior data quality. Based on the distinctive chemical compositions, the sources, transport, and atmospheric mixing of the airborne pollutants in the near-surface atmosphere can be better studied and understood.

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.

Application of the Hardman methodology to the Army Remotely Piloted Vehicle (RPV)

NASA Technical Reports Server (NTRS)

1983-01-01

The application of the HARDMAN Methodology to the Remotely Piloted Vehicle (RPV) is described. The methodology was used to analyze the manpower, personnel, and training (MPT) requirements of the proposed RPV system design for a number of operating scenarios. The RPV system is defined as consisting of the equipment, personnel, and operational procedures needed to perform five basic artillery missions: reconnaissance, target acquisition, artillery adjustment, target designation and damage assessment. The RPV design evaluated includes an air vehicle (AV), a modular integrated communications and navigation system (MICNS), a ground control station (GCS), a launch subsystem (LS), a recovery subsystem (RS), and a number of ground support requirements. The HARDMAN Methodology is an integrated set of data base management techniques and analytic tools, designed to provide timely and fully documented assessments of the human resource requirements associated with an emerging system's design.

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

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.

Hyperparameter Classification of Arctic Sea Ice and Snow Based on Aerial Laser Data, Passive Microwave Data and Field Data

NASA Astrophysics Data System (ADS)

Herzfeld, U. C.; Maslanik, J.; Williams, S.; Sturm, M.; Cavalieri, D.

2006-12-01

In the past year, the Arctic sea-ice cover has been shrinking at an alarming rate. Remote-sensing technologies provide opportunities for observations of the sea ice at unprecedented repetition rates and spatial resolutions. The advance of new observational technologies is not only fascinating, it also brings with it the challenge and necessity to derive adequate new geoinformatical and geomathematical methods as a basis for analysis and geophysical interpretation of new data types. Our research includes validation and analysis of NASA EOS data, development of observational instrumentation and advanced geoinformatics. In this talk we emphasize the close linkage between technological development and geoinformatics along case studies of sea-ice near Point Barrow, Alaska, based on the following data types: AMSR-E and PSR passive microwave data, RADARSAT and ERS SAR data, manually-collected snow-depth data and laser-elevation data from unmanned aerial vehicles. The hyperparameter concept is introduced to facilitate characterization and classification of the same sea-ice properties and spatial structures from these data sets, which differ with respect to spatial resolution, measured parameters and observed geophysical variables. Mathematically, this requires parameter identification in undersampled, oversampled or overprinted situations.

Floating aerial LED signage based on aerial imaging by retro-reflection (AIRR).

PubMed

Yamamoto, Hirotsugu; Tomiyama, Yuka; Suyama, Shiro

2014-11-03

We propose a floating aerial LED signage technique by utilizing retro-reflection. The proposed display is composed of LEDs, a half mirror, and retro-reflective sheeting. Directivity of the aerial image formation and size of the aerial image have been investigated. Furthermore, a floating aerial LED sign has been successfully formed in free space.

Application of Copper Indium Gallium Diselenide Photovoltaic Cells to Extend the Endurance and Capabilities of Unmanned Aerial Vehicles

DTIC Science & Technology

2009-09-01

Group V element to make them n or p material. Another common group of semiconductors are called III–V compounds , such as gallium arsenide (GaAs), or...these compounds used for photovoltaics are Cadmium Telluride (CdTe), and Copper Indium Gallium DiSelenide, commonly referred to as CIGS [49]. Figure...INDIUM GALLIUM DISELENIDE PHOTOVOLTAIC CELLS TO EXTEND THE ENDURANCE AND CAPABILITIES OF UNMANNED AERIAL VEHICLES by William R. Hurd

High-Resolution Monitoring of Himalayan Glacier Dynamics Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Immerzeel, W.; Kraaijenbrink, P. D. A.; Shea, J.; Shrestha, A. B.; Pellicciotti, F.; Bierkens, M. F.; de Jong, S. M.

2014-12-01

Himalayan glacier tongues are commonly debris covered and play an important role in modulating the glacier response to climate . However, they remain relatively unstudied because of the inaccessibility of the terrain and the difficulties in field work caused by the thick debris mantles. Observations of debris-covered glaciers are therefore limited to point locations and airborne remote sensing may bridge the gap between scarce, point field observations and coarse resolution space-borne remote sensing. In this study we deploy an Unmanned Airborne Vehicle (UAV) on two debris covered glaciers in the Nepalese Himalayas: the Lirung and Langtang glacier during four field campaigns in 2013 and 2014. Based on stereo-imaging and the structure for motion algorithm we derive highly detailed ortho-mosaics and digital elevation models (DEMs), which we geometrically correct using differential GPS observations collected in the field. Based on DEM differencing and manual feature tracking we derive the mass loss and the surface velocity of the glacier at a high spatial resolution and accuracy. We also assess spatiotemporal changes in supra-glacial lakes and ice cliffs based on the imagery. On average, mass loss is limited and the surface velocity is very small. However, the spatial variability of melt rates is very high, and ice cliffs and supra-glacial ponds show mass losses that can be an order of magnitude higher than the average. We suggest that future research should focus on the interaction between supra-glacial ponds, ice cliffs and englacial hydrology to further understand the dynamics of debris-covered glaciers. Finally, we conclude that UAV deployment has large potential in glaciology and it represents a substantial advancement over methods currently applied in studying glacier surface features.

Identifying Contingency Requirements using Obstacle Analysis on an Unpiloted Aerial Vehicle

NASA Technical Reports Server (NTRS)

Lutz, Robyn R.; Nelson, Stacy; Patterson-Hine, Ann; Frost, Chad R.; Tal, Doron

2005-01-01

This paper describes experience using Obstacle Analysis to identify contingency requirements on an unpiloted aerial vehicle. A contingency is an operational anomaly, and may or may not involve component failure. The challenges to this effort were: ( I ) rapid evolution of the system while operational, (2) incremental autonomy as capabilities were transferred from ground control to software control and (3) the eventual safety-criticality of such systems as they begin to fly over populated areas. The results reported here are preliminary but show that Obstacle Analysis helped (1) identify new contingencies that appeared as autonomy increased; (2) identify new alternatives for handling both previously known and new contingencies; and (3) investigate the continued validity of existing software requirements for contingency handling. Since many mobile, intelligent systems are built using a development process that poses the same challenges, the results appear to have applicability to other similar systems.

Multi-terminal remote monitoring and warning system using Micro Air Vehicle for dangerous environment

NASA Astrophysics Data System (ADS)

Yu, Yanan; Wang, Xiaoxun; He, Chengcheng; Lai, Chenlong; Liu, Yuanchao

2015-11-01

For overcoming the problems such as remote operation and dangerous tasks, multi-terminal remote monitoring and warning system based on STC89C52 Micro Control Unit and wireless communication technique was proposed. The system with MCU as its core adopted multiple sets of sensor device to monitor environment parameters of different locations, such as temperature, humidity, smoke other harmful gas concentration. Data information collected was transmitted remotely by wireless transceiver module, and then multi-channel data parameter was processed and displayed through serial communication protocol between the module and PC. The results of system could be checked in the form of web pages within a local network which plays a wireless monitoring and warning role. In a remote operation, four-rotor micro air vehicle which fixed airborne data acquisition device was utilized as a middleware between collecting terminal and PC to increase monitoring scope. Whole test system has characteristics of simple construction, convenience, real time ability and high reliability, which could meet the requirements of actual use.

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs

PubMed Central

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E.; Hernandez, Carmen; Dalmau, Oscar

2017-01-01

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. PMID:28621740

77 FR 36250 - Information Collection Request; Request for Aerial Photography

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-18

... the responsibility for conducting and coordinating the FSA's aerial photography, remote sensing... FSA Aerial Photography Field Office (APFO) uses the information from this form to collect the customer... respond, including through the use of appropriate automated, electronic, mechanical, or other...

The Development and Flight Testing of an Aerially Deployed Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Smith, Andrew

An investigation into the feasibility of aerial deployed unmanned aerial vehicles was completed. The investigation included the development and flight testing of multiple unmanned aerial systems to investigate the different components of potential aerial deployment missions. The project consisted of two main objectives; the first objective dealt with the development of an airframe capable of surviving aerial deployment from a rocket and then self assembling from its stowed configuration into its flight configuration. The second objective focused on the development of an autopilot capable of performing basic guidance, navigation, and control following aerial deployment. To accomplish these two objectives multiple airframes were developed to verify their completion experimentally. The first portion of the project, investigating the feasibility of surviving an aerial deployment, was completed using a fixed wing glider that following a successful deployment had 52 seconds of controlled flight. Before developing the autopilot in the second phase of the project, the glider was significantly upgraded to fix faults discovered in the glider flight testing and to enhance the system capabilities. Unfortunately to conform to outdoor flight restrictions imposed by the university and the Federal Aviation Administration it was required to switch airframes before flight testing of the new fixed wing platform could begin. As a result, an autopilot was developed for a quadrotor and verified experimentally completely indoors to remain within the limits of governing policies.

Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

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.

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.

APPLIED REMOTE SENSING

EPA Science Inventory

Remote Sensing is a scientific discipline of non-contact monitoring. It includes a range of technologies that span from aerial photography to advanced spectral imaging and analytical methods. This Session is designed to demonstrate contemporary practical applications of remote se...

Infrared vehicle recognition using unsupervised feature learning based on K-feature

NASA Astrophysics Data System (ADS)

Lin, Jin; Tan, Yihua; Xia, Haijiao; Tian, Jinwen

2018-02-01

Subject to the complex battlefield environment, it is difficult to establish a complete knowledge base in practical application of vehicle recognition algorithms. The infrared vehicle recognition is always difficult and challenging, which plays an important role in remote sensing. In this paper we propose a new unsupervised feature learning method based on K-feature to recognize vehicle in infrared images. First, we use the target detection algorithm which is based on the saliency to detect the initial image. Then, the unsupervised feature learning based on K-feature, which is generated by Kmeans clustering algorithm that extracted features by learning a visual dictionary from a large number of samples without label, is calculated to suppress the false alarm and improve the accuracy. Finally, the vehicle target recognition image is finished by some post-processing. Large numbers of experiments demonstrate that the proposed method has satisfy recognition effectiveness and robustness for vehicle recognition in infrared images under complex backgrounds, and it also improve the reliability of it.

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.

First Experiences Using Small Unmanned Aerial Vehicles for Volcano Observation in the Visible Range

NASA Astrophysics Data System (ADS)

Buschmann, M.; Krüger, L.; Bange, J.

2007-05-01

Many of the most active volcanoes in the world are located in Middle and South America. While permanently installed sensors for seismicity give reliable supervision of volcanic activities, they lack the possibility to determine occurrence and extent of surface activities. Both from the point of science and civil protection, visible documentation of activities is of great interest. While satellites and manned aircraft already offer many possibilities, they also have disadvantages like delayed or poor image data availability or high costs. The Institute of Aerospace Systems of the Technical University of Braunschweig, in collaboration with the spin-off company Mavionics, developed a family of extremely small and lightweight Unmanned Aerial Vehicles (UAV), with the smallest aircraft weighting only 550~g (19~ounces) at a wing span of 50 cm (20~inch). These aircraft are operating completely automatically, controlled by a highly miniaturized autopilot system. Flight mission is defined by a list of GPS waypoints using a conventional notebook. While in radio range, current position and status of the aircraft is displayed on the notebook and waypoints can easily be changed by the user. However, when radio connection is not available, the aircraft operates on its on, completing the flight mission automatically. This greatly increases the operating range of the system. Especially for the purpose of volcano observation in South America, the aircraft Carolo~P330 was developed, weighting 5~kg (11~pounds) at a wing span of 3.3~m ( 11~ft). The whole system can be easily carried by car and the electric propulsion system avoids handling of flammable liquids. The batteries can be recharged in the field. Carolo~P330 has an endurance of up to 90~minutes at a flight speed of 25~m/s, giving it a maximum range of 67 km (41~miles). It was especially designed to operate under harsh conditions. The payload is a digital still camera, which delivers aerial images with a resolution of up to 8

Remotely Operated Vehicles (ROVs) Provide a "Big Data Progression"

NASA Astrophysics Data System (ADS)

Oostra, D.; Sanghera, S. S.; Mangosing, D. C., Jr.; Lewis, P. M., Jr.; Chambers, L. H.

2015-12-01

This year, science and technology teams at the NASA Langley Science Directorate were challenged with creating an API-based web application using RockBlock Mobile sensors mounted on a zero pressure high-altitude balloon. The system tracks and collects meteorological data parameters and visualizes this data in near real time, using a MEAN development stack to create an HTML5 based tool that can send commands to the vehicle, parse incoming data, and perform other functions to store and serve data to other devices. NASA developers and science educators working on this project saw an opportunity to use this emerging technology to address a gap identified in science education between middle and high school curricula. As students learn about data analysis in elementary and middle school, they are taught to collect data from in situ sources. In high school, students are then asked to work with remotely sensed data, without always having the experience or understanding of how that data is collected. We believe that using ROVs to create a "big data progression" for students will not only enhance their ability to understand how remote satellite data is collected, but will also provide the outlet for younger students to expand their interest in science and data prior to entering high school. In this presentation, we will share and discuss our experiences with ROVs, APIs and data viz applications, with a focus on the next steps for developing this emerging capability.

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.

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

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

Low altitude unmanned aerial vehicle for characterising remediation effectiveness following the FDNPP accident.

PubMed

Martin, P G; Payton, O D; Fardoulis, J S; Richards, D A; Yamashiki, Y; Scott, T B

2016-01-01

On the 12th of March 2011, The Great Tōhoku Earthquake occurred 70 km off the eastern coast of Japan, generating a large 14 m high tsunami. The ensuing catalogue of events over the succeeding 12 d resulted in the release of considerable quantities of radioactive material into the environment. Important to the large-scale remediation of the affected areas is the accurate and high spatial resolution characterisation of contamination, including the verification of decontaminated areas. To enable this, a low altitude unmanned aerial vehicle equipped with a lightweight gamma-spectrometer and height normalisation system was used to produce sub-meter resolution maps of contamination. This system provided a valuable method to examine both contaminated and remediated areas rapidly, whilst greatly reducing the dose received by the operator, typically in localities formerly inaccessible to ground-based survey methods. The characterisation of three sites within Fukushima Prefecture is presented; one remediated (and a site of much previous attention), one un-remediated and a third having been subjected to an alternative method to reduce emitted radiation dose. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Mapping snow depth in alpine terrain with remotely piloted aerial systems and structure-from-motion photogrammetry - first results from a pilot study

NASA Astrophysics Data System (ADS)

Adams, Marc; Fromm, Reinhard; Bühler, Yves; Bösch, Ruedi; Ginzler, Christian

2016-04-01

Detailed information on the spatio-temporal distribution of seasonal snow in the alpine terrain plays a major role for the hydrological cycle, natural hazard management, flora and fauna, as well as tourism. Current methods are mostly only valid on a regional scale or require a trade-off between the data's availability, cost and resolution. During a one-year pilot study, we investigated the potential of remotely piloted aerial systems (RPAS) and structure-from-motion photogrammetry for snow depth mapping. We employed multi-copter and fixed-wing RPAS, equipped with different low-cost, off-the shelf sensors, at four test sites in Austria and Switzerland. Over 30 flights were performed during the winter 2014/15, where different camera settings, filters and lenses, as well as data collection routines were tested. Orthophotos and digital surface models (DSM) where calculated from the imagery using structure-from-motion photogrammetry software. Snow height was derived by subtracting snow-free from snow-covered DSMs. The RPAS-results were validated against data collected using a variety of well-established remote sensing (i.e. terrestrial laser scanning, large frame aerial sensors) and in-situ measurement techniques. The results show, that RPAS i) are able to map snow depth within accuracies of 0.07-0.15 m root mean square error (RMSE), when compared to traditional in-situ data; ii) can be operated at lower cost, easier repeatability, less operational constraints and higher GSD than large frame aerial sensors on-board manned aircraft, while achieving significantly higher accuracies; iii) are able to acquire meaningful data even under harsh environmental conditions above 2000 m a.s.l. (turbulence, low temperature and high irradiance, low air density). While providing a first prove-of-concept, the study also showed future challenges and limitations of RPAS-based snow depth mapping, including a high dependency on correct co-registration of snow-free and snow-covered height

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.