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Articles 1 - 14 of 14
Full-Text Articles in Engineering
Incorporation Of Unmanned Aerial Vehicle (Uav) Point Cloud Products Into Remote Sensing Evapotranspiration Models, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, William P. Kustas, Héctor Nieto, Maria Mar Alsina, Alex White, John H. Prueger, Lynn Mckee, Joseph Alfieri, Lawrence E. Hipps, Calvin Coopmans, Nick Dokoozlian
Incorporation Of Unmanned Aerial Vehicle (Uav) Point Cloud Products Into Remote Sensing Evapotranspiration Models, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, William P. Kustas, Héctor Nieto, Maria Mar Alsina, Alex White, John H. Prueger, Lynn Mckee, Joseph Alfieri, Lawrence E. Hipps, Calvin Coopmans, Nick Dokoozlian
Civil and Environmental Engineering Faculty Publications
In recent years, the deployment of satellites and unmanned aerial vehicles (UAVs) has led to production of enormous amounts of data and to novel data processing and analysis techniques for monitoring crop conditions. One overlooked data source amid these efforts, however, is incorporation of 3D information derived from multi-spectral imagery and photogrammetry algorithms into crop monitoring algorithms. Few studies and algorithms have taken advantage of 3D UAV information in monitoring and assessment of plant conditions. In this study, different aspects of UAV point cloud information for enhancing remote sensing evapotranspiration (ET) models, particularly the Two-Source Energy Balance Model (TSEB), over …
Domain Adaptation In Unmanned Aerial Vehicles Landing Using Reinforcement Learning, Pedro Lucas Franca Albuquerque
Domain Adaptation In Unmanned Aerial Vehicles Landing Using Reinforcement Learning, Pedro Lucas Franca Albuquerque
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Landing an unmanned aerial vehicle (UAV) on a moving platform is a challenging task that often requires exact models of the UAV dynamics, platform characteristics, and environmental conditions. In this thesis, we present and investigate three different machine learning approaches with varying levels of domain knowledge: dynamics randomization, universal policy with system identification, and reinforcement learning with no parameter variation. We first train the policies in simulation, then perform experiments both in simulation, making variations of the system dynamics with wind and friction coefficient, then perform experiments in a real robot system with wind variation. We initially expected that providing …
Extending Mission Duration Of Uas Multicopters: Multi-Disciplinary Approach, Marc Lussier
Extending Mission Duration Of Uas Multicopters: Multi-Disciplinary Approach, Marc Lussier
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
Multicopters are important tools in industry, the military, and research but suffer from short flight times and mission durations. In this thesis, we discuss three different ways to increase flight times and therefore increase the viability of using multicopters in a variety of missions. Alternate fuel sources such as hydrogen fuel and solar cells are starting to be used on multicopters, in our research we simulate modern fuel cells and show how well they currently work as the power source for multicopters and how close they are to becoming useful in Unmanned Aircraft System (UAS) technology. Increasing the efficiency in …
Development Of An Autonomous Aerial Toolset For Agricultural Applications, Terrance Life
Development Of An Autonomous Aerial Toolset For Agricultural Applications, Terrance Life
Mahurin Honors College Capstone Experience/Thesis Projects
According to the United Nations, the world population is expected to grow from its current 7 billion to 9.7 billion by the year 2050. During this time, global food demand is also expected to increase by between 59% and 98% due to the population increase, accompanied by an increasing demand for protein due to a rising standard of living throughout developing countries. [1] Meeting this increase in required food production using present agricultural practices would necessitate a similar increase in farmland; a resource which does not exist in abundance. Therefore, in order to meet growing food demands, new methods will …
Propulsion System Testing For A Long-Endurance Solar-Powered Unmanned Aircraft, D. Dantsker, Robert Deters, Marco Caccamo
Propulsion System Testing For A Long-Endurance Solar-Powered Unmanned Aircraft, D. Dantsker, Robert Deters, Marco Caccamo
Publications
The increase in popularity of unmanned aerial vehicles (UAVs) has been driven by their use in civilian, education, government, and military applications. However, limited on-board energy storage significantly limits flight time and ultimately usability. The propulsion system plays a critical part in the overall energy consumption of the UAV; therefore, it is necessary to determine the most optimal combination of possible propulsion system components for a given mission profile, i.e. propellers, motors, and electronic speed controllers (ESC). Hundreds of options are available for the different components with little performance specifications available for most of them. In order to determine the …
Uav/Satellite Multiscale Data Fusion For Crop Monitoring And Early Stress Detection, V. Sagan, M. Maimaitijiang, P. Sidike, M. Maimaitiyiming, H. Erkbol, S. Hartling, K. T. Peterson, J. Peterson, Joel Gerard Burken, F. Fritschi
Uav/Satellite Multiscale Data Fusion For Crop Monitoring And Early Stress Detection, V. Sagan, M. Maimaitijiang, P. Sidike, M. Maimaitiyiming, H. Erkbol, S. Hartling, K. T. Peterson, J. Peterson, Joel Gerard Burken, F. Fritschi
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Early stress detection is critical for proactive field management and terminal yield prediction, and can aid policy making for improved food security in the context of climate change and population growth. Field surveys for crop monitoring are destructive, labor-intensive, time-consuming and not ideal for large-scale spatial and temporal monitoring. Recent technological advances in Unmanned Aerial Vehicle (UAV) and high-resolution satellite imaging with frequent revisit time have proliferated the applications of this emerging new technology in precision agriculture to address food security challenges from regional to global scales. In this paper, we present a concept of UAV and satellite virtual constellation …
The Impact Of Shadows On Partitioning Of Radiometric Temperature To Canopy And Soil Temperature Based On The Contextual Two-Source Energy Balance Model (Tseb-2t), Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, Hector Nieto, William Kustas, Calvin Coopmans
The Impact Of Shadows On Partitioning Of Radiometric Temperature To Canopy And Soil Temperature Based On The Contextual Two-Source Energy Balance Model (Tseb-2t), Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, Hector Nieto, William Kustas, Calvin Coopmans
AggieAir Publications
Tests of the most recent version of the two-source energy balance model have demonstrated that canopy and soil temperatures can be retrieved from high-resolution thermal imagery captured by an unmanned aerial vehicle (UAV). This work has assumed a linear relationship between vegetation indices (VIs) and radiometric temperature in a square grid (i.e., 3.6 m x 3.6 m) that is coarser than the resolution of the imagery acquired by the UAV. In this method, with visible, near infrared (VNIR), and thermal bands available at the same high-resolution, a linear fit can be obtained over the pixels located in a grid, where …
Uumanned Aerial Vehicle Data Analysis For High-Throughput Plant Phenotyping, Jiating Li
Uumanned Aerial Vehicle Data Analysis For High-Throughput Plant Phenotyping, Jiating Li
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
The continuing population is placing unprecedented demands on worldwide crop yield production and quality. Improving genomic selection for breeding process is one essential aspect for solving this dilemma. Benefitted from the advances in high-throughput genotyping, researchers already gained better understanding of genetic traits. However, given the comparatively lower efficiency in current phenotyping technique, the significance of phenotypic traits has still not fully exploited in genomic selection. Therefore, improving HTPP efficiency has become an urgent task for researchers. As one of the platforms utilized for collecting HTPP data, unmanned aerial vehicle (UAV) allows high quality data to be collected within short …
Using A Balloon-Launched Unmanned Glider To Validate Real-Time Wrf Modeling, Travis J. Schuyler, S. M. Iman Gohari, Gary Pundsack, Donald Berchoff, Marcelo I. Guzman
Using A Balloon-Launched Unmanned Glider To Validate Real-Time Wrf Modeling, Travis J. Schuyler, S. M. Iman Gohari, Gary Pundsack, Donald Berchoff, Marcelo I. Guzman
Chemistry Faculty Publications
The use of small unmanned aerial systems (sUAS) for meteorological measurements has expanded significantly in recent years. SUAS are efficient platforms for collecting data with high resolution in both space and time, providing opportunities for enhanced atmospheric sampling. Furthermore, advances in mesoscale weather research and forecasting (WRF) modeling and graphical processing unit (GPU) computing have enabled high resolution weather modeling. In this manuscript, a balloon-launched unmanned glider, complete with a suite of sensors to measure atmospheric temperature, pressure, and relative humidity, is deployed for validation of real-time weather models. This work demonstrates the usefulness of sUAS for validating and improving …
First Approach To Coupling Of Numerical Lifting-Line Theory And Linear Covariance Analysis For Uav State Uncertainty Propagation, Cory D. Goates, Randall S. Christensen, Robert C. Leishman
First Approach To Coupling Of Numerical Lifting-Line Theory And Linear Covariance Analysis For Uav State Uncertainty Propagation, Cory D. Goates, Randall S. Christensen, Robert C. Leishman
Faculty Publications
Numerical lifting-line is a computationally efficient method for calculating aerodynamic forces and moments on aircraft. However, its potential has yet to be tapped for use in guidance, navigation, and control (GN&C). Linear covariance analysis is becoming a popular GN&C design tool and shows promise for pairing with numerical lifting-line. Pairing numerical lifting-line with linear covariance analysis allows for forward propagation of state uncertainty for real-time decision making. We demonstrate this for select state variables in a drone aerial recapture situation. Linear covariance analysis uses finite difference derivatives obtained from numerical lifting-line to calculate force and moment variances. These show agreement …
Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao
Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao
Biological Systems Engineering: Papers and Publications
The development of unmanned aerial vehicles (UAVs) and image processing algorithms for field-based phenotyping offers a non-invasive and effective technology to obtain plant growth traits such as canopy cover and plant height in fields. Crop seedling stand count in early growth stages is important not only for determining plant emergence, but also for planning other related agronomic practices. The main objective of this research was to develop practical and rapid remote sensing methods for early growth stage stand counting to evaluate mechanically seeded rapeseed (Brassica napus L.) seedlings. Rapeseed was seeded in a field by three different seeding devices. A …
Design Of Plant Protection Uav Variable Spray System Based On Neural Networks, Sheng Wen, Quanyong Zhang, Xuanchun Yin, Yubin Lan, Jiantao Zhang, Yufeng Ge
Design Of Plant Protection Uav Variable Spray System Based On Neural Networks, Sheng Wen, Quanyong Zhang, Xuanchun Yin, Yubin Lan, Jiantao Zhang, Yufeng Ge
Biological Systems Engineering: Papers and Publications
Recently, unmanned aerial vehicles (UAVs) have rapidly emerged as a new technology in the fields of plant protection and pest control in China. Based on existing variable spray research, a plant protection UAV variable spray system integrating neural network based decision making is designed. Using the existing data on plant protection UAV operations, combined with artificial neural network (ANN) technology, an error back propagation (BP) neural network model between the factors affecting droplet deposition is trained. The factors affecting droplet deposition include ambient temperature, ambient humidity, wind speed, flight speed, flight altitude, propeller pitch, nozzles pitch and prescription value. Subsequently, …
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Faculty Publications
A key enabler of autonomous vehicles is the ability to plan the path of the vehicle to accomplish mission objectives. To be robust to realistic environments, path planners must account for uncertainty in the trajectory of the vehicle as well as uncertainty in the location of obstacles. The uncertainty in the trajectory of the vehicle is a difficult quantity to estimate, and is influenced by coupling between the vehicle dynamics, guidance, navigation, and control system as well as any disturbances acting on the vehicle. Monte Carlo analysis is the conventional approach to determine vehicle dispersion, while accounting for the coupled …
The Effect Of Communication And Vehicle Properties On The Search Performance Of A Swarm Of Unmanned Aerial Vehicles, Jenna E. Newcomb, Andrew Ning
The Effect Of Communication And Vehicle Properties On The Search Performance Of A Swarm Of Unmanned Aerial Vehicles, Jenna E. Newcomb, Andrew Ning
Faculty Publications
An unmanned aerial vehicle (UAV) swarm allows for a more time-efficient method of searching a specified area than a single UAV or piloted plane. There are a variety of factors that affect how well an area is surveyed. We specifically analyzed the effect both vehicle properties and communication had on the swarm search performance. We used non-dimensionalization to examine the effect vehicle properties had on search performance so the results can be applied to any domain size with any number and type of vehicle. We found that even if vehicles could only sense 10% of the grid area at any …