Browsing by Subject "UAV"

Now showing 1 - 17 of 17
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    Accuracy of UAV Pitot-Static System
    (2012-04-18) Carlson, Ryan
    Though they are unnecessary for the structural integrity of the aircraft, an error in the pitot-static system can cause inaccuracies in flight and eventually lead to aircraft failure. Through a series of tests, the University of Minnesota’s UAV pitot-static system error was calculated and graphed. This allows the pressure sensors built into the pitot-static system to be calibrated for error, which prevents harm to the aircraft and operators.
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    Characterizing the impact of genetic and environmental variation on maize utilizing phenomic approaches
    (2020-08) Tirado, Sara
    To gain a better understanding of how genotypic elements interact with the environment, we need to develop more efficient ways of monitoring plant phenotypes so that we can gather phenotypic data through time. Remote sensing technologies provide effective means to do this. Sensor, computational, and platform technologies keep evolving and provide avenues to evaluate how plants grow and respond to environmental conditions. The goals of this thesis were to develop methods and analytical procedures to evaluate maize plant phenotypic performance under varied environmental conditions. The first set of experiments were geared towards utilizing unmanned aerial vehicles equipped with RGB cameras to assess how maize plants grow in response to various field management conditions, including various planting dates and densities, and weather events. These tools were used to assess variation for lodging responses and downstream impacts on productivity. More generally, results from this thesis demonstrate that measurements collected early in development can be useful for improving predictions of end-season traits. The second set of experiments provided insights into using hyperspectral technologies for genotypic differentiation and abiotic stress detection. There is a large amount of variation in reflectance throughout maize leaves that can be useful in distinguishing different maize genotypes at the seedling stage and for detecting and quantifying abiotic stress conditions including cold, heat, and salt stress early in development. By documenting phenotypic differences across genotypes and environments through time in a more efficient manner by taking advantage of available remote sensing technologies, we can improve our understanding of how different environmental and genetic elements impact plant productivity and facilitate advancements in crop improvement and production.
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    Evaluating the Impact of Parasitic Drag on the Accuracy of Endurance Predictions
    (2018-08) Heide, Leonid
    The cost-effectiveness and versatility of electric unmanned aerial vehicles (UAVs) has led to an increase in demand for efficient payload-carrying aircraft [4]. Many project criteria require an endurance prediction based on a specific mission profile. Current methods for determining the endurance of fixed-wing UAVs involves estimating the key variable of parasitic drag using empirical equations and approximated drag values. This study seeks to evaluate the impact of estimating parasitic drag using conventional methods on the accuracy of endurance predictions for UAVs. Using glide tests, drag is measured for a small electric aircraft, and compared to predictions made using the component drag build up-method for conventional aircraft. It is demonstrated that the parasitic drag generated by small UAVs is sufficiently large to invalidate endurance predictions based on coefficients of drag calculated with the standard component drag build up method developed for fixed wing aircraft.
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    A formal investigation of the organization of guidance behavior: implications for humans and autonomous implications for humans and autonomous
    (2012-10) Kong, Zhaodan
    Guidance behavior generated either by artificial agents or humans has been actively studied in the fields of both robotics and cognitive science. The goals of these two fields are different. The former is the automatic generation of appropriate or even optimal behavior, while the latter is the understanding of the underlying mechanism. Their challenges, though, are closely related, the most important one being the lack of a unified, formal and grounded framework where the guidance behavior can be modeled and studied. This dissertation presents such a framework. In this framework, guidance behavior is analyzed as the closed-loop dynamics of the whole agent-environment system. The resulting dynamics give rise to interaction patterns. The central points of this dissertation are that: first of all, these patterns, which can be explained in terms of symmetries that are inherent to the guidance behavior, provide building blocks for the organization of behavior; second, the existence of these patterns and humans' organization of their guidance behavior based on these patterns are the reasons that humans can generate successful behavior in spite of all the complexities involved in the planning and control. This dissertation first gives an overview of the challenges existing in both scientific endeavors, such as human and animal spatial behavior study, and engineering endeavors, such as autonomous guidance system design. It then lays out the foundation for our formal framework, which states that guidance behavior should be interpreted as the collection of the closed-loop dynamics resulting from the agent's interaction with the environment. The following, illustrated by examples of three different UAVs, shows that the study of the closed-loop dynamics should not be done without the consideration of vehicle dynamics, as is the common practice in some of the studies in both autonomous guidance and human behavior analysis. The framework, the core concepts of which are symmetries and interaction patterns, is then elaborated on with the example of Dubins' vehicle's guidance behavior. The dissertation then describes the details of the agile human guidance experiments using miniature helicopters, the technique that is developed for the analysis of the experimental data and the analysis results. The results confirm that human guidance behavior indeed exhibits invariance as defined by interaction patterns. Subsequently, the behavior in each interaction pattern is investigated using piecewise affine model identification. Combined, the results provide a natural and formal decomposition of the behavior that can be unified under a hierarchical hidden Markov model. By employing the languages of dynamical system and control and by adopting algorithms from system identification and machine learning, the framework presented in this dissertation provides a fertile ground where these different disciplines can meet. It also promises multiple potential directions where future research can be headed.
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    Hirsch Lab UAV Commercial Maize Phenotyping Project at UMN SROC Waseca: 2020, 2021, and 2022
    (2024-04-22) Sweet, Dorothy D; Hirsch, Candice N; Hirsch, Cory D; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch Lab
    This dataset provides a valuable resource for evaluating the ability of unoccupied aerial vehicles to collect plant height information from commercial agricultural fields and predict within field variation in yield using temporal traits including plant height, growth rate, and vegetative indices. Many flights were conducted over commercial maize fields using an UAV equipped with an RGB camera and this dataset includes orthomosaics and digital elevation models generated from those flights as well as plot boundary shape files used for extraction of data from those flights. Data in this repository includes extracted plant height, extracted RGB vegetative indices, manual height measurements, weather data, soil data, and grain yield. This experiment consisted of three commercial fields containing single maize hybrids and is therefore useful in assessing the ability of UAV extracted values in identifying within field variation for prediction of yield. It can also be used to test different methods of extracting plant height values from commercial fields as it includes manual measurements of height to be used in evaluation.
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    Reference Position and Attitude together with Raw Sensor Data from Seven Small UAV Flights during 2011-12
    (2014-09-09) Mokhtarzadeh, Hamid
    Reference trajectory (3D position and attitude) and raw sensor data (at 50 Hz) for seven small UAV flights are included. The flights can be used individually or collectively. Collectively they cover a 1 square kilometer area. The flights were collected over the span of 2011-2012 by the University of Minnesota UAV Research Group and were retrieved for research purposes in 2013-2014. All seven flights have been successfully used to study navigation system design. Through a simulated play-back of the data, both an attitude heading reference system (AHRS) and an airspeed-based dead reckoning navigation system were implemented on all seven flights and the results correspond well with the logged reference solutions. As part of testing new ideas for small UAVs or navigation in general, it is useful to have a data set which has been tried and tested. This subset of flights from the AEM UAV Flight repository is exactly that and is being shared with the hope of serving as a working data set for testing new concepts and ideas.
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    Reliability assessment for low-cost unmanned aerial vehicles
    (2014-11) 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 algorithms to experimental faulted and unfaulted flight test data. Flight tests are conducted with actuator faults that affect the plant input and sensor faults that affect the vehicle state measurements. A model-based detection strategy is designed and uses robust linear filtering methods to reject exogenous disturbances, e.g. wind, while providing robustness to model variation. A data-driven algorithm is developed to operate exclusively on raw flight test data without physical model knowledge. The fault detection and identification performance of these complementary but different methods is compared. Together, enhanced reliability assessment and multi-pronged fault detection and identification techniques can help to bring about the next generation of reliable low-cost unmanned aircraft.
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    Small UAV Position and Attitude, Raw Sensor, and Aerial Imagery Data Collected over Farm Field with Surveyed Markers
    (2015-02-25) Mokhtarzadeh, Hamid; Colten, Todd; mokh0006@umn.edu; Mokhtarzadeh, Hamid
    Imagery and sensor data from a commercial small Uninhabited Aerial Vehicle flown over an agriculture field on the morning of October 22, 2014 have been logged and documented. The field includes 16 surveyed ground control points laid out in a 4x4 square serving as known ground control points. This data set serves to study both challenges and opportunities of UAV-based remote sensing for precision agriculture applications. The raw sensor data can be used for navigation system design and analysis. The imagery and logged aircraft state can be used for image processing as well as remote sensing analysis. It is being shared to served as a documented data set for testing new concepts and ideas.
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    Springer Lab UAV Maize Phenotyping Project at UMN StPaul: 2018 and 2019
    (2020-05-05) Tirado, Sara B; Hirsch, Candice N; Springer, Nathan M; springer@umn.edu; Springer, Nathan M; Springer Lab
    This dataset provides a valuable resource for evaluating the utility of unmanned aerial vehicles to collect phenotypic data in agricultural fields. Many flights throughout the growing season of a maize experiment were conducted and this dataset includes digital elevation models generated from images within these flights, the plot boundary shapefiles for plot identification, plant height values extracted following Tirado et al., 2019 procedure, hand measurement height values conducted following flights, and yield data for each plot. This maize experiment consisted of twelve hybrids planted at three different planting densities (low, medium and high) and two planting dates (early and late) across two years and therefore provides a valuable resource for evaluating how temporal data collected from UAVs can aid in assessing plant productivity. It can also be utilized to develop and test different protocols for plant height extraction from DEMs at different growth stages as the hand measurements can be used to test the accuracy.
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    Synthesis and validation of flight control for UAV.
    (2009-11) Paw, Yew Chai
    Unmanned Aerial Vehicles (UAVs) are widely used worldwide for a board range of civil and military applications. There continues to be a growing demand for reliable and low cost UAV systems. This is especially true for small-size mini UAV systems where majority of systems are still deployed as prototypes due to their lack of reliability. Improvement in the modeling, testing and flight control for the small UAVs would increase their reliability during autonomous flight. The traditional approach used in manned aircraft and large UAV system synthesizing, implementing and validating the flight control system to achieve desired objectives is time consuming and resource intensive. This thesis aims to provide an integrated framework with systematic procedures to synthesize and validate flight controllers. This will help in the certification of UAV system and provide rapid development cycle from simulation to real system flight testing. The effectiveness of the approach is demonstrated by applying the developed framework on a small UAV system that was developed at the University of Minnesota. The thesis is divided into four main parts. The first part is mathematical modeling of the UAV nonlinear simulation model using first principle theory. Flight test system identification technique is used to extract model and model uncertainty parameters to update the nonlinear simulation model. The nonlinear simulation model developed must be able to simulate the actual UAV flight dynamics accurately for real-time simulation and robust control design purposes. Therefore it is important to include model uncertainties into the nonlinear simulation model developed, especially in small UAV system where its dynamics is less well understood than the full-size aircraft. The second part of the work provides the approach and procedures for uncertainty modeling into the nonlinear simulation model such that realization of linear uncertain model is possible. The third part of work describes the flight control design and architecture used in the UAV autopilot system. Classical and model-based control synthesis approaches are presented for roll angle tracking controller to demonstrate the controller synthesis approaches and practical controller implementation issues on the embedded flight computer system. The last part of work blends in all the previous works into the integrated framework for testing and validation of the synthesized controllers. This involves software-in-the-loop, processor-in-the-loop and flight testing of the synthesized controllers using the integrated framework developed.
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    Temporally resolved growth patterns in diverse maize panel
    (2023-01-27) Sweet, Dorothy D; Tirado, Sara B; Cooper, Julian S; Springer, Nathan M; Hirsch, Cory D; Hirsch, Candice N; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch Lab
    Plant height is used in many breeding programs for assessing plant health across environments and predicting yield, which can be used in identifying superior hybrids or evaluating abiotic stress factors. This has often been measured at a single time point when plants have reached their terminal height for the season. Collection of plant height using unoccupied aerial vehicles (UAVs) is faster, allowing for measurements throughout the growing season which could facilitate a better understanding of plant-environment interaction and responses. To assess variation in plant height and growth rate throughout development, plant height data was collected weekly for a panel of ~500 diverse inbred lines over four growing seasons. The variation in plant height throughout the season was found to be significantly explained by genotype, year, and genotype-by-year interactions throughout vegetative growth. However, the relative contributions of these different sources of variation fluctuated throughout development. This variation was further captured by Fréchet distance values which identified genotypes with consistently high or low distances in each of the four years - high distance genotypes being more dissimilar between replications and therefore capturing more environmental variation. Genome-wide association studies revealed many significant SNPs associated with plant height and growth rate at different parts of the growing season that would not be identified by terminal height alone. When comparing growth rates estimated from plant height to growth rates estimated from another morphological characteristic, canopy cover, we found greater stability in growth curves estimated by plant height. This potentially makes canopy cover more useful for understanding environmental modulation of overall plant growth and plant height better for understanding genotypic modulation of overall plant growth. Overall, this suggests evaluations of plant growth throughout the season provide more information than terminal plant height alone.
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    Test platforms for model-based flight research
    (2013-09) Dorobantu, Andrei
    Demonstrating the reliability of flight control algorithms is critical to integrating unmanned aircraft systems into the civilian airspace. For many potential applications, design and certification of these algorithms will rely heavily on mathematical models of the aircraft dynamics. Therefore, the aerospace community must develop flight test platforms to support the advancement of model-based techniques. The University of Minnesota has developed a test platform dedicated to model-based flight research for unmanned aircraft systems. This thesis provides an overview of the test platform and its research activities in the areas of system identification, model validation, and closed-loop control for small unmanned aircraft.
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    UAV for Reliability Senior Design Project
    (2014-07-23) Bergquist, Erik; Reimann, Shawn; Amos, Jeremy; Cole, Jay; Phillips, Justin; Shuster, Simon
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    UAV Laboratories AEM Systems Group Seminar 20140926
    (2014-09-19) Taylor, Brian
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    UAV-based hyperspectral dataset for high-throughput yield phenotyping in wheat
    (2020-01-14) Moghimi, Ali; Yang, Ce; Anderson, James A.; moghi005@umn.edu; Moghimi, Ali; University of Minnesota
    The dataset was collected by a hyperspectral camera (PIKA II, Resonon, Inc.) mounted on an unmanned aerial vehicle (UAV, DJI Matrice 600 Pro) from three experimental yield trial fields (C3, C4, and C9) during two consecutive growing seasons 2017 (C3 and C9) and 2018 (C4). The aerial hyperspectral images were captured within two weeks prior to harvest over 240 spectral channels in visible and near infrared region (400 nm to 900 nm) with about 2.1 nm spectral resolution and about 2 cm spatial resolution. Subsequent to radiometric calibration and noisy band removal, plots were cropped from the hyperspectral images and saved as 3D matrices with Matlab (MAT files) and Python (NPY files) format. The dataset entails hyperspectral cubes of 1021 wheat plots and the grain yield of plots harvested by a combine. The corresponding ground truth data (yield) for each hyperspectral cube representing a plot can be found based on the field (e.g., C3, C4, and C9) and plot ID.
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    Unmanned Aerial Vehicles and Journalistic Disruption
    (Digital Journalism, 2017) Belair-Gagnon, Valerie; Holton, Avery; Owen, Taylor
    In recent years, there has been a surge in research on small unmanned aerial vehicles (UAVs) in news production and news audience engagement. Most of this research has focused on legal, ethical, and regulatory implications of UAVs in newsgathering, while paying less attention to the journalists’ perspectives. To fill this gap in the academic literature, this article explores the ethical principles that guide journalists who use UAVs, how they have worked within these ethical principles, and how they can serve as disruptive innovators. Semistructured interviews with 13 UAV early adopters reveal that legal and regulatory restraints on UAVs facilitated the emergence of a new form of norm entrepreneur inside journalistic institutions. These individuals were able to experiment on the fringes of acceptable practice. In so doing, they seeded their organizations with the skill set and institutional capacity to engage constructively with the use of UAVs once constraints were lifted.