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Nevins, Robert PardyGeoreferencing Unmanned Aerial Systems Imagery via Registration with Geobrowser Reference Imagery
Master of Science, The Ohio State University, 2017, Civil Engineering
Unmanned aerial systems are developing into increasingly competitive platforms for aerial image surveying in a variety of applications. Easy-to-use and relatively inexpensive, their utility is however reliant on georeferencing their imagery with respect to an earth-based coordinate system. Traditionally this requires the time-consuming and potentially cost-increasing introduction of ground control points into the scene of interest. Other techniques, such as direct georeferencing using integrated Global Navigation Satellite System receivers and inertial navigations systems, struggle to achieve comparable accuracy due to weight and cost limitations faced with highest-accuracy instrumentation. In this work, unmanned aerial system imagery was georeferenced via registration with satellite imagery downloaded from online geobrowser image databases, specifically Environmental Systems Research Institute World Imagery. This method allows the potential elimination of all fieldwork related to ground control point distribution and surveying, taking advantage instead of instantaneous access daytime, cloud-free satellite imagery provided by geobrowsers. Registration was performed both using pixel-based template matching, and successive application of pixel-based and feature-based keypoint detection and matching techniques. Test imagery was collected by unmanned aerial systems over a parking lot and surrounding area in central Ohio. Root mean square error results were calculated for both pixel-based and successive pixel-based and feature-based registration with respect to 8 ground control points measured independently by Global Navigation Satellite System survey. Using 0.3 meter reference imagery, sub-pixel accuracy was achieved with successive pixel-based and feature-based registration. Possible applications include unmanned aerial systems mapping for endeavors such as precision agriculture, and unmanned aerial systems navigation.

Committee:

Dorota Grejner-Brzezinska, Ph.D. (Advisor); Charles Toth, Ph.D. (Committee Member); Rongjun Qin, Ph.D. (Committee Member)

Subjects:

Civil Engineering

Keywords:

UAV; UAS; Photogrammetry; Mapping; Image Matching; Image Registration

Hogue, Jonathon D.Mapping a Forest: Utilizing an Unmanned Aerial Vehicle to Track Phenology
Master of Science (MS), Ohio University, 2018, Geography (Arts and Sciences)
This project acquired high-resolution, RGB images of a deciduous forest in Athens, Ohio from an unmanned aerial vehicle over the course of a year. With UAVs, greater temporal and spatial scales exist today than what were available in the recent past with the full capabilities of these images yet to be fully assessed. The goal of the project was to follow the different phenology patterns of various deciduous trees to accurately map the project site while formulating a reproducible methodology for future work. Acquiring mosaics for 29 dates in 2017, a supervised Maximum Likelihood Classification scheme was employed to classify various species using 15 of the mosaics. Simultaneously, spectral profiles were built for 16 common species at the site using 25 of the mosaics. A community level map displaying three main groups was produced for the study site along with a phenology calendar which highlights key dates for identifying various species. The results of this project show that many species have a high amount of overlap in their spectral signals following phenology, making differentiation of individual species difficult when employing a pixel-based approach alone.

Committee:

James Dyer, Dr. (Advisor); James Lein, Dr. (Committee Member); Jana Houser, Dr. (Committee Member)

Subjects:

Geography

Keywords:

Phenology; UAV; forest mapping

Scott, Kevon KOcclusion-Aware Sensing and Coverage in Unmanned Aerial Vehicle (UAV) Networks
MS, University of Cincinnati, 2016, Engineering and Applied Science: Computer Engineering
The use of small and miniature Unmanned Aerial Vehicles (UAVs) for remote sensing and surveillance applications has become increasingly popular in the last two decades. Networks of UAVs, capable of providing flexible aerial views over large areas, are playing important roles in today's distributed sensing systems. Since camera sensors are sensitive to occlusions, it is more challenging to deploy UAVs for sensing in geometrically complex environments, such as dense urban areas and mountainous terrains. The intermittent connectivity in a sparse UAV network also makes it challenging to efficiently gather sensed multimedia data. This thesis is composed of two pieces of work. In the first piece of work, a new occlusion-aware UAV coverage technique with the objective of sensing a target area with satisfactory spatial resolution subject to the energy constraints of UAVs is proposed. An occlusion-aware waypoint generation algorithm is first designed to find the best set of waypoints for taking pictures in a target area. The selected waypoints are then assigned to multiple UAVs by solving a vehicle routing problem (VRP), which is formulated to minimize the maximum energy for the UAVs to travel through the waypoints. A genetic algorithm is designed to solve the VRP problem. Evaluation results show that the proposed coverage technique can reduce energy consumption while achieving better coverage than traditional coverage path planning techniques for UAVs. In the second piece of work, a communication scheme is designed to deliver the images sensed by a set of mobile survey UAVs to a static base station through the assistance of a relay UAV. Given the planned routes of the survey UAVs, a set of relay waypoints are found for the relay UAV to meet the survey UAVs and receive the sensed images. An Online Message Relaying technique (OMR) is proposed to schedule the relay UAV to collect images. Without any global collaboration between the relay UAV and the survey UAVs, OMR utilizes a markov decision process (MDP) that determines the best schedules for the relay UAV such that the image acquisition rate could be maximized. Evaluation results show that the proposed relaying technique outperforms traditional relaying techniques, such as the traveling salesman problem (TSP) and the random walk, in terms of end-to-end delay and frame delivery ratio.

Committee:

Rui Dai, Ph.D. (Committee Chair); Dharma Agrawal, D.Sc. (Committee Member); Carla Purdy, Ph.D. (Committee Member)

Subjects:

Computer Engineering

Keywords:

Unmanned Aerial Vehicle;UAV;Occlusion;FANET;Flying Ad-Hoc Networks;Remote Sensing

Landolfo, GiuseppeAerodynamic and Structural Design of a Small Nonplanar Wing UAV
Master of Science (M.S.), University of Dayton, 2008, Aerospace Engineering
The overall air vehicle performance of a multiple lifting surface configuration has been studied with respect to both structural and aerodynamic considerations for a candidate mission similar to that of the AeroVironment Raven. The configuration studied is a biplane joined at the tips with endplates. More specifically, this study aims to determine if this particular nonplanar wing concept can meet the requirements of the mission for a small Reconnaissance, Surveillance and Target Acquisition UAV. The mission capabilities of small UAVs are constantly growing by implementing recent developments in miniature computers and peripherals, electronic sensors, and optical sensing equipment at affordable cost. The requirements for the mission profile of a small UAV using the aforementioned equipment are defined with an emphasis on the potential advantages that can be offered by the nonplanar concept wing under investigation. A structural analysis using the finite element software ADINA and an aerodynamic analysis based on wind tunnel experimental data and vortex panel code results are performed. The results, compared under varying assumptions specific to an equivalent monoplane and a biplane, suggest potential efficiency gains for the new configuration may be possible using the nonplanar wing configuration under explicit conditions. The results also show structural characteristics and not aerodynamics alone are critical in determining the utility of this nonplanar concept.

Committee:

Aaron Altman (Advisor)

Subjects:

Engineering

Keywords:

Aerospace; aircraft design; aerodynamics; structural analysis; UAV; unmanned aircraft; biplane

Ernest, Nicholas D.UAV Swarm Cooperative Control Based on a Genetic-Fuzzy Approach
MS, University of Cincinnati, 2012, Engineering and Applied Science: Aerospace Engineering

The ever-increasing applications of UAV’s have shown the great capabilities of these technologies. However, for many cases where one UAV is a powerful tool, an autonomous swarm all working cooperatively to the same goal presents amazing potential. Environment that are dangerous for humans, are either too small or too large for safe or reasonable exploration, and even those tasks that are simply boring or unpleasant are excellent areas for UAV swarm applications. In order to work cooperatively, the swarm must allocate tasks and have adequate path planning capability.

This paper presents a methodology for two-dimensional target allocation and path planning of a UAV swarm using a hybridization of control techniques. Genetic algorithms, fuzzy logic, and to an extent, dynamic programming are utilized in this research to develop a code known as “UNCLE SCROOGE” (UNburdening through CLustering Effectively and Self-CROssover GEnetic algorithm). While initially examining the Traveling Salesman Problem, where an agent must visit each waypoint in a set once and then return home in the most efficient path, the work’s end goal was a variant on this problem that more closely resembled the issues a UAV swarm would encounter.

As an extension to Dr. Obenmeyer’s “Polygon-Visiting Dubins Traveling Salesman Problem”, the Multi-Depot Polygon-Visiting Dubins Multiple Traveling Salesman Problem consists of a set number of visibility areas, or polygons that a number of UAV’s, based in different or similar depot must visit. While this case is constant altitude and constant velocity, minimum turning radii are considered through the use of Dubins curves. UNCLE SCROOGE was found to be adaptable to the PVDTSP, where it competed well against the methods proposed by Obenmeyer. Due to limited benchmarking ability, as these are newly formed problems, Obenmeyer’s work served as the only basis for comparison for the PVDTSP. UNCLE SCROOGE brought a 9.8% increase in accuracy, and a run-time reduction of more than a factor of ten for a 20 polygonal case with strict turning requirements. This increase in performance came with a 99% certainty of receiving the best found solution over the course of 100 runs. With only a 1% chance for error in this particular case, the hybridized method has been shown to be quite powerful.

While no comparison is currently possible for MDPVDMTSP solutions, UNCLE SCROOGE was found to develop promising results. On average, it takes the code 25.62 seconds to approximately solve a 200 polygon, 4 depot, 5 UAV’s per depot problem. This polygon count was increased even up to 2,500, with a solution taking 9.8 hours. It has been shown that UNCLE SCROOGE performs well in solving the MDPVDMTSP and has acceptable scalability.

Committee:

Kelly Cohen, PhD (Committee Chair); Manish Kumar, PhD (Committee Member); Bruce Walker, ScD (Committee Member)

Subjects:

Aerospace Materials

Keywords:

UAV Swarm;Cooperative Control;Genetic Algorithm;Fuzzy Logic;Traveling Salesman Problem;;

Sabo, ChelseaRouting and Allocation of Unmanned Aerial Vehicles with Communication Considerations
PhD, University of Cincinnati, 2012, Engineering and Applied Science: Aerospace Engineering

Cooperative Unmanned Aerial Vehicles (UAV) teams are anticipated to provide much needed support for human intelligence, measurement and signature intelligence, signals intelligence, imagery intelligence, and open source intelligence through algorithms, software, and automation. Therefore, it is necessary to have autonomous algorithms that route multiple UAVs effectively and efficiently throughout missions and that these are realizable in the real-world given the associated uncertainties. Current routing strategies ignore communication constraints altogether. In reality, communication can be restricted by bandwidth, line-of-sight, maximum communication ranges, or a need for uninterrupted transmission. Generating autonomous algorithms that work effectively around these communication constraints is key for the future of UAV surveillance applications.

In this work, both current and new routing strategies for UAVS are analyzed to determine how communications impact efficiency of information return. It is shown that under certain communication conditions, a new approach on routing can be more efficient than typically adopted strategies. This new approach defines and presents a new formulation based on a minimum delivery latency objective function. The problem is formulated such that information is not considered delivered until it is returned back to a high-bandwidth connection (depot) which is common when communication is restricted. The size of the region is shown to be dependent upon distance between requests, UAV bandwidth, UAV velocity, and data size, but it was shown that for large-sized data, long distances, and low bandwidth, it is generally better to route UAVs with this new minimum latency objective.

With the added decision of when to deliver information to a high-bandwidth connection, an already computationally complex problem grows even faster. Because of scaling issues, a heuristic algorithm was developed that was constructed by analyzing the optimal solution. The algorithm is a cluster-first, route-second approach, but differs from conventional Vehicle Routing Problem (VRP) solutions in that the number of clusters is not necessarily equal to the number of vehicles. Because of this, a unique approach to clustering is adopted to form clusters using hierarchical agglomerative clustering and fuzzy logic. Based on a detailed Monte Carlo analysis, the heuristic algorithm showed near-optimal (within ~5%) results calculable in real-time (allowing it to be used in dynamic scenarios too) and scaled to much larger problem sizes. Furthermore, the performance was analyzed under varying degrees of dynamism and arrival rates. Results showed good performance, and found the boundaries for the regions of light and heavy load cases for a single vehicle to be about 0.3 and 4 requests an hour, respectively. Finally, both static and dynamic cases were validated in flight testing, highlighting the usability of this approach.

Committee:

Kelly Cohen, PhD (Committee Chair); Derek Kingston, PhD (Committee Member); Manish Kumar, PhD (Committee Member); Grant Schaffner, PhD (Committee Member)

Subjects:

Aerospace Materials

Keywords:

UAV; Vehicle Routing; Task Allocation; Communication

Clem, Garrett StuartAn Optimized Circulating Vector Field Obstacle Avoidance Guidance for Unmanned Aerial Vehicles
Master of Science (MS), Ohio University, 2018, Mechanical Engineering (Engineering and Technology)
Unmanned Aerial Vehicles (UAVs) conventionally navigate by following a series of pre-planned waypoints. When encountering an obstacle in flight, such as no-fly zones or other aircraft, the vehicle’s path or waypoints may need to be re-planned. Waypoint guidance can be used to avoid obstacles, which are typically generated off-line and relayed to the UAV requiring active communications. Vector Fields (VFs) that are generated based on a desired path can provide guidance around a newly discovered obstacle without the need for a re-plan. VF convergence and circulation components were optimized to minimize deviation from a desired path when guiding around a circular obstacle. Results indicated that the developed VF obstacle avoidance optimizer provides similar path deviation performance as waypoints without the need for re-planning. Lookup tables for GVF circulation and decay radius were constructed allowing for real time obstacle avoidance without the need to re-plan mission waypoints. Experimental flight tests were conducted using a indoor quadcopter with imposed turn rate constraints, emulating a fixed wing UAV. Deviation from the planned path for simulation and experimentation were compared.

Committee:

Jay Wilhelm (Committee Chair)

Subjects:

Engineering; Mechanical Engineering; Robotics; Robots

Keywords:

Unmanned Aerial Vehicles; UAV;quadcopter; guidance; vector field; navigation; control; obstacle avoidance; crayflie; autonomy

Nemati, AlirezaDesigning, Modeling and Control of a Tilting Rotor Quadcopter
PhD, University of Cincinnati, 2016, Engineering and Applied Science: Electrical Engineering
The aim of the present work is to model, design, control, fabricate and experimentally study quadcopter with tilting propellers. A tilting quadcopter is an aerial vehicle whose rotors can tilt along axes perpendicular to their respective axes of rotation. The tilting rotor quadcopter provides the added advantage in terms of additional stable configurations, made possible by additional actuated controls, as compared to a traditional quadcopter without titling rotors. The tilting rotor quadcopter design is accomplished by using an additional motor for each rotor that enables the rotor to rotate along the axis of the quadcopter arm. Conventional quadcopters, due to limitation in mobility, belong to a class of underactuated robots which cannot achieve any arbitrary desired state or configuration. For example, the vehicle cannot hover at a defined point at a tilted angle. It needs to be completely horizontal in order to hover. An attempt to achieve any pitch or roll angle would result in forward (pitch) motion or lateral (roll) motion. This proposed tilting rotor concept turns the traditional quadcopter into an over-actuated flying vehicle allowing us to have complete control over its position and orientation. In this work, a dynamic model of the tilting rotor quadcopter vehicle is derived for flying and hovering modes. The model includes the relationship between vehicle orientation angles and rotor tilt-angles. Furthermore, linear and nonlinear controllers have been designed to achieve the hovering and navigation capability while having any desired pitch and/or roll orientation. In the linear approach, the four independent speeds of the propellers and their rotations about the axes of quadcopter arms have been considered as inputs. In order to start tracking a desired trajectory, first, hovering from the initial starting point is needed. Then, the orientation of the vehicle to the desired pitch or roll angle is obtained. Subsequently, any further change in pitch or roll angles, obtained using a linear controller, result in motion of the quadcopter along the desired trajectory. The dissertation then presents a nonlinear strategy for controlling the motion of the quadcopter. The overall control architecture is divided into two sub-controllers. The first controller is based on the feedback linearization control derived from the dynamic model of the tilting quadcopter. This controls the pitch, roll, and yaw motions required for movement along an arbitrary trajectory in space. The second controller is based on two Proportional Derivative (PD) controllers which are used to control the tilting of the quadcopter independently along the pitch and the yaw directions respectively. The overall control enables the quadcopter to combine tilting and movement along a desired trajectory simultaneously. Furthermore, the stability and control of tilting-rotor quadcopter is presented upon failure of one propeller during flight. On failure of one propeller, the quadcopter has a tendency of spinning about the primary axis fixed to the vehicle as an outcome of the asymmetry about the yaw axis. The tilting-rotor configuration is an over-actuated form of a traditional quadcopter and it is capable of handling a propeller failure, thus making it robust in one propeller failure during the flight. The dynamics of the vehicle once the failure accrued is derived and a controller is designed to achieve hovering and navigation capability. The dynamic model and the controller of the vehicle were verified with the help of numerical studies for diff erent flight scenarios as well as failure mode. Subsequently, two diff erent models of the vehicle were designed, fabricated and tested. Experimental results have validated the dynamical modeling and the flight controllers.

Committee:

Manish Kumar, Ph.D. (Committee Chair); Ali Minai, Ph.D. (Committee Chair); Raj Bhatnagar, Ph.D. (Committee Member); Kelly Cohen, Ph.D. (Committee Member); Rui Dai, Ph.D. (Committee Member)

Subjects:

Electrical Engineering

Keywords:

UAV;Tilt-Rotor Quadcopter;Nonlinear Control;Modeling

Gunn, Daniel VictorTarget Acquisition with UAVs: Vigilance Displays and Advanced Cueing Interfaces
PhD, University of Cincinnati, 2002, Arts and Sciences : Psychology
Future Uninhabited Aerial Vehicles (UAVs) will require operators to switch quickly and efficiently from supervisory to manual control. Utilizing a vigilance task in which threat detections (critical signals) led observers to perform a subsequent manual target acquisition task, the present investigation revealed that the type of vigilance display might have important design implications for future UAV systems. A sensory display format resulted in more threat detections, fewer false alarms, and faster target acquisition times and imposed a lighter workload than a cognitive display format. Thus, the former may be the best display arrangement for future UAV controllers. Additionally, advanced visual, spatial audio, and haptic cueing interfaces enhanced acquisition performance over no cueing in the target acquisition phase of the task, and did so to a similar degree. This finding suggests that advanced cueing interfaces may also prove useful in future UAV systems and that these interfaces are functionally interchangeable.

Committee:

Dr. Joel S. Warm (Advisor)

Subjects:

Psychology, Experimental

Keywords:

target acquisition; UAV; vigilance; advanced cueing interaces; spatial audio

Diskin, YakovDense 3D Point Cloud Representation of a Scene Using Uncalibrated Monocular Vision
Master of Science (M.S.), University of Dayton, 2013, Electrical Engineering
We present a 3D reconstruction algorithm designed to support various automation and navigation applications. The algorithm presented focuses on the 3D reconstruction of a scene using only a single moving camera. Utilizing video frames captured at different points in time allows us to determine the depths of a scene. In this way, the system can be used to construct a point cloud model of its unknown surroundings. In this thesis, we present the step by step methodology of the development of a reconstruction technique. The original reconstruction process, resulting with a point cloud was computed based on feature matching and depth triangulation analysis. In an improved version of the algorithm, we utilized optical flow features to create an extremely dense representation model. Although dense, this model is hindered due to its low disparity resolution. As feature points were matched from frame to frame, the resolution of the input images and the discrete nature of disparities limited the depth computations within a scene. With the third algorithmic modification, we introduce the addition of the preprocessing step of nonlinear super resolution. With this addition, the accuracy of the point cloud which relies on precise disparity measurement has significantly increased. Using a pixel by pixel approach, the super resolution technique computes the phase congruency of each pixel’s neighborhood and produces nonlinearly interpolated high resolution input frames. Thus, a feature point travels a more precise discrete disparity. Also, the quantity of points within the 3D point cloud model is significantly increased since the number of features is directly proportional to the resolution and high frequencies of the input image. Our final contribution of additional preprocessing steps is designed to filter noise points and mismatched features, giving birth to the complete Dense Point-cloud Representation (DPR) technique. We measure the success of DPR by evaluating the visual appeal, density, accuracy and computational expense of the reconstruction technique and compare with two state-of-the-arts techniques. After the presentation of rigorous analysis and comparison, we conclude by presenting the future direction of development and its plans for deployment in real-world applications.

Committee:

Asari Vijayan, PhD (Committee Chair); Raul Ordonez, PhD (Committee Member); Eric Balster, PhD (Committee Member)

Subjects:

Electrical Engineering; Engineering

Keywords:

monocular vision; 3D Scene Reconstruction; Dense Point-cloud Representation; Point Cloud Model; DPR; Super Resolutoin; Vision Lab; University of Dayton; Computer Vision; Vision Navigation; UAV; UAS; UGV; RAIDER; Yakov Diskin; Depth Resolution Enhancement

Meyer, Danielle LEnergy Optimization of a Hybrid Unmanned Aerial Vehicle (UAV)
Master of Science, The Ohio State University, 2018, Electrical and Computer Engineering
Unmanned Aerial Vehicles (UAV) have continued to receive attention from corporations and governmental agencies due to their wide range of potential applications and hybrid nature. More Electric Aircraft (MEA) promise many benefits (e.g., reduced weight, decreased fuel consumption, and high reliability) and their development continues to be the trend. Hybrid UAVs are an ideal prototype to implement concepts of aircraft electrification due to their small size and the DC nature of their power systems. However, papers addressing the energy optimization UAV electric power systems fail to consider the importance of high accuracy and computational speed. This thesis proposes an energy optimization method to enhance the energy durability of a UAV through a novel approach integrating an optimization formulation and a detailed UAV simulation model, with physical circuitry characteristics. This approach allows for increased computation efficiency while still capturing physical system constraints experienced during real world flight, which are complex and highly nonlinear due to aerial, thermal, and electrical dynamics. Optimization formulations created within this work are based on dynamic programming and moving-horizon model predictive control (MPC). The efficacy of this method is proven on a realistic UAV system. Within the MPC formulation, various charge strategies are implemented and fuel consumption is calculated to provide insight into the trade-offs inherent within the UAV system, wherein battery discharging is required for high demand dash periods, but additional charge can only be supplied via increased output engine power. That is, minimal fuel consumption must be considered in light of the need for non-optimal output engine power to charge the battery such that a total mission can be completed. Algorithmic considerations regarding horizon size for MPC and algorithmic enhancements, considering random loads and renewable generation capacity on-board the UAV are presented. These results regarding enhanced algorithmic elements provide insight into the capability of the algorithm to function within a real-time environment and the benefit of solar arrays to provide additional generation. Using MPC as the optimization technique of choice allows for the development of an algorithm capable of handling both missions with a deterministic load and within online implementations, as deterministic cases represent a downsized problem where algorithmic considerations can be studied and iterated to reach satisfactory online implementation. While this thesis approaches the problem from the perspective of UAV design, i.e., optimization for a deterministic load profile, the algorithmic enhancements provided here represent initial steps towards online implementation.

Committee:

Jiankang Wang (Advisor); Mahesh Illindala (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Unmanned Aerial Vehicle; UAV; Optimization; Model Predictive Control; Algorithm; Modeling; Energy Management; Aerial Power System

Resor, Michael IrvinCOMPUTATIONAL INVESTIGATION OF ROTARY ENGINE HOMOGENEOUS CHARGE COMPRESSION IGNITION FEASIBILITY
Master of Science in Engineering (MSEgr), Wright State University, 2014, Mechanical Engineering
The Air Force Research Laboratory (AFRL) has been investigating the heavy fuel conversion of small scale Unmanned Aerial Vehicles (UAV). One particular platform is the Army Shadow 200, powered by a UEL Wankel rotary engine. The rotary engine historically is a proven multi-fuel capable engine when operating on spark ignition however, little research into advanced more efficient compression concepts have been investigated. A computational fluid dynamics model has been created to investigate the feasibility of a Homogeneous Charge Compression Ignition (HCCI) rotary engine. This research evaluates the effects, rotor radius to crankshaft eccentricity ratio, known as K factor, equivalence ratio, and engine speed and how they affect the response of horsepower, maximum temperature, and peak pressure to determine the feasibility of HCCI operation. The results show that the advanced HCCI strategy is promising to significantly improve efficiency of the rotary engine.

Committee:

George Huang, Ph.D. (Advisor); Haibo Dong, Ph.D. (Advisor); Greg Minkiewicz, Ph.D. (Committee Member); Scott Thomas, Ph.D. (Committee Member); Zifeng Yang, Ph.D. (Committee Member)

Subjects:

Aerospace Engineering; Automotive Engineering; Fluid Dynamics; Mechanical Engineering

Keywords:

Rotary Engine Wankel HCCI Homogeneous Charge Compression Ignition UAV Fluid Dynamics CFD

Tan, RuoyuTracking of Ground Mobile Targets by Quadrotor Unmanned Aerial Vehicles
MS, University of Cincinnati, 2013, Engineering and Applied Science: Mechanical Engineering
An Unmanned Air Vehicle (UAV) is an aircraft without a human pilot on board. It can be controlled either autonomously by computers onboard, or using a remote control by a pilot on the ground, or in another vehicle. In both military and civilian sectors, UAVs are quickly obtaining popularity and expected to expand dramatically in the years to come. As UAVs gain more attention, one of the immediate requirements would be to have UAVs work as much autonomously as possible. One of the common tasks that UAVs would be engaged in is target tracking which has various potential applications in military field, law-enforcement, wildlife protection effort, and so on. This thesis focuses on development of a controller for UAVs to track ground target. In particular, this thesis focuses on quadrotor UAV, which is a multicopter that is lifted and propelled using four motors. Admittedly, several target tracking control methods have been developed in recent years. However, only a few of them have been applied on a quadrotor. Most of these tracking methods, particularly those based on Proportional Derivative (PD) control laws, which have been applied on quadrotors, are not time efficient due to practical acceleration constraint and a number of parameters that need to be tuned. The UAV control problem can be divided into 4 sub-problems: Position Control, Motor Control, Trajectory Tracking and Trajectory Generation. In this thesis, the dynamic equations of motion for quadrotors and a Proportional Derivative control law is derived to solve the problems of Position Control, Motor Control and Trajectory Tracking. A Proportional Navigation (PN) based switching strategy is proposed to address the problem of Trajectory Generation. The experiments and numerical simulations are performed using non-maneuvering and maneuvering targets. The simulation results show that the proposed PN based switching strategy not only carries out effective tracking but also results into smaller oscillations and errors when compared to the widely used PD tracking method. The switching strategy, as proposed as a solution to target tracking problem, leaves an important question with regard to when should the switching happen. It is intuitive that the time of switching will play a role in how fast the UAV converges to the target. The second problem considered in this thesis relates to the optimal time of switching that would minimize the positional error between the UAV and the target. An optimal switching strategy is proposed to obtain the optimal switching time for both non-maneuvering and maneuvering targets. Analytical solutions that generate trajectories based on PN and PD methods are used in this strategy. The numerical simulations validate the optimality, reliability, and accuracy of the proposed method for both non-maneuvering and maneuvering targets.

Committee:

Manish Kumar, Ph.D. (Committee Chair); Kelly Cohen, Ph.D. (Committee Member); David Thompson, Ph.D. (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Unmanned Air Vehicle;quadrotor UAV;multicopter;Proportional Navigation;Trajectory Generation

Calhoun, Sean M.Six Degree-of-Freedom Modeling of an Uninhabited Aerial Vehicle
Master of Science (MS), Ohio University, 2006, Electrical Engineering & Computer Science (Engineering and Technology)

Developing a six degree-of-freedom (6-DOF) aircraft model has many practical purposes, especially in these times of rapidly growing Uninhabited Air Vehicle (UAV) technologies. This thesis covers some of the various topics involved in the development of such a model. The research performed was conducted at the Avionics Engineering Center, utilizing the Brumby R/C aircraft. Topics include a brief overview of the instrumentation system, techniques for inertia estimation, and system identification using the Ordinary Least Squares (OLS) method. Finally, the design and development of a Matlab/SIMULINK model will be covered, which will illustrate the accuracy and validity of the 6-DOF model.

Committee:

Douglas Lawrence (Advisor)

Subjects:

Engineering, Aerospace

Keywords:

UAV; Unmanned Vehicle; 6-DOF Model; System Identification; Brumby

Findler, Michael JamesCognitively Sensitive User Interface for Command and Control Applications
Doctor of Philosophy (PhD), Wright State University, 2011, Engineering PhD
While there are broad guidelines for display or user interface design, creating effective human-computer interfaces for complex, dynamic systems control is challenging. Ad hoc approaches which consider the human as an afterthought are limiting. This research proposed a systematic approach to human / computer interface design that focuses on both the semantic and syntactic aspects of display design in the context of human-in-the-loop supervisory control of intelligent, autonomous multi-agent simulated unmanned aerial vehicles (UAVs). A systematic way to understand what needs to be displayed, how it should be displayed, and how the integrated system needs to be assessed is outlined through a combination of concepts from naturalistic decision making, semiotic analysis, and situational awareness literature. A new sprocket-based design was designed and evaluated in this research. For the practical designer, this research developed a systematic, iterative design process: design using cognitive sensitive principles, test the new interface in a laboratory situation; bring in subject matter experts to examine the interface in isolation; and finally, incorporate the resulting feedback into a full-size simulation. At each one of these steps, the operator, the engineer and the designer reexamined the results.

Committee:

S. Narayanan, PhD (Committee Chair); Misty Blue-Terry, PhD (Committee Member); Mateen Rizki, PhD (Committee Member); Joseph Litko, PhD (Committee Member); Yan Liu, PhD (Committee Member)

Subjects:

Industrial Engineering

Keywords:

Unmanned aerial vehicles; UAV; Visual Thinking; Naturalistic Decision Making; Situation Awareness

Charvat, Robert C.Surveillance for Intelligent Emergency Response Robotic Aircraft (SIERRA Project)
MS, University of Cincinnati, 2012, Engineering and Applied Science: Aerospace Engineering

Unmanned Aerial Systems (UASs) have proven their potential in wartime environments by providing an alternative to manned technologies that risk human life. UASs are able to perform in situations that are dangerous or undesirable to humans. Also, UASs allow for miniaturization of technologies previously used for these tasks, which provides higher task performance at a lower cost. By combining miniaturized technology platforms with already existing technologies from the public domain, this technology has proved to be beneficial to emergency management operations.

Wildland fires are a source of concern to emergency management organizations and, as a natural occurrence, will continue to be concern in the future. As the world's population continues to grow, and people continue to spread into more rural environments, wildland fires are an increasing risk to life and infrastructure. For many locations, these risks can be managed with prevention programs and risk mitigation strategies. Such methods of prevention and mitigation include pre-existing fire lines and management of flammable materials near infrastructure. However, in many locations the primary form of risk reduction is a proper response to fires. As fire size tends to grows in an exponential manner with time, a quick response is essential to combating disaster. Rapid action requires significant surveillance to support situational awareness. Technology that can provide this situational awareness would be a significant advancement over current manned aerial platforms.

The Surveillance for Intelligent Emergency Response Robotic Aircraft (SIERRA) Project is aimed at partnering government, manufacturing, emergency response, and academic expertise to develop unmanned aerial systems for use in emergency management environments. The SIERRA Project focuses on three areas of this development: Potential application of this technology with current fire tactics at the operational level, current technology capabilities and systems engineering requirements for this type of system, and analysis of flight data of the Zephyr (a tactical UAS platform weighing less than 10 pounds). After this research is completed, it will allow for the introduction of research into the concept of a wildland fire agency air force. This allows wildland fire forces to have full fleet capability, which will revolutionize wildland fire response and the recommended requirements for the next generation of tactical UAS platforms.

Committee:

Kelly Cohen, PhD (Committee Chair); Eugene Rutz, MS (Committee Member); Manish Kumar, PhD (Committee Member); Gary Slater, PhD (Committee Member)

Subjects:

Aerospace Materials

Keywords:

SIERRA;UAS;Systems Engineering;Unmanned Aerial System;Drone;UAV;

Geyman, Matthew KennethWing/Wall Aerodynamic Interactions in Free Flying, Maneuvering MAVs
Master of Science (M.S.), University of Dayton, 2012, Aerospace Engineering
Micro Air Vehicles (MAVs) are small remotely piloted air vehicles that can be flown between or inside of buildings for military or surveillance purposes. This type of flight in the urban environment involves many aerodynamic hazards. The research in this thesis investigates how the aerodynamic interactions between a maneuvering MAV’s wingtip vortex and its distance away from a building wall could affect the MAV’s flight controls. Free flight particle image velocimetry (PIV) testing and wind tunnel testing are used to investigate the aerodynamic interactions between a MAV wingtip vortex and a wall. Elliptical instabilities and a vortex rebound off of the wall are discovered in the PIV testing while the wind tunnel results show a higher aircraft coefficient of lift near the wall. All of these results force the aircraft to experience a rolling motion while flying along a wall. It is imperative that a MAV anticipate this motion and adjust its flight controls in order to accurately fly along a wall and successfully complete its mission in an urban environment.

Committee:

Aaron Altman, PhD (Committee Chair); Gregory Parker, PhD (Committee Member); Markus Rumpfkeil, PhD (Committee Member)

Subjects:

Aerospace Engineering

Keywords:

MAV; UAV; aerodynamics; wall effect; wingtip vortex; PIV; wind tunnel; micro air vehicle; vicon

Belzer, Jessica A.Unmanned Aircraft Systems in the National Airspace System: Establishing Equivalency in Safety and Training Through a Fault Tree Analysis Approach
Master of Science (MS), Ohio University, 2017, Electrical Engineering & Computer Science (Engineering and Technology)
With approval of UAS for civilian use in the National Airspace System, comes the need for formal integration. Manned and unmanned aircraft will share the same volumes of airspace, for which the safety standards must be upheld. Under manned aircraft operations, certain implicit assumptions exist that must be made explicit and translatable to the unmanned aircraft context. A formal system safety assessment approach through a fault tree analysis was used to identify assumptions contingent on a pilot’s presence inside the fuselage and areas of weakness in operational equivalency of UAS. The UAS fault tree framework developed is applicable to unmanned aircraft systems of different sizes and complexity, while maintaining a semblance to the framework accepted within the manned aircraft community. In addition, a database of UAS incidents and accidents occurring internationally 2001-2016 was developed from published materials and databases of various sources. Database events were categorized according to the UAS Fault Tree Framework Level 1 Subsystems, the International Civil Aviation Organization (ICAO) Aviation Occurrence Categories, and the Human Factors Analysis and Classification System (HFACS). ICAO Aviation Occurrence Category specific fault trees were constructed for the three most commonly occurring categories in the database results. Significant sources of risk for UAS operations lie in Aircraft/System and Flight Crew/Human Factors failures. Commonly occurring Occurrence Categories in the results of the UAS database were different than those identified for fatal accidents occurring in manned commercial aviation operations. Increased system reliability and standardization is needed to ensure equivalent levels of safety for UAS operations in the NAS. Additionally, needs of UAS pilots are different than those for manned and model aircraft. Training requirements must be approached independently and formally evaluated for their effectiveness in risk mitigation.

Committee:

Frank van Graas, Ph.D. (Advisor); Maarten Uijt de Haag, Ph.D. (Committee Member); Jeffrey Dill, Ph.D. (Committee Member); Robert Stewart, Ph.D. (Committee Member)

Subjects:

Engineering

Keywords:

Fault Tree Analysis; UAS; UAV; Unmanned Aircraft System; FTA; System Safety Assessment; SSA; sUAS;

Mohan, Arvind ThanamData-Driven Analysis Methodologies for Unsteady Aerodynamics from High Fidelity Simulations
Doctor of Philosophy, The Ohio State University, 2017, Aero/Astro Engineering
Numerical methods and computational approaches for studying fluid flow have become increasingly popular and more mature in their capabilities since the 1960s, when the prohibitive experimental costs associated with flight vehicle development programs necessitated an alternative approach. Computational Fluid Dynamics (CFD) approaches for several practical applications were pioneered in the early 1980s, but despite the algorithmic advances the computing power necessary to compute full three-dimensional flow-fields remained a bottleneck. With the advent of powerful microprocessors and high performance supercomputers, high fidelity three-dimensional CFD for cases of practical interest have become feasible over the last couple of decades. Although these high fidelity simulations contain the desired physics, extracting that information is proving to be a challenge due to their extremely large size. For instance, a 3D Direct Numerical Simulation (DNS) or Large Eddy Simulation (LES) of an airfoil can produce terabytes of data. For such large datasets, it becomes difficult to use conventional analysis and visualization techniques without resorting to statistical methods more suited to such ``big data" problems. There are several such methods, each of which usually places emphasis on a certain aspect of the dataset. However, these can be used in conjunction with each other to complement each other to generate a comprehensive understanding of the fundamental physical mechanisms prevalent in a flow-field. The central goal of this dissertation is to develop strategies based on novel statistical, model reduction and signal processing techniques to derive such physical insights into large CFD datasets of practical interest. To demonstrate this, three high fidelity LES datasets of various unsteady flow-fields arising in Micro Air Vehicle (MAV) flight have been analyzed in depth. They are a) Static stall of a NACA 0015 airfoil with plasma control, b) Dynamic stall in a plunging SD 7003 airfoil, and c) Interaction of a stream-wise oriented vortex impinging on a rectangular wing, which is a canonical problem in the aerodynamics of formation flight. First, model reduction as an effective means to study complex, realistic flows is investigated. The recently popularized model reduction technique, Dynamic Mode Decomposition (DMD) has been given special emphasis in addition to the well known Proper Orthogonal Decomposition (POD), to study the three cases mentioned above. In the NACA 0015 static stall case, DMD analysis reveals a strong instability in the flow-field at a Strouhal number St = 2. Subsequent actuation with a Nano-Second Pulse Dielectric Barrier Discharge (NS-DBD) plasma actuator at this frequency is found to mitigate stall, indicating the effectiveness of DMD analysis in estimating actuation parameters for flow control a priori. The potential of DMD in understanding the physics of a turbulent flow-field is then further explored using the SD 7003 airfoil dynamic stall case. DMD shows that the large scale energetic structures in the leading edge vortex oscillate with a frequency equal to that of the airfoil plunging frequency, with several harmonics. Additionally, the relationship between DMD and POD modes are also studied, showing how key similarities among these different techniques can be leveraged to form a more perceptive understanding of the physics. Apart from model reduction for physics extraction, a major emphasis of this work has been on analysis of non-stationary signals arising from turbulent flows. Despite Fast Fourier Transform (FFT) and DMD being effective tools to study local and global periodic features in the flow, the inherently non-stationary nature of turbulence in several applications pose significant limitations to their reliable usage. Thus, such datasets require special treatment to account for their non-stationary behavior, with reduced approximation errors. One such technique that has been explored in this work is the Empirical Mode Decomposition (EMD). EMD was initially popularized in the earth sciences community to study intermittent features and trends in highly non-stationary signals. The effectiveness of EMD in fluid mechanics is demonstrated by analyzing the case of a stream-wise oriented vortex impinging on a rectangular wing, where EMD extracts the prominent surface pressure signatures from temporal signals of the impinging vortex. Furthermore, it is shown that these results can be used in conjunction with DMD, such that key local frequencies identified by EMD guide DMD to extract their global surface pressure footprint on the airfoil surface. Some more recent works in literature have also pointed to the utility of EMD in analyzing non-stationary data in turbulence, and its adoption is likely to increase in the research community. Although EMD proves to be a useful solution for feature extraction from non-stationary signals, it has some significant practical limitations. A crucial impediment is that EMD in its basic form can be applied only for univariate/single-channel data. For multivariate signals, the algorithm cannot easily extract common patterns and features in the different channels, due to theoretical constraints in its mathematical formulation. This is a significant deficiency in fluid mechanics since signals from several sources, in both experiment and CFD, are often used to study the flow, intrinsically making it a multivariate dataset. Case-specific bivariate and trivariate analysis for turbulence have not shown much promise. To address this need, a generalized n-variate treatment, Multivariate EMD (MEMD) is adopted as a potential solution in this work. MEMD is a very recent development which has been primarily used in the neuroscience community to analyze multichannel data. Its application in turbulence has been demonstrated in this work by using it to study the inception (or onset) of dynamic stall in the SD 7003 case mentioned above. The stall inception data exhibits a very high degree of non-stationarity across time and space. Since MEMD, unlike EMD, successfully extracts intermittent features/oscillations among the multivariate signals, it is able to uncover several new dynamics of the flow which were previously elusive. Finally, this work also extends its focus to the spectral analysis of non-stationary signals. Although the Fast Fourier Transform (FFT) has been widely used to study spectra in turbulent datasets, they tend to be deficient in generating the spectra for non-stationary signals where the frequency/wavenumber often varies. This is because these methods can reliably extract only periodic features in the signal, while the other features tend to be missed. Wavelet analysis is a very popular and time-tested alternative mathematically well suited to compute transient spectra for non-stationary signals, and is widely used in different domains of science and engineering. However, they require a user defined parameter known as the mother wavelet, the choice of which significantly impacts their effectiveness. Often, careful selection of the mother wavelet requires some a priori insight into the signal. This can be a problematic, especially during exploratory data analysis of turbulent flows. As a potential solution, this work proposes that the algorithm of Matching Pursuits (MP), which has been typically used in biomedical sciences for spectral analysis and sensor fusion, to compute spectra. MP needs minimal user guidance for this purpose, and is therefore very robust and repeatable. The application of MP to analyze spectra during the inception of stall demonstrates excellent performance. Furthermore, the stall inception case has been used to show that MEMD and MP can be used in tandem to track and analyze disturbances in the flow. The results indicate that inception of dynamic stall may be a two-stage process, with the spatio-temporal movement of various flow structures dictating the dynamics of each stage. Therefore, this approach provides a general framework to study other problems in fluid mechanics where rapidly evolving flow features may need to be tracked.

Committee:

Datta Gaitonde (Advisor); Jen Ping-Chen (Committee Member); Sandip Mazumder (Committee Member); Mei Zhuang (Committee Member)

Subjects:

Aerospace Engineering

Keywords:

CFD; aerodynamics; turbulence; DMD; EMD; Multivariate EMD; Matching Pursuits; Statistics; Wavelets; MAV; UAV

McCrink, Matthew HDevelopment of Flight-Test Performance Estimation Techniques for Small Unmanned Aerial Systems
Doctor of Philosophy, The Ohio State University, 2015, Aero/Astro Engineering
This dissertation provides a flight-testing framework for assessing the performance of fixed-wing, small-scale unmanned aerial systems (sUAS) by leveraging sub-system models of components unique to these vehicles. The development of the sub-system models, and their links to broader impacts on sUAS performance, is the key contribution of this work. The sub-system modeling and analysis focuses on the vehicle’s propulsion, navigation and guidance, and airframe components. Quantification of the uncertainty in the vehicle’s power available and control states is essential for assessing the validity of both the methods and results obtained from flight-tests. Therefore, detailed propulsion and navigation system analyses are presented to validate the flight testing methodology. Propulsion system analysis required the development of an analytic model of the propeller in order to predict the power available over a range of flight conditions. The model is based on the blade element momentum (BEM) method. Additional corrections are added to the basic model in order to capture the Reynolds-dependent scale effects unique to sUAS. The model was experimentally validated using a ground based testing apparatus. The BEM predictions and experimental analysis allow for a parameterized model relating the electrical power, measurable during flight, to the power available required for vehicle performance analysis. Navigation system details are presented with a specific focus on the sensors used for state estimation, and the resulting uncertainty in vehicle state. Uncertainty quantification is provided by detailed calibration techniques validated using quasi-static and hardware-in-the-loop (HIL) ground based testing. The HIL methods introduced use a soft real-time flight simulator to provide inertial quality data for assessing overall system performance. Using this tool, the uncertainty in vehicle state estimation based on a range of sensors, and vehicle operational environments is presented. The propulsion and navigation system models are used to evaluate flight-testing methods for evaluating fixed-wing sUAS performance. A brief airframe analysis is presented to provide a foundation for assessing the efficacy of the flight-test methods. The flight-testing presented in this work is focused on validating the aircraft drag polar, zero-lift drag coefficient, and span efficiency factor. Three methods are detailed and evaluated for estimating these design parameters. Specific focus is placed on the influence of propulsion and navigation system uncertainty on the resulting performance data. Performance estimates are used in conjunction with the propulsion model to estimate the impact sensor and measurement uncertainty on the endurance and range of a fixed-wing sUAS. Endurance and range results for a simplistic power available model are compared to the Reynolds-dependent model presented in this work. Additional parameter sensitivity analysis related to state estimation uncertainties encountered in flight-testing are presented. Results from these analyses indicate that the sub-system models introduced in this work are of first-order importance, on the order of 5-10% change in range and endurance, in assessing the performance of a fixed-wing sUAS.

Committee:

James W. Gregory (Advisor); Charles Toth (Committee Member); Cliff Whitfield (Committee Member); Jeffery P. Bons (Committee Member)

Subjects:

Aerospace Engineering

Keywords:

UAS, UAV, Propulsion systems, aircraft design, inertial navigation, Kalman filter, sensor calibration, flight testing, HIL

Fuller, Ryan MichaelAdaptive Noise Reduction Techniques for Airborne Acoustic Sensors
Master of Science in Engineering (MSEgr), Wright State University, 2012, Electrical Engineering
Ground and marine based acoustic arrays are currently employed in a variety of military and civilian applications for the purpose of locating and identifying sources of interest. An airborne acoustic array could perform an identical role, while providing the ability to cover a larger area and pursue a target. In order to implement such a system, steps must be taken to attenuate environmental noise that interferes with the signal of interest. In this thesis, we discuss the noise sources present in an airborne environment, present currently available methods for mitigation of these sources, and propose the use of adaptive noise cancellation techniques for removal of unwanted wind and engine noise. The least mean squares, affine projection, and extended recursive least squares algorithms are tested on recordings made aboard an airplane in-flight, and the results are presented. The algorithms provide upwards of 37dB of noise cancellation, and are able to filter the noise from a chirp with a signal to noise ratio of -20db with minimal mean square error. The experiment demonstrates that adaptive noise cancellation techniques are an effective method of suppressing unwanted acoustic noise in an airborne environment, but due to the complexity of the environment more sophisticated algorithms may be warranted.

Committee:

Brian Rigling, PhD (Committee Chair); Kefu Xue, PhD (Committee Member); Fred Garber, PhD (Committee Member)

Subjects:

Acoustics; Aerospace Engineering; Applied Mathematics; Electrical Engineering; Engineering; Remote Sensing

Keywords:

Adaptive Noise Cancellation; Adaptive Algorithms; Acoustic Sensors; Acoustic Eavesdropping; UAV; Unmanned Aerial Vehicle; Active Noise Reduction; Remote Sensing; Signal Processing; Acoustics

Sabo, ChelseaUAV Two-Dimensional Path Planning In Real-Time Using Fuzzy Logic
MS, University of Cincinnati, 2011, Engineering and Applied Science: Aerospace Engineering
There are a variety of scenarios in which the mission objectives rely on a UAV being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. In these situations, not only can these obstacles be dynamic, but sometimes there is no way to plan ahead of the mission to avoid them. Additionally, there are many situations in which it is desirable to send in an exploratory robot where the environment is dangerous/ contaminated and there is a great deal of uncertainty. These scenarios could either be too risky to send people or not available to humans. With an appropriate dynamic motion planning algorithm in these situations, robots or UAVs would be able to maneuver in any unknown and/or dynamic environment towards a target in real-time. An autonomous system that can handle these varying conditions rapidly and efficiently without failure is imperative to the future of unmanned aerial vehicle (UAV). This paper presents a methodology for two-dimensional path planning of a UAV using fuzzy logic. This approach is selected due to its ability to emulate human decision making and relative ease of implementation. The fuzzy inference system takes information in real time about obstacles (if within the agent’s sensing range) and target location and outputs a change in heading angle and speed. The FL controller was validated for both simple (polygon obstacles in a sparse space) and complex environments (i.e. non-polygon obstacles, symmetrical/concave obstacles, dense environments, etc). Additionally, Monte Carlo testing was completed to evaluate the performance of the control method. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the Fuzzy Logic Controller (FLC) feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an Artificial Potential Field (APF) solution, a commonly used intelligent control method, had an average of 18% failure rate. Also, the APF method failed about 1/3 of the time for very dense environments (the FLC only had 5% failure rate). These results highlighted one of the advantages of the FLC method: its adaptability to additional rules while maintaining low control effort. Furthermore, the solutions showed superior results when compared to the APF solutions when compared to distance traversed. Overall, the FLC produced solutions that were on average only about 7.7% greater distance traveled (as opposed to 9.7% for the APF).

Committee:

Kelly Cohen, PhD (Committee Chair); Shaaban Abdallah, PhD (Committee Member); Manish Kumar, PhD (Committee Member)

Subjects:

Aerospace Materials

Keywords:

UAV;Path Planning;Fuzzy Logic;Online;Real-Time;Motion Planning

Bharadwaj, Akshay S.A Perception Payload for Small-UAS Navigation in Structured Environments
Master of Science (MS), Ohio University, Electrical Engineering & Computer Science (Engineering and Technology)
Unmanned Aircraft System (UAS) are proving to be increasingly favorable in military and commercial applications. The range of applications include surveillance, aerial photography, environmental observations, search and rescue, mapping, forestry, agricultural survey, law enforcement among many. The small size unmanned multi-copters are highly capable and cost effective for low altitude operations and have extended access to dangerous and hazardous environments which were previously unavailable. Irrespective of the applications, a position and navigation solution are necessary to fly the UAS completely autonomous or even to manually control it easily. The Global Navigation Satellite System (GNSS) has become one of the most dependable solution for position and navigation outdoors but does not perform well in the indoor environment as the signal is obstructed by the roof and the walls. Hence, there is a need for non-Global Positioning System (GPS) position and navigation solution methods for indoors. Simultaneous Localization and Mapping (SLAM) and feature-based integrated navigation are two methods that can be used for this purpose, using various types of sensors like ranging sensors, cameras, and Inertial Measurement Unit (IMU). This thesis will focus on integrating depth imagery, Short Wave Infrared (SWIR) imagery and Long Wave Infrared (LWIR) imagery with an IMU to obtain and estimate of both the position and the map of the environment. In this discussion, the region of operation is restricted to structured environments and would be extended to unstructured environments in the future. This work will include preliminary flight test results from a small-size Blackout quadcopter operated in a structured indoor environment for maintenance purposes. The quadcopter has been equipped with a 3DR Pixhawk flight controller and an Odroid XU4 onboard computer running Ubuntu. The Robotics Operating System (ROS) is used to interface with and integrate all the sensors and control the flight controller. The optical sensors include a forward-pointing Occipital providing both SWIR imagery and depth information, and a Lepton LWIR camera to pick up heat signature image of objects in the environment. The latter is connected to the Odroid via a Serial Peripheral Interface (SPI).

Committee:

Maarten Uijt de Haag (Advisor); Frank Van Graas (Committee Member); Jim Zhu (Committee Member); Martin J Mohlenkamp (Committee Member)

Subjects:

Electrical Engineering

Keywords:

UAS; SLAM; point cloud segmentation; thermal imagery for navigation; fast planar feature extraction; vision sensor stack for UAV

Brezina, Aron JonMeasurement of Static and Dynamic Performance Characteristics of Electric Propulsion Systems
Master of Science in Engineering (MSEgr), Wright State University, 2012, Mechanical Engineering
Today's unmanned aerial vehicles are being utilized by numerous groups around the world for various missions. Most of the smaller vehicles that have been developed use commercially-off-the-shelf parts, and little information about the performance characteristics of the propulsion systems is available in the archival literature. In light of this, the aim of the present research was to determine the performance of various small-scale propellers in the 4.0 to 6.0 inch diameter range driven by an electric motor. An experimental test stand was designed and constructed in which the propeller/electric motor was mounted in a wind tunnel for both static and dynamic testing. Both static and dynamic results from the present experiment were compared to those from previous studies. For static testing, the coefficient of thrust, the coefficient of propeller power, and the overall efficiency, defined as the ratio of the propeller output power to the electrical input power, were plotted versus the propeller rotational speed. For dynamic testing, the rotational speed of the propeller was held constant at regular intervals while the freestream airspeed was increased from zero to the windmill state. The coefficient of thrust, the coefficient of power, the propeller efficiency and the overall efficiency were plotted versus the advance ratio for various rotational speeds. The thrust and torque were found to increase with rotational speed, propeller pitch and diameter, and decrease with airspeed. Using the present data and data from the archival and non-archival sources, it was found that the coefficient of thrust increases with propeller diameter for square propellers where D = P. The coefficient of thrust for a family of propellers (same manufacturer and application) was found to have a good correlation from static conditions to the windmill state. While the propeller efficiency was well correlated for this family of propellers, the goodness of fit parameter was improved by modifying the propeller efficiency with D/P.  

Committee:

Scott K. Thomas, PhD (Committee Chair); Haibo Dong, PhD (Committee Member); Zifeng Yang, PhD (Committee Member); Mitch Wolff, PhD (Committee Member)

Subjects:

Aerospace Engineering; Engineering; Mechanical Engineering

Keywords:

Propeller; Small Unmanned Aerial Vehicle; UAV; Electric Propulsion System; Advance Ratio; Low Reynolds Number; Wind Tunnel Testing

Kresge, Jared T.Telerobotic System Design for a Remotely Operated Lightweight Park Flyer Mirco Aerial Vehicle
Master of Science (MS), Ohio University, 2006, Electrical Engineering & Computer Science (Engineering and Technology)

The development of unmanned aerial vehicles (UAV) has recently become a popular topic at research institutions. These new UAV designs tend to create smaller, lighter, and application specific vehicles. This thesis describes the design of a telerobotically controlled UAV system and the development of hardware and software for an instrumentation system to be used on a lightweight radio controlled (R/C) park flyer aircraft. This requires that the instrumentation system meet the size and weight constraints as well as measure the dynamics of the aircraft using a set of minimal sensors with limited processing capabilities.

Committee:

Frank van Graas (Advisor)

Keywords:

UAV; MAV; Instrumentation; Aircraft Control; Aircraft Modeling; Flight Testing

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