Engineering Commons^™

Homotopy-Safe Trajectory Planning And Attack Detection For Low-Altitude Uav Under False Map Information Injection Attacks, Chen Li, Qi, Juntao Zhao, Xin Yuan, Kai Wu, Wei Ni, Ren Ping Liu

Research outputs 2022 to 2026

Low-altitude unmanned aerial vehicles (UAVs) have been extensively deployed in logistics support, surveillance, and disaster relief. However, their open communication networks and inherently vulnerable navigation systems render them susceptible to false map information injection attacks (FMIIA). To effectively mitigate the impact of FMIIA, this paper presents a UAV local flight trajectory optimization framework that integrates a robust attack detection method based on initial excitation (IE) and an efficient local path reconstruction approach utilizing the Marden theorem. First, an IE-based adaptive robust observer is formulated, where IE enhances the observability of the system's input-output responses, enabling joint estimation of the UAV's …

Color-Coding: An Aid Or Hindrance In A Multi-Unmanned Aerial Vehicle Supervisory Control Task, Austin Daniel Wood

Theses and Dissertations

The purpose of the current study was to investigate the effect of coding types (i.e., alphanumeric coding, color-coding, and redundant color + alphanumeric coding) for vehicle identification and status information on pilots’ recognition performance, situational awareness (SA), and workload for a multi-vehicle operations ground control station (GCS) supervisory control task. With the aviation industry's push towards operators supervising and controlling multiple vehicles, it is pertinent to identify design features that support the capabilities and limitations of human operators. The current study employed a within-subjects, repeated-measures experimental design, in which a sample of 33 students with aviation experience performed three trials, …

Robust Real-Time Uav Target Tracking With Onboard Vision-Based Yaw Control, Rylan Malarchick, Jose Castelblanco, Enrique Amaya, Carmen Dimario, Graysen Brinkman, Chirag Kumar, Kiwon Yoon, Sajid Berhane

Beyond: Undergraduate Research Journal

Autonomous tracking of agile unmanned aerial vehicles (UAVs) presents significant challenges for real-time perception and control systems. This work presents AIRHOUND (Autonomous Intelligent Rotorcraft for Hostile Object Unified Navigation and Detection), a UAV platform implementing vision-based yaw tracking through a modular ROS2 software architecture. The system employs YOLOv8 object detection optimized with NVIDIA TensorRT for embedded deployment on an NVIDIA Jetson Orin companion computer. Detected targets are processed through a geometric tracking module that converts pixel coordinates to angular yaw errors using pinhole camera intrinsics, with a proportional controller generating rate-limited yaw commands. These commands are streamed to a PX4 …

Uav Trio Formations For Aerial Pest Deterrence With Vision-Based Bird Monitoring, Benjamin Andrew Ly, Chris Kwon, Christian Joseph Macaranas

Electrical Engineering

No abstract provided.

Designing A Collaborative Uav-Ugv System For Autonomous Challenge Completion, Ember Reysen

Honors Theses

The coordination between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) holds significant potential for completing complex tasks such as disaster response and construction surveillance by leveraging the strengths of aerial flight and stable on-ground transportation. Unfortunately, coordination between UAVs and UGVs is extremely complex and task-dependent, leading to limited understanding of autonomous collaboration. This thesis explores the process of designing an UAV-UGV collaborative system capable of aerially scouting a target destination, relaying its coordinates to a ground vehicle, and performing a precision landing for unison travel. I utilize computer vision techniques via OpenCV for target marker identification, ROS …

Multimodal Aerial Image-Based Ground Object Detection And Classification Using Yolo, Erik Nielsen

All Theses

Object detection in unmanned aerial vehicles (UAVs) present a unique challenge due to small object sizes, varying viewpoints, and changing environmental conditions. These challenges are exacerbated when operating during daytime and nighttime scenarios where illumination differences can heavily impact detection performance. This work is motivated by military object detection applications where the ability to reliably identify small objects such as landmines or unexploded ordnance from aerial imagery presents a critical safety need and a significant technical challenge. In this paper, we investigate object detection using both visible (RGB) and infrared (IR) imagery to improve robustness and reliability across diverse operating …

Uav Blast Load Characterization For Structural Design, Jalee Grace Spain

Civil Engineering Undergraduate Honors Theses

As the use of drones, or UAVs, increases, so does the risk of collision with infrastructure. When drones collide with a building, an impact or blast load is applied. Using current literature and structural analysis, a load case can be defined for a blast load induced by a drone.

Uav-Based Sensor Integration For In-Situ Lake Water Quality Monitoring, Alec R. Campbell

Biological and Agricultural Engineering Undergraduate Honors Theses

Surface water monitoring is often constrained by limited spatial and temporal coverage due to the labor-intensive nature of traditional sampling methods, particularly in environments that are difficult to access or pose safety risks. Unmanned aerial vehicles (UAVs) offer a promising solution by enabling more frequent, spatially distributed, and cost-effective data collection. This study presented the design, development, and field evaluation of a UAV-based system for real-time, in-situ water quality monitoring. The system integrated multiple sensors, including oxidation-reduction potential (ORP), RGB spectrometry, pH, electrical conductivity (EC), dissolved oxygen (DO), and a multispectral spectrometer within a UAV platform.

Field testing was conducted …

The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien

Makara Journal of Technology

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two …

Evaluating Uav Visual-Inertial Odometry Trajectory Error And Feature-Level Metrics Over Repetitive Floor Patterns, Anass El Mekkoussi

Doctoral Dissertations and Master's Theses

Visual-Inertial Odometry (VIO) is a widely used state estimation technique for Uncrewed Aerial Vehicle (UAV) navigation in environments where Global Navigation Satellite System (GNSS) signals are unavailable. VIO systems that rely on visual feature tracking are susceptible to performance degradation when operating over surfaces containing repetitive visual textures, where visually similar features can produce ambiguous correspondences that introduce errors into the trajectory estimate. Despite the prevalence of repetitive textures in indoor UAV operating environments such as warehouses, manufacturing facilities, and infrastructure corridors, the specific impact of different repetitive pattern geometries on per-surface VIO accuracy has received limited systematic study, and …

Research On Uav Path Planning Method Based On Collision Free Trajectory, Jun Xie, Qi Zhang, Yanyun Peng, Haonan Shi, Dongyang Li, Xi Liu

Journal of System Simulation

Abstract: In view of the problems of poor quality, long time consumption, and low efficiency of the autonomous path planning method for unmanned aerial vehicles, a path planning method for unmanned aerial vehicles based on a collision-free trajectory was proposed. Under the premise of uncertainty, the time-related virtual points and collision threshold were set; the obstacle was modeled as a rectangle; the interest points around the rectangle were defined. The uncertainty optimization model between the unmanned aerial vehicles and the obstacle was established, so as to obtain the allowable edge of the collision-free trajectory of the unmanned aerial vehicles. The …

Comparative Assessment Of Uav-Based Tseb And Field-Calibrated Aquacrop For Evapotranspiration On The Arid Coast Of Peru, Roxana Peña-Amaro, José Huanuqueño-Murillo, Lia Ramos-Fernández, Abel Ramos-Ayala, David Quispe-Tito, Lena Cruz-Villacorta, Elizabeth Heros-Aguilar, Edwin Pino-Vargas, Alfonso Torres-Rua

Civil and Environmental Engineering Faculty Publications

Precise estimation of evapotranspiration (ET) is essential for sustainable water management in arid agroecosystems, particularly for high-water-demand crops such as rice. This study integrated very-high-resolution UAV thermal–multispectral imagery with a Two-Source Energy Balance model (UAV–TSEB) and a field-calibrated AquaCrop model to quantify daily ET and its components under continuous flooding on the arid Peruvian coast during the 2024–2025 season. A network of 24 drainage lysimeters provided an independent observational benchmark (ET_lys); to represent the treatment-level response, lysimeter observations were aggregated as the mean across the 24 units for each UAV campaign. Thirteen UAV surveys supplied radiometric surface temperature …

Dynamic Thrust Testbed For Uav Electric Motors, Colin M. Flowers, Robert C. Johnson Jr., Carson P. Holt

Williams Honors College, Honors Research Projects

This project seeks to bring new testing capability to the Zips Aero Design Team through the design, manufacture, integration, and testing of a dynamic thrust testbed for UAV electric motors. The project centers upon the revival and modification of a past prototype aircraft for use as a testbed for in-flight thrust measuring and recording. The team currently lacks the ability to test dynamic thrust under the operating conditions and flight speeds that are encountered in competition. Project technical areas include component and product design, electrical and electronics, and fluid mechanics, including the use of SolidWorks, MATLAB, and ArduPilot. Aside from …

The Development Of A Convenient And Consistent Methodology For Flight Proficiency To Certify Multi-Rotor Uas Pilots For State Departments Of Transportation, Colin H. Dees, Joseph M. Burgett

The Professional Constructor

To fly an unmanned aircraft system (UAS), commonly referred to as a “drone,” the Federal Aviation Administration (FAA) requires pilots to pass a knowledge test. There is no requirement at the state or federal level for drone operators to demonstrate the ability to operate a UAS. The National Institute of Science and Technology (NIST) has created an exam for public and private entities to assess basic UAS flight proficiency. It is the only nationally recognized flight proficiency protocol. NIST does not provide a scoring recommendation and leaves it to the user to determine the minimum criteria to pass. There is …

Control Strategies For 6-Dof Quadcopter Uavs: Cascade Pid Stabilization In White Noise Conditions, An Vo Van, Hung Ha Duy

Makara Journal of Technology

In this study, a cascade PID control structure is proposed and implemented for a 6-degree-of-freedom (6-DOF) unmanned aerial vehicle (UAV) to enhance stability and trajectory tracking capabilities under both noise and non-noise conditions. The controller was designed based on the Tyreus–Luyben tuning method and was evaluated using quantitative metrics, including rise time, settling time, overshoot, and steady-state error. Simulation results on MATLAB/Simulink show that the controller achieves high performance in angular channels (ϕ, θ, ψ) and altitude (z) with a short rise time (< 2s), slight overshoot (< 1%), and nearly eliminated steady-state error. However, the horizontal position channels (x, y) have a longer settling time (~110s) and are sensitive to white noise. Quantitative comparisons with other control methods show that the cascade PID outperforms the standard PID in terms of accuracy and stability, achieving a performance comparable to LQR under noise-free conditions, but is less robust in the presence of noise than advanced methods like SMC and MPC. These results confirm the feasibility of cascade PID in UAV applications and indicate potential future improvements by integrating nonlinear, adaptive, or intelligent control strategies.

Improved Pid Search Algorithm For Uav Path Planning In Mountainous Environments, Yi Peng, Yunkui Lei, Qingqing Yang, Hui Li, Jianming Wang

Journal of System Simulation

Abstract: To address the challenges of UAV path planning in mountainous environments, including high computational complexity and suboptimal optimization performance, and the disadvantages of the PIDbased search algorithm, such as low optimization accuracy and slow convergence rate, this paper proposed an improved PID search algorithm (IPSA). The method introduced a good point set to ensure a more uniform population distribution, thereby enhancing population diversity and global search capability. The Q-learning algorithm was employed to adapt PID parameter adjustments, incorporating an exploration rate factor to further improve the algorithm's exploration and computational capabilities. A lens imaging opposition-based learning mechanism was also …

Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …

Path Planning Of Improved Rrt Algorithm Based On Deep Reinforcement Learning, Xiuman Liang, Ziliang Liu, Zhendong Liu

Journal of System Simulation

Abstract: To address the low planning efficiency, poor safety, and limited practicability of the RRT algorithm in global path planning within complex three-dimensional environments, which fail to meet the requirements of planning the safe flight path of UAVs, an improved SAC-RRT algorithm was proposed, which fused SAC deep reinforcement learning algorithm and RRT algorithm. A target point bias strategy and a dynamic step size based on the SAC decision-making network were designed to reduce the blindness of RRT. A random point correction process was designed to optimize the position of random points based on actions from the decision network and …

Autonomous Landing Of An Unmanned Aerial Vehicle On An Unmanned Surface Vessel Using Model Predictive Control With An Adaptive-Covariance Extended Kalman Filter, Jorge Estupinan

Doctoral Dissertations and Master's Theses

This thesis presents the development of vision-based estimation and model predictive control (MPC) strategies to enable an Unmanned Aerial Vehicle (UAV) to land autonomously on an Unmanned Surface Vessel (USV) subjected to wave-induced motion. An innovative Adaptive-Covariance Extended Kalman Filter (AEKF) implementation was developed for the estimation of the 6 degree-of-freedom USV states using GPS and vision-based measurements of AprilTag markers on the USV landing platform. The AEKF employs an uncontrolled 6 degree-of-freedom nonlinear model augmented with second-order harmonic wave-induced motion dynamics. The AEKF implements two correction techniques: an adaptive covariance adjustment and an artificial covariance inflation regulated by a …

Partially Supervised Reinforcement Learning For Gps-Denied Navigation, Ethan Weilheimer

McKelvey School of Engineering Graduate Student Theses & Dissertations

Navigating dynamic environments is a key challenge for autonomous agents, yet most existing research focuses on 3D settings or settings where the agent has full access to relevant semantics. In this work, we propose a learning framework for aerial navigation in the presence of changing dynamics and limited positional information. Specifically, we consider a drone navigation task where a drone at one time has access to GPS location information, which it has now lost and needs to navigate in the same area but at a future time with no GPS signal and differing transition dynamics. To address this, we introduce …

G.W.A.I.H.I.R. Guided Wing Aircraft For Intelligent Hybrid Insertion And Recovery, Abdirahman Ahmed Shirwa, Zach Richards, Derek Harwood, Alex Duncan

Senior Design Project For Engineers

The paper outlines the conceptual and preliminary design of a hybrid vertical takeoff and landing (VTOL) heavy lift unmanned aerial vehicle (UAV) for autonomous cargo transport missions. The primary design objective was to create an aircraft capable of carrying a 15 kg payload over a range of 33 km, achieving a top cruise speed of 45 km/h and maintaining an endurance capacity of at least 90 minutes.

A comprehensive literature review informed key design decision, including airfoil selection, structural material, propulsion system configuration, and control. Key requirements were established early in the design process, such as payload capacity, energy efficiency, …

Uav Path Planning Based On Improved Deep Deterministic Policy Gradients, Sen Zhang, Qiangqiang Dai

Journal of System Simulation

Abstract: Aiming at the problems of poor convergence and invalid exploration when UAVs perform path planning in complex environments, an improved deep deterministic policy gradient(DDPG) algorithm is proposed. Using a dual experience pooling mechanism to store success and failure experiences separately, the algorithm is able to use the success experience to strengthen the strategy optimization and learn from the failure experience to avoid the wrong path; an APF method is introduced to add a bootstrap term to the planning, which is combined with the exploration of noisy actions in a randomized sampling process to dynamically integrate the selected actions; multi-objective …

Parallel Task Transmission And Processing Optimization Scheme For Uav-Assisted Internet Of Vehicles, Chao Yang, Ruiqun Zheng, Zhen Li, Hongwei Zhang, Yanqun Tang, Dongze Li

Journal of System Simulation

Abstract: To address the increasing of computation demands of internet of vehicles (IoV) users due to the sudden traffic congestion, unmanned aerial vehicles (UAVs) are introduced to the intelligent transportation systems (ITS) to construct an UAV-assisted IoV network. The UAV limited energy and computing resources lead to the current traditional UAV coverage strategy with one by one less efficiency. We propose a parallel task transmission and processing optimization strategy, considering the line-of-sight communication links and fast moving characteristics of UAV. After receiving the tasks from vehicles in the service point, UAV can fly to the next point and perform task …

Jamming-Tolerant Low-Rate Wireless Personal Area Network For Detection Sensor Networks, Michael A. Eddy

Theses and Dissertations

This research evaluates the impact of electronic warfare, particularly jamming, on an audio-based drone detection wireless sensor network (WSN) using Monte Carlo simulations. A six-node IEEE 802.15.4 network, with five edge nodes and a central sink, is tested against jamming probabilities ranging from 0-100% in 5% increments across 30 iterations per configuration. Results show that packet delivery ratio (PDR) degrades linearly at approximately 20% per jammed node, while detection performance often exceeds PDR. Even at 80% jamming, detection success rates remain above 57%, highlighting resilience despite network degradation. The study reveals that jamming effectiveness depends on node placement relative to …

Using Unmanned Aerial Vehicles To Facilitate Traffic Incident Management, Adam William Hill

Theses and Dissertations

Incident management teams (IMTs) minimize crash impacts and create a safer highway network for people and communities. Research has shown that optimizing the IMT fleet has strong benefits to the roadway network, but future models indicate that increasing IMT presence may have diminishing returns after excessive roadway saturation. The Utah Department of Transportation (UDOT) would like to improve situational awareness in areas of poor or limited camera coverage, where situational awareness is typically poor. UDOT is considering the use of unmanned aerial systems (UAS) to provide live camera coverage of traffic conditions in these instances. This thesis synthesizes practice from …

Improving The Operator-Swarm Dynamic Under Mental Fatigue Constraints In Search And Rescue Operations, Jordan Morrow

Masters Theses

"Human-robot applications that allow for work to be done remotely are largely dependent on the lassitude of the operators. The exhaustion of these operators is a result of work completion and duration. Previous research attempts to evaluate the impact on reaction by quantiying human weariness. This paper examines how human weariness affects the human-robot dynamic in UAV-assisted search and rescue missions. An explanation of the connection between mental exhaustion and operator responsiveness over prolonged durations is provided by the search and rescue operations using UAV swarms (SAROUS) model. Through the use of artificial intelligence, SAROUS is modernized. This allows the …

Numerical Investigation Of Wind Disturbance Around A Multirotor Uav In Crosswind And Vertical Flight, Garrison Page

Theses and Dissertations--Mechanical and Aerospace Engineering

Uncrewed Aerial Vehicles (UAVs) are being increasingly utilized in a wide range of research applications, especially in meteorology. This is due to such factors as their ease of use, maneuverability compared to other forms of data collection, and for rotor- craft, the ability to hover. However, the rotorwash generated by UAVs can introduce significant disturbances, potentially affecting measurement accuracy from sensors. While several studies have investigated the rotorwash of individual UAVs utilizing Particle Image Velocimetry (PIV) and Computational Fluid Dynamics (CFD), there is limited exploration into how different rotor configurations and external wind conditions influence regions of turbulent flow around …

Acoustic Characterization Of A Quadcopter Using A Test Stand, Jared Schmal

Theses and Dissertations--Mechanical and Aerospace Engineering

Unmanned Aerial Vehicles (UAVs) with multirotor propulsion and control, commonly called drones or multicopters, generate a complex acoustic field that is not entirely understood. Many components and their interactions contribute to the overall noise level and behavior of the acoustic field. However, performing acoustic measurements on a multicopter in a confined space, such as a small anechoic chamber, can be an extremely difficult and time-consuming process. A test stand was developed to allow for rapid and safe acoustic measurements in a controlled environment. The design, development, and initial measurements are discussed. The performance and acoustic response are assessed to examine …

Development Of An Quadcopter Unmanned Aerial Vehicle For Atmospheric Remote Sensing, Omar J. Addasi

Dissertations and Theses

This paper explores the development of a quadcopter unmanned aerial vehicle (UAV, a.k.a. drone) for atmospheric remote sensing of temperature, pressure, humidity, and PM2.5 particulate matter quantities. A 3-D printed drone body is designed and flight tuning is performed. An optimal length for an upward extending mast for the drone body is determined. Low cost, lightweight sensors are compared against higher precision sensors in both static and dynamic conditions. In addition, an initial investigation into the design of a pressure sensor based anemometer is performed.

Delivery Of Medical Supplies To Remote Locations Via Unmanned Aerial Vehicles: Approaches, Challenges, And Solutions, Meshari Aljohani, Ravi Mukkamala, Stephanie Olariu

Computer Science Faculty Publications

Unmanned Aerial Vehicles (UAVs) are becoming more important in improving healthcare logistics, in particular due to their cost effectiveness, minimized risk, and versatile operational capabilities. This study explores the deployment of autonomous UAVs to deliver medical supplies to remote areas. Advances in ledger technology, smart contracts, and machine learning have transformed tasks previously managed by human teams or manually controlled UAVs into fully autonomous missions. We present a comprehensive analysis of the challenges and initial solutions vital for the effective use of autonomous UAVs in the delivery of medical supplies. In addition, we propose a machine-learning model to optimize UAV …