Engineering Commons^™

End-To-End Autonomous Quadcopter Using Reinforcement Learning, Mohamed Marwan Chawa

Theses and Dissertations

This thesis investigates the potential of Reinforcement Learning (RL) for achieving robust and adaptable quadcopter control, focusing on trajectory and attitude stabilization. We compare state-of-the-art RL algorithms, specifically Proximal Policy Optimization (PPO), against traditional Proportional-Integral-Derivative (PID) controllers across three tasks: hovering, slow trajectory following, and fast trajectory following. To enhance realism, we employ a modified PyFlyt simulation environment with a high-fidelity Crazyflie 2.x model, accounting for motor dynamics, noise, wind disturbances, and aerodynamic drag.

The challenge of operating a quadcopter can be divided into two distinct parts: planning a flight path and actually following that path. Our focus is on …

Algorithm And Semi-Physical System Simulation For Command Intent Recognition Of Uav In Low-Resource Environment, Hongfu Liu, Yajing Fu, Wanpeng Zhang, Hu Zhang

Journal of System Simulation

Abstract: When a communication network is partially disabled or disrupted, an UAV is plunged into a "low-resource environment" and must rely on local hardware resources. This situation imposes constraints on computing power, storage capacity, and energy availability. To address the need for command intent recognition in such environments, a semi-physical simulation system for UAV in emergency rescue operations has been designed and implemented. Based on the low resource airborne hardware in the loop, the system simulates UAV command intention recognition and mission planning through GIS+BIM 3D environment modeling task scenarios. A new lightweight algorithm for intent recognition has been proposed, …

Performance Evaluation Of Routing Protocols And Ml-Based Enhancements For Uav-Assisted Post-Disaster Communication Networks, Prachi Choudhary

Doctoral Dissertations and Master's Theses

During natural disasters, the existing communication systems collapse, and the disaster-affected areas become disconnected without any means of exchanging information. The collapse of existing communication networks poses challenges for First-Responders (FRs) in locating survivors during Search and Rescue (SAR) operations and for survivors to communicate for emergency aid. To alleviate post-disaster consequences and save lives, Uncrewed Air Vehicles (UAVs), commonly known as drones, can be employed to establish adaptable and reliable emergency communication networks. UAVs offer portability and rapid deployment, making them effective in crises. This thesis presents two main contributions: 1) Evaluation and Comparison of Routing Protocol Performance: The …

Dynamic Resource Allocation For Beyond 5g Networks Through Uav-Assisted Communication, Iman Adel Sami

Thesis/ Dissertation Defenses

In response to the surging demand for cellular services, driven partly by the post-COVID-19 era, network operators are grappling with the challenge of enhancing network capacity and throughput. Fifth-generation mobile technology and beyond (6G) with techniques like network slicing are emerging as promising solutions for faster data speeds and improved network performance across various devices. In network slicing, distributing radio resources between different virtual operators (slices) is often performed in a static manner. Therefore, due to the dynamic user demand, the users of one virtual operator could suffer from a lack of resources, whereas another virtual operator with overlapping cells …

Determining The Difference In Monthly Hazardous Uas Sightings Pre- And Post-Trust​, Jacob Daniel Anderson, Kyle Beane, Ethan Ryan Prins, Brooke Wheeler

Aeronautics Student Publications

Unmanned Aerial Systems (UASs) present a significant challenge to regulators. This study determined that there was no statistically significant difference in monthly UAS sightings before and after the implementation of TRUST.

Control Of X-Delta Arm And Self-Leveling Robot Systems For Uav Applications, Prathibha Sobha

UNLV Theses, Dissertations, Professional Papers, and Capstones

The water droplet penetration test (WDPT) is an environmental assessment method for analyzing soil properties by measuring the penetration of water droplets into soil. This test provides insights into soil moisture retention and resilience, especially valuable in fire-prone or arid regions where soil recovery and erosion control are essential. Although this project does not conduct an actual WDPT, it investigates two key robotic systems designed to support such applications: an X-delta robot arm, which simulates precise droplet delivery patterns, and a self-leveling platform that ensures stability on uneven terrain, where the X-delta robot is mounted. Together, these systems examine the …

Impact Of Weather Systems On Uav Parameters Using Computational Fluid Dynamics, Saif Aljuhaishi, Yaseen K. Al-Timimi, Basim I. Wahab

Karbala International Journal of Modern Science

Since drones cannot fly in any kind of weather, they are not safe for time-sensitive activities. The study examines how the passage of weather systems in Iraq leads to the ban on drone flights, and how these weather conditions impact the aerodynamic forces of the drone. Hourly climate data for the study area were obtained from ECMWF ERA5 and CAMS in NetCDF format for four climate stations (Erbil, Baghdad, Rutbah, and Basrah). A ScanEagle drone was chosen for this study. The Python programming language was used to perform mathematical operations to calculate the ban on drone flights. ArcGIS 10.8 was …

Water Use Efficiency In Rice Under Alternative Wetting And Drying Technique Using Energy Balance Model With Uav Information And Aquacrop In Lambayeque, Peru, Lia Ramos-Fernández, Roxana Peña-Amaro, José Huanuqueño-Murillo, David Quipse-Tito, Mayra Maldonado-Huarhuachi, Elizabeth Heros-Aguilar, Lisveth Flores Del Pino, Edwin Pino-Vargas, Javier Quille-Mamani, Alfonso Torres-Rua

Civil and Environmental Engineering Faculty Publications

In the context of global warming, rising air temperatures are increasing evapotranspiration (ET_c) in all agricultural crops, including rice, a staple food worldwide. Simultaneously, the occurrence of droughts is reducing water availability, affecting traditional irrigation methods for rice cultivation (flood irrigation). The objective of this study was to determine ET_c (water use) and yield performance in rice crop under different irrigation regimes: treatments with continuous flood irrigation (CF) and irrigations with alternating wetting and drying (AWD₅, AWD₁₀, and AWD₂₀) in an experimental area in INIA–Vista Florida. Water balance, rice physiological data, …

Ground Robot Relocation Method Based On Uav Point Cloud Map, Hongzhi Huang, Kai Yan, Changfeng Liu, Jianwen Wang, Bin Luo

Journal of System Simulation

Abstract: In response to the challenge of relocalization in air-ground collaborative systems without the support of Global Navigation Satellite System (GNSS), and the associated issues of insufficient accuracy, a coarse-to-fine relocalization algorithm based on a three-dimensional point cloud map is proposed. The algorithm eliminates the influence of invalid point clouds from the sky and ground through index filtering, performs coarse localization by extracting global features from the point cloud and applying truncated least squares estimation, and then employs voxel-based iterative closest point (ICP) for precise optimization to obtain the more accurate localization results. A ground robot localization and autonomous navigation …

Search Technology For Aircraft Debris Integrating Data Augmentation And Deep Learning Algorithm, Zhe Yang, Yinghan Cui, Lingxi Guo, Jiaxin Li, Xusheng Wu

Journal of System Simulation

Abstract: The reliable recovery of aircraft debris is of great significance for the complete acquisition of flight test data and the subsequent research and development of models. To ensure the safety of flight tests,the landing area of aircraft experiments is generally an unmanned area,and the actual landing point of the aircraft often deviates from the theoretical landing point. The characteristics of the debris target are complex and the dispersion area is large, making it difficult to search for aircraft debris solely by manpower. Aiming at the difficult problem of aircraft debris recovery in the landing area, through on UAV platforms …

Uav Online Track Planning Based On Dmoea-Aptc Algorithm, Erchao Li, Shenghui Zhang

Journal of System Simulation

Abstract: In order to solve the dynamic multi-objective optimization problem with time correlation, this paper introduces the concept of time correlation feature and establishes the model of UAV timecorrelation dynamic multi-objective optimization problem moedl on the basis of UAV online track planning problem, and proposes a dynamic multi-objective double-layer optimization algorithm using adaptive predictive response mechanism and time-correlation optimization mechanism (DMOEA-APTC). The intensity of environmental change was judged according to the correlation of environmental change and different response mechanisms were used to quickly adapt to environmental change. In the optimization process, the least square method was used to learn the …

Uav Dynamic Path Planning Algorithm Combined With Dynamic Window Approach, Bin Liu, Ying Lan, Wentao Huang, Qinqin Fan

Journal of System Simulation

Abstract: To solve the problem of the poor search for optimal performance and obstacle avoidance ability of path planning algorithms in complex dynamic environments, a UAV dynamic path planning algorithm combined with dynamic window approach (UAV-DPPA-DWA) is proposed. In the UAVDPPA- DWA algorithm, a novel elliptic tangent graph algorithm based on the evaluation of offset degree and obstacle distance is proposed to obtain the optimal guidance path for the UAV in static environments. If the UAV detects moving obstacles, a localized obstacle avoidance trajectory will be generated using the dynamic window method with adaptive parameters. Otherwise, the UAV will continue …

A Methodology For Evaluating And Comparing Unmanned Inspection Platforms In Underground And Indoor Environments, Sydney Shockley

Graduate Theses & Non-Theses

This report summarizes a research project focused on development of a methodology for evaluating the performance of various unmanned aerial vehicles (UAVs, commonly referred to as drones) and robotic platforms in GPS-denied environments, highlighting a clear stratification based on technological sophistication and design intent. A series of flight trials were designed and implemented in various environments including indoor spaces with various geometries and obstacles, and an underground mine. These trials examined signal range from the unmanned platform to the controller, the ability to navigate through confined spaces and obstacles, the overall ease-of-use and responsiveness of controls, as well as specialized …

A Methodology For Evaluating And Comparing Unmanned Inspection Platforms In Underground And Indoor Environments, Sydney Shockley

Graduate Theses & Non-Theses

This report summarizes a research project focused on development of a methodology for evaluating the performance of various unmanned aerial vehicles (UAVs, commonly referred to as drones) and robotic platforms in GPS-denied environments, highlighting a clear stratification based on technological sophistication and design intent. A series of flight trials were designed and implemented in various environments including indoor spaces with various geometries and obstacles, and an underground mine. These trials examined signal range from the unmanned platform to the controller, the ability to navigate through confined spaces and obstacles, the overall ease-of-use and responsiveness of controls, as well as specialized …

Applying Uas Lidar For Developing Small Project Terrain Models, Ashraf Siddiqui

Graduate Theses and Dissertations

Unmanned aerial systems (UAS) LiDAR was used to collect survey data for small-area projects, particularly bridge replacement projects. The project aimed to compare UAS LiDAR data with conventional surveying methods. For the project, five bridge sites were selected for UAS LiDAR and conventional survey data collection, which include Lincoln Bridge 1 (East), Lincoln Bridge 2 (West), Humnoke, Frenchman’s Bayou, and Mountain Home. Data for each site was collected during the 2021–2022 winter. A DJI M600 Pro and Phoenix LiDAR Systems AL3-16 LiDAR unit were used for the UAS LiDAR measurements. The conventional survey equipment used included a global navigation satellite …

Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins

All Theses

As climate-exacerbated wildfires increasingly threaten landscapes and communities, there is an urgent and pressing need for sophisticated fire management technologies. Coordinated teams of Unmanned Aerial Vehicles (UAVs) present a promising solution for detection, assessment, and even incipient-stage suppression – especially when integrated into a multi-layered approach with other recent wildfire management technologies such as geostationary/polar-orbiting satellites and CCTV detection networks. However, there remains significant challenges in developing the necessary sensing, navigation, coordination, and communication subsystems that enable intelligent UAV teams. Further, federal regulations governing UAV deployment and autonomy pose constraints on real-world aerial testing, creating a disconnect between theoretical research …

Gps-Denied Navigation Using Location Estimation And Texel Image Correction, Nikolas I. Jensen

All Graduate Theses and Dissertations, Fall 2023 to Present

In recent years, the use of small drones, also categorized as small Unmanned Aerial Vehicles (sUAV), has surged. They are used for tasks like surveying land, collecting data from a distance, and performing maneuvers for military operations. These drones are popular because they are affordable, small, easy to use, and can navigate well in complex areas. These factors make them a cheap and quick option for tasks like surveying and surveillance when compared to traditional methods.

This thesis introduces a system that uses algorithms to figure out where the drone is. Typically, this relies on sensors and GPS, but GPS …

Uav Path Planning Based On Improved Harris Hawk Algorithm And B-Spline Curve, Zhifeng Huang, Yuanhua Liu

Journal of System Simulation

Abstract: Aiming at the global path planning problem of unmanned aerial vehicles (UAVs) in dynamic environments, this paper proposes an improved Harris Hawk optimization algorithm. To address the problem of insufficient search performance in the later stage of the algorithm, an adaptive chaos and core population dynamic partitioning strategy is proposed to improve the searchability of the algorithm in the later stage. The Harris Hawk update formula is modified, and the golden sine strategy is introduced to improve the search efficiency of the algorithm. Then, an adaptive dynamic cloud optimal solution perturbation strategy is integrated to improve the ability of …

Unmanned Aerial Vehicle (Uav)-Based High-Throughput Phenotyping For Maize Improvement, Eric T. Rodene

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Modern breeding programs rely heavily on efficiently screening large numbers of genotypes for agronomic traits, such as disease resistance, drought tolerance, and yield. Identifying the genetic loci or genes associated with these traits using GWAS or functional analyses will benefit future plant breeding efforts seeking to incorporate these traits into new crop varieties, whether through conventional breeding or gene editing techniques. Unmanned aerial vehicle (UAV)-based image data has been increasingly used for this task, as it allows entire test plots to be quickly and cost-effectively phenotyped. In my research, I have developed methods to improve the accuracy of machine learning …

Analyzing Swimming Performance Using Drone Captured Aerial Videos, Ngoc Doan Thu Tran, Kenny Tsu Wei Choo, Shaohui Foong, Hitesh Bhardwaj, Shane Kyi Hla Win, Wei Jun Ang, Kenneth T. Goh, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Monitoring swimmer performance is crucial for improving training and enhancing athletic techniques. Traditional methods for tracking swimmers, such as above-water and underwater cameras, face limitations due to the need for multiple cameras and obstructions from water splashes. This paper presents a novel approach for tracking swimmers using a moving UAV. The proposed system employs a UAV equipped with a high-resolution camera to capture aerial footage of the swimmers. The footage is then processed using computer vision algorithms to extract the swimmers' positions and movements. This approach offers several advantages, including single camera use and comprehensive coverage. The system's accuracy is …

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

All Dissertations

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 …

Advancing Near Surface Soil Moisture Measurements Using Robotics, Automation, And Remote Sensing, Hemanth Narayan Dakshinamurthy

All Graduate Theses and Dissertations, Fall 2023 to Present

Near-surface soil moisture, or the water content within the soil, is important for understanding the interactions between land and the atmosphere, and for monitoring plants in agricultural settings. However, soil moisture can be highly variable within the same field and varies considerably with time. The challenge involved with measuring soil moisture is that traditional techniques that rely on obtaining large samples are labor and time-intensive, especially for large fields. Developments in sensor technologies have allowed users to record the soil moisture regularly at the points where the sensors are installed. However, to understand how soil moisture changes across a field …

System Identification For Motion Control Of Unmanned Aerial Vehicles Platform, Raj Ramesh Agarwal

Theses and Dissertations

Comprehensive research on Unmanned Aerial Vehicles (UAV) system identification for motion control parameters is presented in this thesis, with a focus on the necessity of precise control and improved performance. Using Pseudorandom Binary Sequence (PRBS) and Normally Distributed Random Numbers, it presents a unique technique for excitation of UAV dynamic systems. It also shows how effective random signals are in time-domain identification for precise control in a range of flying circumstances. The piece of research includes a thorough analysis and implementation of various approaches and its further improvements, highlighting the benefits and drawbacks of each. These approaches include the free …

Collaborative Navigation Method For 5g Cluster Uav Based On Configuration Optimization, Chao Gao, Zheng Huang, Xuan Zhao, Hongxing Wang, Tao Long

Journal of System Simulation

Abstract: The existing range based cooperative navigation methods for clustered UAVs generally ignore the impact of space configuration on positioning and energy determination, which makes it difficult to obtain the accurate navigation and positioning results. In view of this, a collaborative navigation method is proposed for 5G clustered UAVs based on spatial configuration optimization. The relative ranging error model of UAVs based on 5G signals in complex environments is constructed, and the optimization strategy for collaborative navigation nodes is established based on the minimum geometric division of precision(GDOP) criterion to achieve the real-time optimization of collaborative navigation spatial configuration; A …

Implementation Of Path Planning Methods To Detect And Avoid Gps Signal Degradation In Urban Environments, Ayush Raminedi

Doctoral Dissertations and Master's Theses

In the modern world, various missions are being carried out under the assistance of autonomous flight vehicles due to their ability to operate in a wide range of flight conditions. Regardless, these autonomous vehicles are prone to GPS signal loss in urban environments due to obstructions that cause scintillation, multi-path, and shadowing. These effects that decrease the GPS functionality can deteriorate the accuracy of GPS positioning causing losses in signal tracking leading to a decrease in navigation performance. These effects are modeled into the simulation environment and are used as part of the path planning algorithm to provide better navigation …

Bim-Gis Integration An Innovative Tool To Enhance Urban Heritage Management In The Digital Era, Ali H. Misilmani, Ibtihal Y. El-Bastawissi, Hany Ayad, Samer El Sayary

Architecture and Planning Journal (APJ)

Due to the great loss of the cities’ ancient monuments and urban heritage resulting from either natural disasters or irresponsible human actions, it has become very urgent to find an innovative tool for restoring and conserving historical buildings in a smart and sustainable way. Furthermore, this tool can help in decision making regarding the selection of appropriate materials and intervention works. Such objectives have been realized through innovative integration of BIM & GIS to enhance urban heritage management. BIM data has been imported into the GIS environment to be visualized in 3D and analyse different scenarios for buildings’ sustainable development. …

Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …

Assessing The Potential Of Uav-Based Multispectral And Thermal Data To Estimate Soil Water Content Using Geophysical Methods, Yunyi Guan, Katherine R. Grote

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Knowledge of the soil water content (SWC) is important for many aspects of agriculture and must be monitored to maximize crop yield, efficiently use limited supplies of irrigation water, and ensure optimal nutrient management with minimal environmental impact. Single-location sensors are often used to monitor SWC, but a limited number of point measurements is insufficient to measure SWC across most fields since SWC is typically very heterogeneous. To overcome this difficulty, several researchers have used data acquired from unmanned aerial vehicles (UAVs) to predict the SWC by using machine learning on a limited number of point measurements acquired across a …

Real-Time Detection Of Sea Turtles Using Uav And Neural Networks On Edge Devices, Jose A. Gonzalez Nunez, Jose G. Gonzalez Nunez, Mustafa I. Akbas, Patrick Currier, Nickolas D. Macchiarella

Journal of Aviation/Aerospace Education & Research

Sea turtle populations continue to diminish around the globe for various reasons. Therefore, the need for innovative solutions to monitor sea turtles has been increasing. This research paper focuses on an innovative application of artificial intelligence (AI) and machine learning (ML) together with unmanned aerial vehicles (UAV) to improve sea turtle conservation efforts. We outline the design, implementation, and evaluation of a system that deploys UAVs equipped with high-resolution cameras, coupled with a purpose-built neural network to recognize, classify, and monitor sea turtles. This project thus serves as a platform for understanding the wider applicability and limitations of this technology …

A New Trajectory In Uav Safety: Leveraging Reinforcement Learning For Distance Maintenance Under Wind Variations, Xiaolin Xu, Jeffrey Sun

Journal of Aviation/Aerospace Education & Research

In the field of aviation, safety is a critical cornerstone, and the operation of Unmanned Aerial Vehicle (UAV) systems is deeply connected with this principle. A thorough analysis and rigorous simulation and testing of aircraft systems are essential to avoid severe safety hazards. This paper delves into the safety issue in UAV operations, specifically regarding maintaining minimum safety distances under fluctuating wind conditions. The study introduces a novel solution based on a Deep Deterministic Policy Gradient (DDPG) model, a reinforcement learning method. The DDPG model was trained using a simulated environment created through the Gazebo simulator, with values for wind …