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Full-Text Articles in Computer Engineering

Heterogeneous Collaborative Robotics: Multi-Robot Navigation In Dynamic Environments, Tyler Nicholas Raettig Dec 2024

Heterogeneous Collaborative Robotics: Multi-Robot Navigation In Dynamic Environments, Tyler Nicholas Raettig

Theses and Dissertations

Abstract: The challenges of multi-robot navigation in dynamic environments, focusing on uncertainties in obstacle complexities, partial observation, and the transition of policies from simulations to the real world. The proposed approach utilizes a deep reinforcement learning (DRL) framework enabling a Light Detection and Ranging (LiDAR)-equipped robot to communicate with a camera-equipped robot to achieve optimal paths despite their different sensors. The key contributions include the development of a cooperative architecture for information exchange between robots, a DRL-based framework for learning navigation policies, and a training mechanism based on dynamic randomization for enhanced real-world adaptability. Experimental validation using Gazebo simulations demonstrates …


End-To-End Learning For A Low-Cost Robotics Arm, Abhishek Chothani Dec 2024

End-To-End Learning For A Low-Cost Robotics Arm, Abhishek Chothani

Theses and Dissertations

Robotic manipulation is a cornerstone of automation, with the ultimate goal of developing versatile systems capable of executing a wide range of real-world tasks autonomously. Traditional robotics approaches, while reliable and widely adopted in industrial settings, often struggle with adaptability, perception, and dynamic task execution. This thesis explores the evolution from classical robotics techniques to modern learning-based approaches, leveraging advancements in artificial intelligence to overcome these limitations.

Initially, the thesis presents a pick-and-place pipeline built using the Drake robotics framework and the KUKA iiwa robotic arm. This system employs a pseudoinverse controller for inverse kinematics to perform structured tasks like …


Improving Robustness Of Learning-Based Approaches In Autonomous Systems And Engineering Education, Godwyll Aikins Dec 2024

Improving Robustness Of Learning-Based Approaches In Autonomous Systems And Engineering Education, Godwyll Aikins

Theses and Dissertations

This dissertation advances the development of robust learning-based approaches across two complementary domains: engineering education and autonomous systems. Through four studies, this research addresses critical challenges in preparing data-proficient engineers and developing reliable autonomous systems that can operate under uncertainty and incomplete information. The engineering education study examines how mechanical and aerospace engineering undergraduates conceptualize and develop data proficiency skills essential for modern engineering practice. Through interviews with 27 students, the research employs the How People Learn framework to analyze student perspectives on information literacy, data interpretation, and computational thinking. The findings inform pedagogical strategies for developing data proficiency in …


Collapse Of Pre-Covid-19 Differences In Performance In Online Vs. In-Person College Science Classes, And Continued Decline In Student Learning, Gregg R. Davidson, Hong Xiao, Kristin Davidson Nov 2024

Collapse Of Pre-Covid-19 Differences In Performance In Online Vs. In-Person College Science Classes, And Continued Decline In Student Learning, Gregg R. Davidson, Hong Xiao, Kristin Davidson

Faculty and Student Publications

Abstract: Studies comparing student outcomes for online vs. in-person classes have reported mixed results, though with a majority finding that lower-performing students, on average, fare worse in online classes, attributed to the lack of built-in structure provided by in-person instruction. The online/in-person outcome disparity was normative for non-major geology classes at the University of Mississippi prior to COVID-19, but the difference disappeared in the years after 2020. Previously distinct trendlines of GPA-based predictions of earned-grade for online and in-person classes merged. Of particular concern, outcomes for in-person classes declined to match pre-COVID-19 online expectations, with lower-GPA students disproportionally impacted. Objective …


2024 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department Oct 2024

2024 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2024.


Computer Vision In A Robotic Arm, Jack Maxwell Oct 2024

Computer Vision In A Robotic Arm, Jack Maxwell

College of Engineering Summer Undergraduate Research Program

We used a machine learning-based object detection algorithm to give a robotic arm the ability to "see" with its camera.


Design And Implementation Of An Inverted Short Baseline Acoustic Positioning System, Jakob Frabosilio Sep 2024

Design And Implementation Of An Inverted Short Baseline Acoustic Positioning System, Jakob Frabosilio

Master's Theses

This document details the design, implementation, testing, and analysis of an inverted short baseline acoustic positioning system. The system presented here is an above-water, air-based prototype for an underwater acoustic positioning system; it is designed to determine the position of remotely-operated underwater vehicles (ROVs) and autonomous underwater vehicles (AUVs) in the global frame using a method that does not drift over time.

A ground-truth positioning system is constructed using a stacked hexapod platform actuator, which mimics the motion of an AUV and provides the true position of an ultrasonic microphone array. An ultrasonic transmitter sends a pulse of sound towards …


Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan Aug 2024

Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan

All Dissertations

This thesis is concerned with the data-driven solution to the optimal control problem with safety constraints for a class of control-affine nonlinear systems. Designing optimal control satisfying safety constraints is a problem of interest in various applications, including robotics, power systems, transportation networks, and manufacturing. This problem is known to be non-convex. One of this thesis's main contributions is providing a convex formulation to this non-convex problem. The second main contribution is providing a data-driven framework for solving the control problem with safety constraints. The linear operator theoretic framework involving Perron-Frobenius and Koopman operators provides the convex formulation and associated …


Ultrashort Pulsed Laser Treatment Is Effective At Sterilizing Metal Surfaces For Planetary Protection, Kaleb Mcquillan Aug 2024

Ultrashort Pulsed Laser Treatment Is Effective At Sterilizing Metal Surfaces For Planetary Protection, Kaleb Mcquillan

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

To prevent forward contamination from microbes aboard spacecraft intended for exploration of solar system bodies there is a need for effective sterilization methods. However, current techniques are both time-consuming and expensive. For example, dry heat sterilization requires removal from the assembly site and several days of treatment. Furthermore, some components such as optics and electronics are not compatible with current sterilization techniques. In this thesis, a novel femtosecond laser surface processing technique for the rapid sterilization of spacecraft hardware is reported. Femtosecond lasers produce extremely high photon fluxes (1029 photons/s*cm2, ~0.03 J/cm2) in extremely short …


Studying The Performance Of Object Recognition With Fusion Of Visible Light And Infrared Images With Neural Networks, Plamen Petkov Jul 2024

Studying The Performance Of Object Recognition With Fusion Of Visible Light And Infrared Images With Neural Networks, Plamen Petkov

Doctoral Dissertations and Master's Theses

Neural networks have been used for object detection and recognition in both color and intensity camera images. As the use of infrared cameras, colloquially termed thermal cameras, has increased and costs have decreased, object detection and recognition in infrared camera images have been increasingly studied. An infrared image is treated as an intensity image, just like a grayscale camera image, except the intensity corresponds to infrared radiation instead of visible light. The information provided by these two types of images are different, especially in different lighting and environmental situations, and some types of objects are more easily recognized in visible …


Development Of A Rule-Based Monitoring System For Autonomous Heavy Equipment Safety, Amirpooya Shirazi Jul 2024

Development Of A Rule-Based Monitoring System For Autonomous Heavy Equipment Safety, Amirpooya Shirazi

Department of Construction Engineering and Management: Dissertations, Theses, and Student Research

Roadway construction work zones are constantly exposed to interactions among construction equipment, workers, and vehicles. Furthermore, ensuring safety in these areas is considered a challenging task due to the complexity of the environment. As shown in the rising trend of fatal accidents in roadway work zones, current OSHA regulations in construction safety are insufficient in effectively detecting unsafe situations and mitigating the risks. Furthermore, best practices, such as internal traffic control planning (ITCP), exhibit critical limitations requiring continuous monitoring of active work zones as well as adjustments to the site coordination plans due to the dynamic nature of work zone …


Cognitive Manufacturing: Definition And Current Trends, Fadi El Kalach, Ibrahim Yousif, Thorsten Wuest, Amit Sheth, Ramy Harik Jun 2024

Cognitive Manufacturing: Definition And Current Trends, Fadi El Kalach, Ibrahim Yousif, Thorsten Wuest, Amit Sheth, Ramy Harik

Publications

Manufacturing systems have recently witnessed a shift from the widely adopted automated systems seen throughout industry. The evolution of Industry 4.0 or Smart Manufacturing has led to the introduction of more autonomous systems focused on fault tolerant and customized production. These systems are required to utilize multimodal data such as machine status, sensory data, and domain knowledge for complex decision making processes. This level of intelligence can allow manufacturing systems to keep up with the ever-changing markets and intricate supply chain. Current manufacturing lines lack these capabilities and fall short of utilizing all generated data. This paper delves into the …


Exploring The Impact Of Artificial Intelligence On Project Management Across The Manufacturing, Technology, And Construction Industries, Susie Diaz Ferrera Jun 2024

Exploring The Impact Of Artificial Intelligence On Project Management Across The Manufacturing, Technology, And Construction Industries, Susie Diaz Ferrera

Harrisburg University Dissertations and Theses

This study explores the impact of Artificial Intelligence (AI) on project management across the manufacturing, technology, and construction industries. The research focuses on understanding the benefits, challenges, and long-term implications of AI utilization in these sectors. Key findings indicate that 46% of participants use AI mainly for task automation and enhancing functions like brainstorming and communication, which significantly boosts efficiency and team productivity. Despite these benefits, the research identifies several obstacles, including high initial costs, inadequate training, technical issues, and unclear regulatory guidelines. The study addresses four main questions, revealing that AI not only enhances project management processes but also …


Development Of A Multi-Use Modular Microfluidic Platform Using 3d Printing, Carson Emeigh May 2024

Development Of A Multi-Use Modular Microfluidic Platform Using 3d Printing, Carson Emeigh

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Microfluidic lab-on-a-chip (LoC) technology has driven numerous innovations due to their ability to perform laboratory-scale experiments on a single chip using microchannels. Although LoC technology has been innovative, it still suffers from limitations related to its fabrication and design flexibility. Typical LoC fabrication, with photolithography, is time consuming, expensive, and inflexible. To overcome the limitations of LoC devices, modular microfluidic platforms have been developed where multiple microfluidic modules, each with a specific function or group of functions, can be combined on a single platform. Modular microfluidics have overcome some of the limitations of LoC devices, but currently, their fabrication is …


Summonable Construction Delivery Robot, Kevin M. Lewis May 2024

Summonable Construction Delivery Robot, Kevin M. Lewis

Honors Capstones

In many different construction industries, there is a need for tools, parts, and other necessary items to be transported quickly and efficiently over various types of terrain. Human resources have often been used to address these needs, which can become very time and cost inefficient over long periods. The design proposal here is aimed at addressing this need by developing an autonomous outdoor mobile robot based on a quadrupedal robot design. This approach differs by incorporating a wheeled and quadrupedal hybrid actuation system that provides terrain negotiation and speed at the appropriate times. The team uses Robot Operating System (ROS) …


Deep Reinforcement Learning Of Variable Impedance Control For Object-Picking Tasks, Akshit Lunia May 2024

Deep Reinforcement Learning Of Variable Impedance Control For Object-Picking Tasks, Akshit Lunia

All Theses

The increasing deployment of robots in industries with varying tasks has accelerated the development of various control frameworks, enabling robots to replace humans in repetitive, exhaustive, and hazardous jobs. One critical aspect is the robots' interaction with their environment, particularly in unknown object-picking tasks, which involve intricate object weight estimations and calculations when lifting objects. In this study, a unique control framework is proposed to modulate the force exerted by a manipulator for lifting an unknown object, eliminating the need for feedback from a force/torque sensor. The framework utilizes a variable impedance controller to generate the required force, and an …


Experiment Development And Validation Of A Granular Jamming Robotic Gripper, Jacob R. Dowd May 2024

Experiment Development And Validation Of A Granular Jamming Robotic Gripper, Jacob R. Dowd

UNLV Theses, Dissertations, Professional Papers, and Capstones

A granular jamming gripper (GJG) is widely known as a Universal Gripper because of the wide range of objects that it can grasp and the simplicity of control, design, and manufacturing. Despite multitude of research improving the GJG, here, we focus on the base version of the GJG and attempt to glean the range of objects that it may reliably grasp. Despite the limited range of objects, which were a sphere, rectangular prism, and cylinder, we gleaned geometric properties as it relates to successful and unsuccessful grasping. This was based on the two types of testing: push and pull testing …


Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens May 2024

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …


2024 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department Apr 2024

2024 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2024.


Under Pressure: The Soft Robotic Clap-And-Fling Of Cuvierina Atlantica, Daniel Mead Mar 2024

Under Pressure: The Soft Robotic Clap-And-Fling Of Cuvierina Atlantica, Daniel Mead

USF Tampa Graduate Theses and Dissertations

Evolution over billions of years has led to unique animals of all types. The tiny sea butterfly is one that remains mostly anonymous because of its size and low place on the food chain, but it is a swimming creature that when examined closely reveals a surprise. Shockingly, it has a swimming motion nearly identical to small insects flying at intermediate Reynolds numbers, referred to as the clap-and-fling. The centimeter long pteropod flapping briskly at 5Hz escapes attention with its size and speed. Modeling the clap-and-fling motion of the sea butterfly at a larger scale allows the benefits and uniqueness …


Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson Feb 2024

Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson

Dissertations

Our co-authored research ‘Steminism: Analyzing Factors That Improve Retention for Women as STEM Majors’ analyzed factors that contributed to the retention of women in science, technology, engineering, and mathematics (STEM) programs at Missouri University of Science & Technology (Missouri S&T). Women make up half of the US population, and while careers in (STEM) are an integral part of the US economy, women are underrepresented in these career fields. The purpose of our dissertation is to address the underrepresentation of women in STEM majors. Our methodology included homogeneous sampling to collect qualitative data. More specifically, we consulted with academic advisors and …


Nonlinear Guidance And Control Of Unmanned Aerial Manipulators For Delivering A Payload On A Moving Platform, Ravi Gyawali Jan 2024

Nonlinear Guidance And Control Of Unmanned Aerial Manipulators For Delivering A Payload On A Moving Platform, Ravi Gyawali

Mechanical and Aerospace Engineering Theses - Archive

Unmanned Aerial manipulators (UAMs) are a class of Unmanned Aerial Vehicles (UAVs) equipped with a manipulator. By combining the aerial mobility of a UAV with a manipulator's dexterity, these hybrid systems can perform a wide range of complex tasks while reducing risks and costs. As a result, they are increasingly being utilized for military, industrial, and agricultural applications.

The thesis presents a novel approach for a multi-UAM system to collaboratively deliver a payload on a stationary or maneuvering platform. A sliding-mode-based guidance law, sourced from existing literature, is integrated with a combined control technique for the UAVs and their respective …


Strategies To Mitigate Efflorescence In Walls Constructed Using Clays Bricks; A Review Article, Marwa Abdulkareem. Anber, Soran Abdulrahman Ahmad, Naros Rahman Mahmoud, Kawan Fuoad. Kayani, Mohammed Ali Abdulrehman Jan 2024

Strategies To Mitigate Efflorescence In Walls Constructed Using Clays Bricks; A Review Article, Marwa Abdulkareem. Anber, Soran Abdulrahman Ahmad, Naros Rahman Mahmoud, Kawan Fuoad. Kayani, Mohammed Ali Abdulrehman

Al-Esraa University College Journal for Engineering Sciences

The construction of buildings, especially residential housing for communities, is a significant industry on a global scale. Masonry units such as bricks, blocks, and stones are often utilized materials. Bricks are highly regarded because to their widespread availability, cost-effectiveness, and excellent insulating capabilities. Nevertheless, the presence of efflorescence presents a difficulty in the construction of brick walls. Efflorescence refers to the process in which salts move to the outer layer of the brick, resulting in the formation of white deposits and negatively impacting its visual appeal. Efflorescence is caused by various circumstances, such as the existence of salts in bricks, …


The Importance Of Cryptography In Cloud Computing, Saja Alaam Talib Jan 2024

The Importance Of Cryptography In Cloud Computing, Saja Alaam Talib

Al-Esraa University College Journal for Engineering Sciences

Cloud computing has grown as a widely accepted concept simultaneously, as the alarms for the security of data and information. This paper seeks to establish the comprehensive roles of cryptography in tackling these issues in the Cloud environment. The study begins with the historical background of cryptography and then moves on to analyze trends in information technology before discussing on the challenges to security in cloud computing. The goal of its publication is to highlight the importance of using cryptographic technologies for the protection of information confidentiality, its integrity and compliance. The combination of literature review and the case study …


On Uncertainty For Ill-Posed Robot Decision Problems, Jared Joseph Beard Jan 2024

On Uncertainty For Ill-Posed Robot Decision Problems, Jared Joseph Beard

Graduate Theses, Dissertations, and Problem Reports (ETD)

As robots adopt more real world responsibilities, they will be expected to solve more complicated problems. In some cases limited prior knowledge will result in unmodelled environmental conditions; in others, multiple users may have competing perspectives on how to frame a decision problem. Many existing frameworks, namely Markov decision processes (MDP) presuppose users have identified a specific problem with models sufficient to solve or learn a problem. If we wish to extend MDPs to novel problems or those heavily dependent on user feedback, autonomous decision makers must be able to identify limitations in how a given problem is framed and …


Observability-Aware Path Planning For Autonomous Navigation, Raymond Brink Neistat Jan 2024

Observability-Aware Path Planning For Autonomous Navigation, Raymond Brink Neistat

Open Access Master's Theses

Terrain-Aided Navigation (TAN) is a popular method of localization for GPS-denied vehicles, particularly in the marine domain. There are many ways to perform TAN in a marine setting, such as Bathymetric SLAM (BSLAM) and Bayesian Filtering with the aid of an a priori map. These techniques have been studied extensively, but show an overall lack of rigorous observability analyses. Without nonlinear observability analyses, TAN practitioners do not have an analytical indicator to know which areas of terrain will provide opportunities for the best localization performance. This thesis reviews current developments in the endeavors of nonlinear observability analyses as well as …


Enhancing Robotic Exploration Through Semantically-Guided Sampling Strategies, Christopher Alexander Arend Tatsch Jan 2024

Enhancing Robotic Exploration Through Semantically-Guided Sampling Strategies, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports (ETD)

From space and deep-sea exploration to disaster response and environmental monitoring, autonomous robots are essential for advancing science, improving safety, and addressing critical challenges. This dissertation introduces a novel open-source strategy for autonomous robotic exploration: the Semantically-Guided Exploration (SGE) framework. Designed for ground vehicles, SGE integrates semantic understanding into the autonomous exploration process, improving decision-making in complex environments. Specifically, the proposed sampling-based approach uses the information from the semantic segmentation of RGB images and depth images to guide the robot's selection of exploration goals. This method enables the robot to steer away from potential dangers such as large rocks and …


Development Of A Solidworks Api, Andrew Magyar Jan 2024

Development Of A Solidworks Api, Andrew Magyar

Williams Honors College, Honors Research Projects

With the current advancements in CAD software, and precision of modern motors, we believe that a new way to communicate from hardware to software is possible. This report details the steps we have taken to attempt just that. The essential idea behind this is that modern controls for robotics are not as user friendly as they can be. The general action taken is to create an API for SolidWorks that connects it to the other necessary controller software and makes it so that a robot, and its exact current position, can be changed simply and intuitively from SolidWorks. Furthermore, the …


The Impact Of Modern Buildings On Traditional Urban Environments And Urban Identity, Ann S. Ibrahim Jan 2024

The Impact Of Modern Buildings On Traditional Urban Environments And Urban Identity, Ann S. Ibrahim

Al-Esraa University College Journal for Engineering Sciences

Contemporary cities face significant challenges in integrating modern buildings into traditional urban environments while preserving urban identity. This study focuses on the relationship between modern architecture and urban heritage. The research problem revolves around how modern buildings affect urban identity in traditional areas, and whether they can interact positively with the urban context without distorting its traditional character.

The study aims to analyze this impact by examining a range of global examples using architectural indicators such as visual integration, spatial integration, material harmony, urban scale, accessibility, and environmental impact. A three-point scale (weak, partial, excellent) was applied to assess each …


Shape Inverse Prediction Of Magnetic Field-Actuated Soft Robots By Neural Network Machine Learning, Lineth J. Perez Monsalve Jan 2024

Shape Inverse Prediction Of Magnetic Field-Actuated Soft Robots By Neural Network Machine Learning, Lineth J. Perez Monsalve

Theses and Dissertations

Soft robotics has drawn tremendous interest in recent years because the compliance and motion of soft robotics enable biocompatibility and versatility for many applications, such as human-machine interaction, wearable and assistive devices, and health monitoring. This study introduces a novel predictive modeling approach using neural networks for shape control of magnetic soft robots. The robots are made of silicone materials embedded with hard magnetic particles, which respond to the external magnetic field provided by a ring-type of permanent magnet. These robots, free from physical connections to external devices, i.e., non-tethered actuation, hold significant potential for applications in healthcare, such as …