Computer Engineering Commons^™

Reference Frames In Human Sensory, Motor, And Cognitive Processing, Dongcheng He

Electronic Theses and Dissertations

Reference-frames, or coordinate systems, are used to express properties and relationships of objects in the environment. While the use of reference-frames is well understood in physical sciences, how the brain uses reference-frames remains a fundamental question. The goal of this dissertation is to reach a better understanding of reference-frames in human perceptual, motor, and cognitive processing. In the first project, we study reference-frames in perception and develop a model to explain the transition from egocentric (based on the observer) to exocentric (based outside the observer) reference-frames to account for the perception of relative motion. In a second project, we focus …

Drone Detection Using Yolov5, Burchan Aydin, Subroto Singha

Faculty Publications

The rapidly increasing number of drones in the national airspace, including those for recreational and commercial applications, has raised concerns regarding misuse. Autonomous drone detection systems offer a probable solution to overcoming the issue of potential drone misuse, such as drug smuggling, violating people’s privacy, etc. Detecting drones can be difficult, due to similar objects in the sky, such as airplanes and birds. In addition, automated drone detection systems need to be trained with ample amounts of data to provide high accuracy. Real-time detection is also necessary, but this requires highly configured devices such as a graphical processing unit (GPU). …

Skeleton-Based Hand Gesture Recognition Using Data-Level Fusion, Oluwaleke Yusuf

Theses and Dissertations

Hand Gesture Recognition (HGR) is a form of perceptual computing that allows artificial systems to capture and interpret human gestures. HGR has applications in human-machine interaction, virtual reality, augmented reality, and human behavior analysis. The human hand can assume a near-infinite number of poses and orientations to form myriad gestures, thus increasing the difficulty of the HGR task.

The hand skeleton of connected joints effectively describes the hand’s geometric shape and thus contains richer semantic gesture information while eliminating noise from individual differences in physical hand characteristics. The efficacy and computational efficiency of skeleton-based HGR frameworks can be significantly enhanced …

Gesture-Based American Sign Language (Asl) Translation System, Kayleigh Moore, Stefano Pecile, Mahdi Yazdanpour

Posters-at-the-Capitol

According to the World Health Organization (WHO), over 5% of the world's population experiences severe hearing loss. Approximately 9 million people in the U.S. are either functionally deaf or have mild-to-severe hearing loss. In this research, we designed and implemented a translation interface which turns American Sign Language (ASL) gestures captured from a pair of soft robotic gloves into text and speech instantaneously.

We used a combination of flex sensors, tactile sensors, and accelerometers to recognize hand gestures and to record hand and fingers positions, movements, and orientations. The digitized captured gestures were then sent to our proposed translation interface …

A Path Planning Framework For Multi-Agent Robotic Systems Based On Multivariate Skew-Normal Distributions, Peter Estephan

Theses, Dissertations and Capstones

This thesis presents a path planning framework for a very-large-scale robotic (VLSR) system in an known obstacle environment, where the time-varying distributions of agents are applied to represent the multi-agent robotic system (MARS). A novel family of the multivariate skew-normal (MVSN) distributions is proposed based on the Bernoulli random field (BRF) referred to as the Bernoulli-random-field based skew-normal (BRF-SN) distribution. The proposed distributions are applied to model the agents’ distributions in an obstacle-deployed environment, where the obstacle effect is represented by a skew function and separated from the no-obstacle agents’ distributions. First, the obstacle layout is represented by a Hilbert …

Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi

Electronic Theses and Dissertations

Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans …

Understanding And Quantifying Human Factors In Programming From Demonstration: A User Study Proposal, Shakra Mehak, Aayush Jain, John D. Kelleher, Philip Long, Michael Guilfoyle, Maria Chiara Leva

Conference papers

Programming by demonstration (PbD) is a promising method for robots to learn from direct, non-expert human interaction. This approach enables the interactive transfer of human skills to the robot. As the non-expert user is at the center of PbD, the efficacy of the learned skill is largely dependent on the demonstrations provided. Although PbD methods have been extensively developed and validated in the field of robotics, there has been inadequate confirmation of their effectiveness from the perspective of human teachability. To address this gap, we propose to experimentally investigate the impact of communicating robot learning process on the efficacy of …

Design And Fabrication Of A Force-Displacement Control Mechanism For Bone-Surgical Tool Testing, Kenneth Nwagu

College of Graduate Studies: Theses & Dissertations

This project focuses on the design and fabrication of an experimental setup for orthopedic-tool testing, tailored for a surgical instrumentation company. The multifaceted project encompasses a literature review, conceptual design, prototyping, and rigorous testing, resulting in a versatile control system capable of assessing various orthopedic tools, including bone drills, saws, burrs, and power handpieces.

Orthopedic surgical procedures (which include cutting and/or drilling into bone) often need to be performed on bones for faster recovery. The drilling and cutting process can cause an increase in temperature at the cutting site which can cause bone necrosis. The tools also need to be …

A Camera-Only Based Approach To Traffic Parameter Estimation Using Mobile Observer Methods, Temitope D. Jegede

College of Graduate Studies: Theses & Dissertations

As vehicles become more modern, a large majority of vehicles on the road will have the required sensors to smoothly interact with other vehicles and infrastructure on the road. There will be many benefits of this new connectivity between vehicles on the road but one of the most profound improvements will be in the area of road accident prevention. Vehicles will be able to share information vital to road safety to oncoming vehicles and vehicles that are occluded so they do not have a direct line of sight to see a pedestrian or another vehicle on the road.

Another advantage …

Improving The Flexibility And Robustness Of Machine Tending Mobile Robots, Richard Ethan Hollingsworth

Theses and Dissertations

While traditional manufacturing production cells consist of a fixed base robot repetitively performing tasks, the Industry 5.0 flexible manufacturing cell (FMC) aims to bring Autonomous Industrial Mobile Manipulators (AIMMs) to the factory floor. Composed of a wheeled base and a robot arm, these collaborative robots (cobots) operate alongside people while autonomously performing tasks at different workstations. AIMMs have been tested in real production systems, but the development of the control algorithms necessary for automating a robot that is a combination of two cobots remains an open challenge before the large scale adoption of this technology occurs in industry. Currently popular …

Parallel Real Time Rrt*: An Rrt* Based Path Planning Process, David Yackzan

Theses and Dissertations--Mechanical and Aerospace Engineering

This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network …

Robotic Inspection And Data Analytics To Localize And Visualize The Structural Defects Of Civil Infrastructure, Jinglun Feng

Dissertations and Theses

Ground Penetrating Radar (GPR) serves as a significant nondestructive evaluation (NDE) technique to inspect and survey underground objects (e.g., rebars, utility pipes) in complex urban environments. In addition to GPR, visual-based surface defect detection plays a crucial role in assessing and maintaining civil infrastructure. To facilitate deployment on a robotic platform and enhance inspection capabilities, the integration of GPR and visual-based sensors, such as RGB-D cameras, is crucial to obtain accurate subsurface and surface information. This thesis presents a novel robotic-based inspection system for the efficient collection of NDE data and accurate 3D reconstruction of both subsurface and surface infrastructure …

Modelling And Mitigating Interlocutor Confusion In Situated Human-Avatar And Human-Robot Interaction, Na Li

Dissertations

Human-Robot Interaction (HRI) is an important but challenging field focused on improving the interaction between humans and robots, to make the interaction more intelligent and effective. However, building a natural conversational HRI is an interdisciplinary challenge for scholars, engineers, and designers. Achieving successful conversational interaction with a social robot necessitates not only observing a user’s active participation in the interaction but also being aware of their emotional and attitudinal states as the interaction progresses. On the topic of attitudinal states, one field that has received little attention to date is monitoring the user for possible confusion states. Confusion is a …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

Exploiting The Advantages And Overcoming The Challenges Of The Cable In A Tethered Drone System, Rogerio Rodrigues Lima

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation proposes solutions for motion planning, localization, and landing of tethered drones using only tether variables. A tether-based multi-model localization framework for tethered drones is proposed. This framework comprises three independent localization strategies based on a different model. The first strategy uses simple trigonometric relations assuming that the tether is taut; the second method relies on a set of catenary equations for the slack tether case; the third estimator is a neural network-based predictor that can cover different tether shapes. Multi-layer perceptron networks previously trained with a dataset comprised of the tether variables (i.e., length, tether angles on the …

A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore

VMASC Publications

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents' perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt …

Human Tracking Function For Robotic Dog, Andrew Sharkey

Williams Honors College, Honors Research Projects

With the increase the increase in automation and humans and robots working side by side, there is a need for a more organic way of controlling robots. The goal of this project is to create a control system for Boston dynamics robotic dog Spot that implements human tracking image software to follow humans using computer vision as well as using hand tracking image software to allow for control input through hand gestures.

Initiating Change In Care: Socially Assistive Robots, Sooraj Sushama

Theses and Dissertations

Socially assistive robots (SAR) are autonomous machines equipped with sensors and software that allow them to interact socially with humans. SAR robots are commonly used in healthcare settings to provide patients with non-clinical support, such as conversation and emotional companionship. SARs can also deliver reminders, monitor vital signs, and provide educational information about health conditions or medications. Researchers have studied SAR applications in detail. Additionally, there has been prior research on SAR where users' sociodemographic factors and technology acceptance were studied. But even though the backbone of SAR is an advanced technology, no known research has been done on users' …

Space Force Design Project, Emily Greene, Ashton Orosa, Julia Patek, Nathan Doty

Williams Honors College, Honors Research Projects

The objective of our research project is to develop a lab testbed composed of a curved surface to represent a spacecraft hull, a mobile robot equipped with repair tools, and a robotic arm equipped with a laser 3D scanner. This project is part of a larger grant to the University of Akron from Space Force and Air Research Labs. The lab testbed developed in this project will be used to assist in creating and testing a software and algorithm to inspect and repair spacecraft while in orbit. The project will involve researching spacecraft hulls to create an accurate simulation bed, …

Benchmarking Model Predictive Control And Reinforcement Learning For Legged Robot Locomotion, Shivayogi Akki

Dissertations, Master's Theses and Master's Reports

This research delves into the realm of quadrupedal robotics, focusing on the comparative analysis of Model Predictive Control (MPC) and Reinforcement Learning (RL) as predominant control strategies. Through the comprehensive dataset compiled and the insights derived from this analysis, this research aims to serve as a valuable resource for the legged robotics community, guiding researchers and practitioners in the selection and implementation of control strategies. The ultimate goal is to contribute to the advancement of legged robot capabilities and facilitate their successful deployment in real-world applications.

In this study, we employ the Unitree Go1 quadrupedal robot as a testbed, subjecting …

Imitation Learning For Swarm Control Using Variational Inference, Hafeez Olafisayo Jimoh

Graduate Theses, Dissertations, and Problem Reports (ETD)

Swarms are groups of robots that can coordinate, cooperate, and communicate to achieve tasks that may be impossible for a single robot. These systems exhibit complex dynamical behavior, similar to those observed in physics, neuroscience, finance, biology, social and communication networks, etc. For instance, in Biology, schools of fish, swarm of bacteria, colony of termites exhibit flocking behavior to achieve simple and complex tasks. Modeling the dynamics of flocking in animals is challenging as we usually do not have full knowledge of the dynamics of the system and how individual agent interact. The environment of swarms is also very noisy …

Motion Planning In Artificial And Natural Vector Fields, Bernardo Martinez Rocamora Junior

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation advances the field of autonomous vehicle motion planning in various challenging environments, ranging from flows and planetary atmospheres to cluttered real-world scenarios. By addressing the challenge of navigating environmental flows, this work introduces the Flow-Aware Fast Marching Tree algorithm (FlowFMT*). This algorithm optimizes motion planning for unmanned vehicles, such as UAVs and AUVs, navigating in tridimensional static flows. By considering reachability constraints caused by vehicle and flow dynamics, flow-aware neighborhood sets are found and used to reduce the number of calls to the cost function. The method computes feasible and optimal trajectories from start to goal in challenging …

Design And Development Of A Smartphone App For Health Monitoring And Alerts For Farm Workers, Omer Oztoprak

Graduate Research Theses & Dissertations

This thesis presents the design and development of a novel smartphone applicationfor simultaneous health monitoring and alerts for agricultural workers using multiple wearable sensor devices via Bluetooth Low Energy (BLE). The application combines health data from a range of sensors such as an IMU that detects body movement, a pulse oximeter that captures oxygen saturation and heart rate, and a thermometer that measures body temperature. The software framework is built using Jetpack Compose in Android Studio, and it incorporates the MVVM (Model- View-ViewModel) model to provide optimized data flow and robust efficiency. By integrating the Dagger Hilt Dependency Injection framework, …

Portable Robotic Navigation Aid For The Visually Impaired, Lingqiu Jin

Theses and Dissertations

This dissertation aims to address the limitations of existing visual-inertial (VI) SLAM methods - lack of needed robustness and accuracy - for assistive navigation in a large indoor space. Several improvements are made to existing SLAM technology, and the improved methods are used to enable two robotic assistive devices, a robot cane, and a robotic object manipulation aid, for the visually impaired for assistive wayfinding and object detection/grasping. First, depth measurements are incorporated into the optimization process for device pose estimation to improve the success rate of VI SLAM's initialization and reduce scale drift. The improved method, called depth-enhanced visual-inertial …

Real-Time Motion Controller For Human-Robot Teams Utilizing Artificial Potential Fields, Gabriella Graziani

Theses and Dissertations

This thesis presents a real-time robotic motion control system for human-robot teams. The framework utilizes artificial potential fields (APFs) to guide robotic agents towards a “goal” agent while navigating around “obstacle” agents; these goals and obstacles are also dynamic agents with their own set of tasks. This system is also developed for a live-programming environment, where a controlling agent updates the tasks of all agents within the system at any time during the system’s runtime. This motion controller was created and tested for a human-robot choreographic team. After the controller was fully integrated on a Trossen Robotic LoCobot Wx200 robotic …

Alternatives To Reducing Aviation Fuel-Burn With Technology: Fully Electric Autonomous Taxibot, Denzil Neo

Student Works

Aircraft taxiing operations in the aerodrome were identified to consume the most jet fuel apart from the cruise phase of the flight. This was also well supported by various research associating taxi operations at large, congested airports, with high jet fuel consumption, high carbon emissions, and noise pollution. Existing literature recognised the potential to address the environmental issues of aerodrome taxi operations by operating External or Onboard Aircraft Ground Propulsion Systems (AGPS). Designed to power aircraft with sources other than their main engines, external Aircraft Ground Power Systems (AGPS) have shown the potential to significantly cut jet fuel consumption and …

Designing A Loving Robot: A Social Construction Analysis Of A Sex Robot Creator’S Vision, Annette Masterson

Human-Machine Communication

In 2018, one of the world’s first sex robots was released by CEO Matt McMullen and his company, RealDoll. With artificial intelligence capabilities, the Harmony model is meant to support and converse with users. Using a social construction of technology theory lens, this study develops the theory’s fourth level of analysis, emphasizing mass media’s construction abilities. A critical discourse analysis of 38 publicity interviews found a tendency to emphasize the companionship of sex robots while envisioning a future where integration is normalized, and a sentient robot is possible. As the creator, McMullen’s vision could determine the future of robotic design, …

The Evolution Of Gendered Software: Products, Scientific Reasoning, Criticism, And Tools, Victoria A. E. Kratel

Human-Machine Communication

Over the past 7 decades, gendered software has become globally established. In this theoretical distribution, I outline the evolution of gendered software. The journey of gendered software started with the raw idea fueled by Alan Turing’s imitation game in the 1950s. And only shortly thereafter, in the 1960s and 1970s, the first gendered software products like Joseph Weizenbaum’s ELIZA were developed. Thus, academia took its time to not only explore technological aspects, but to further investigate the matter of gender in the 1990s CASA-paradigm (Nass et al., 1994) and Media Equation (Reeves & Nass, 1996). As these theories reasoned the …

Do People Perceive Alexa As Gendered? A Cross-Cultural Study Of People’S Perceptions, Expectations, And Desires Of Alexa, Leopoldina Fortunati, Autumn P. Edwards, Anna Maria Manganelli, Chad Edwards, Federico De Luca

Human-Machine Communication

Mainly, the scholarly debate on Alexa has focused on sexist/anti-woman gender representations in the everyday life of many families, on a cluster of themes such as privacy, insecurity, and trust, and on the world of education and health. This paper takes another stance and explores via online survey methodology how university student respondents in two countries (the United States, n = 333; and Italy, n = 322) perceive Alexa’s image and gender, what they expect from this voice-based assistant, and how they would like Alexa to be. Results of a free association exercise showed that Alexa’s image was scarcely embodied …