Open Access. Powered by Scholars. Published by Universities.®

Robotics Commons™

Open Access. Powered by Scholars. Published by Universities.®

1,248 Full-Text Articles 2,009 Authors 809,970 Downloads 141 Institutions

All Articles in Robotics

Faceted Search

1,248 full-text articles. Page 19 of 58.

Reference Frames In Human Sensory, Motor, And Cognitive Processing, Dongcheng He 2023 University of Denver

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 2023 Texas A & M University - Commerce

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 2023 American University in Cairo

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 2023 Northern Kentucky University

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 2023 Marshall University

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 2023 University of Denver

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 2023 Technological University Dublin, Ireland

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 2023 Georgia Southern University

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 2023 Georgia Southern University

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 2023 Virginia Commonwealth University

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 2023 University of Kentucky

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 2023 CUNY, City College

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 2023 Technological University Dublin

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 2023 Michigan Technological University

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 2023 Michigan Technological University

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, …


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 2023 Old Dominion University

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 2023 The University of Akron

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 2023 Pepperdine University

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 2023 The University of Akron

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, …


Imitation Learning For Swarm Control Using Variational Inference, Hafeez Olafisayo Jimoh 2023 West Virginia University

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 …


Digital Commons powered by bepress