Robotics Commons^™

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Digital Replica For Trustworthy Cooperative Autonomous Vehicles, Hady Farahat

Theses and Dissertations

Trust in an automated system can be defined as confidence in a vehicle's reliability, safety, and predictability, which is essential for the acceptance and widespread adoption of fully autonomous vehicles (FAVs); without it, users might disengage from using autonomous vehicles or reject the technology altogether. Most of the previous research has focused on trust from an ego vehicle perspective.

However, next-generation vehicles are becoming more autonomous and connected, relying on vehicle-to-vehicle technology and vehicle-to-infrastructure technology with no human intervention. Hence, trust becomes more complex and fragile as multiple agents interact with each other, and it might become harder to establish …

Proactive Safety Reasoning In Human-Robot Collaboration In Disassembly Through Llm-Augmented Stpa And Fmea, Morteza Jalali Alenjareghi, Fardin Ghorbani, Samira Keivanpour, Yuvin Adnarain Chinniah, Sabrina Jocelyn

Études primaires

Disassembly tasks in human–robot collaboration (HRC) environments present safety challenges due to hazardous materials, control system variability, and physically demanding operator tasks. To address these challenges, we propose an AI-augmented risk assessment framework integrating System-Theoretic Process Analysis (STPA) and Failure Mode and Effects Analysis (FMEA). This framework is implemented in four configurations: Term Frequency– Inverse Document Frequency (TF-IDF), Fine-tuned Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and RAG with a structured Knowledge Graph (KG) built from safety standards. The system supports real-time, standards-compliant safety reasoning by generating interpretable, context-specific recommendations. We evaluate these configurations across GPT-3.5 TURBO, GPT-4o, GPT-4.1, and …

Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters, N.R. Yusupbekov, Yu.Sh. Avazov, G.Kh. Rashidov

Chemical Technology, Control and Management

This scientific article investigates the problem of analyzing technological process parameters in the fields of chemistry, energy, and metallurgy based on sensor data and applying intelligent signal processing methods. The main objective is to evaluate the effectiveness of artificial intelligence and deep learning models for intelligent analysis, forecasting, and anomaly detection of data obtained from sensors. Time-series data collected from industrial sensors were analyzed using LSTM (Long Short-Term Memory) and Autoencoder neural networks, as well as the Kalman filter. At the first stage of the study, sensor signals were denoised and their true state was estimated using the Kalman filter. …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Artificial Intelligence In Surveillance And Privacy, Elizabeth D. Brasher

NEXUS: The Liberty Journal of Interdisciplinary Studies

This paper attempts to provide insight into the new and developing world of artificial intelligence and its integration into surveillance technologies. These technologies being implemented by the government, retail companies, healthcare organizations, and more, all raise ethical questions and implications addressed in this article; other topics, such as the integration of Christian ethics and responsibilities, are also explored.

Integrated Compliant Structure For A Hand Exoskeleton, Tristan R. Koopman

Honors Undergraduate Theses

This thesis presents the design and prototyping of a wearable hand exoskeleton that integrates a flexible structural framework to assist with hand movement while maintaining comfort and anatomical conformity. The goal was to create a device that supports tendon-driven actuation through a compliant structure, combining elements of rigidity and flexibility to match the natural geometry and motion of the human hand. Traditional hand exoskeletons often trade off motion for structure or vice versa. This project aims to bridge that gap with a hybrid compliant design that balances flexibility and support. The design process followed an iterative approach involving rapid prototyping …

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …

A Talking Cart, Abdullah Bin Naeem

LSU New Orleans Theses and Dissertations

This research investigates the development of a robust AI-powered detection and tracking engine aimed at revolutionizing the retail checkout experience. The foundation of this work is a comprehensive exploration of state-of-the-art Computer Vision methodologies, particularly focusing on object detection, segmentation, and tracking. The study employs a modular pipeline that integrates advanced visual recognition algorithms with a robust data processing framework.

Key to this work is the construction of a synthetic dataset using Unity3D, enabling the generation of high-quality annotated data that mirrors real-world retail scenarios. This approach addresses the challenge of insufficient labeled datasets by simulating diverse and cluttered shopping …

Authenticated Diagnosing Of Covid-19 Using Deep Learning-Based Ct Image Encryption Approach, Mohamed Attia Abdelgwad, Amira Hassan Abed, Mahmoud Bahloul

Future Computing and Informatics Journal

Researchers are motivated to use artificial intelligence in biometrics, medical imaging encryption, as well as cybersecurity due to its rapid progress. An encryption method for CT scans—which are used to diagnose COVID-19 disease—is proposed in this study. The suggested encryption method creates a connection among an individual's face picture and CT image to increase confidentiality. The simple CT picture is first enhanced with a host image. An encryption key is multiplied by the final result. This key is produced by applying a Convolutional Neural Network (CNN) to recognize characteristics from people's face photographs. Additionally, a straightforward CNN with three convolutional …

Communication Challenges In Underwater Wireless Networks: Mac Protocols And Software Solutions, Dmitrii Dugaev

Dissertations, Theses, and Capstone Projects

Underwater wireless networks (UWNs) represent a diverse and intriguing research domain, encompassing a wide array of scientific and industrial applications. This dissertation delves into the communication challenges at the Medium Access Control (MAC) layer within UWNs, stemming from the distinctive signal propagation conditions and the harshness of the deployment environment. The manuscript provides comprehensive coverage of key aspects of UWNs, including potential applications, communication protocols, methodologies employed in such networks, and existing software solutions that facilitate simulation, emulation, and real testbed scenarios for underwater research endeavors. Furthermore, this research introduces innovative software and communication solutions designed to facilitate the seamless …

Algorithms For Coordinating Multiple Autonomous Vehicles Under Various Constraints With Emphasis On Workload Balancing, Abhishek Patil

Dissertations, Master's Theses and Master's Reports

This dissertation focuses on developing algorithms to solve the problem of coordinating multiple autonomous vehicles under various constraints, aiming to produce practical solutions for real-world applications. Built upon three journal publications addressing two coordination-related problems in different domains, this research document tackles the challenges of heterogeneity constraints and cable entanglement issues encountered by autonomous vehicle systems.

The first problem tackles task allocation and path planning for heterogeneous ground mobile vehicles operating in a 2D environment with asymmetric travel costs. By enhancing previous Primal-Dual approximation heuristic methods, novel techniques are introduced to manipulate dual variables and achieve balanced workload distribution, ultimately …

Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis

Theses and Dissertations

This dissertation explores how to better manage resources in mobile networks, especially for enhancing the performance of Unmanned Aerial Vehicles (UAV)-supported IoT networks. We explored ways to set up a flexible communication architecture that can handle large IoT deployments by making good use of mobile core network resources like bearers and data paths. We developed strategies that meet the needs of IoT networks and enhance network performance. We also developed and tested a system that combines traffic from several mobile devices that use the same user identity and network resources within the core mobile network. We used everyday smartphones, SIM …

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 …

Exploring Cognition And Affect During Human-Cobot Interaction, Angelika T. Canete, Javier Gonzalez-Sanchez, Rafael Guerra Silva

College of Engineering Summer Undergraduate Research Program

Collaborative robots (Cobots) have recently gained popularity due to their capability to work collaboratively with human operators. This collaborative relationship has been named under the robotics discipline of Human-Robot Collaboration (HRC), in which humans and robots work together to accomplish a common task while also being in the same physical space. An important part of collaboration is the human's decision-making, which is largely affected by their affective and cognitive state. A cobot lacks this fundamental understanding of the human operator. In this research, we utilize a server-client program to communicate the affective states of a human user to a Raspberry …

The Heterogeneous Vehicle Routing Problem With Multiple Time Windows For The E-Waste Collection Problem, Aldy Gunawan, Minh P.K Nguyen, Vincent F. Yu, Dang Viet Anh Nguyen

Research Collection School Of Computing and Information Systems

Waste from electrical and electronic equipment (WEEE) or e-waste describes end-of-life electronic products that are discarded. Due to their toxic and negative impacts to humans' health, many publications have been proposed to handle, however, studies related to e-waste collection and transportation to waste disposal sites are not widely studied so far. This study proposes a mixed integer linear programming (MILP) model to solve the e-waste collecting problem by formulating it as the heterogeneous vehicle routing problem with multiple time windows (HVRPMTW). The model is validated with newly developed benchmark instances that are solved by commercial software, CPLEX. The model is …

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

Process Automation And Robotics Engineering For Industrial Processing Systems, Drake Stimpson

USF Tampa Graduate Theses and Dissertations

Automation in industrial systems applications has emerged as the fundamental solution for improving quality, production rate, and efficiency of a process. Much of the recent popularity surrounding the transition of processes from manually operated tasks to automated systems can be attributed to the concept of Industry 4.0, which outlines the fundamental guidelines for integrating cyber-physical systems into industrial processes. Due to rapid advancement of technology in robotics and automation as well as the increase in accessibility of resources to this technology, the capability to develop automated systems has become feasible for small-scale enterprise. This work presents a two-part initiative to …

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 …

Productivity And Quality Evaluation In Assembly Using Collaborative Robots, Carlos F. Manzanares Vega

Open Access Theses & Dissertations

In Industry 4.0, various technologies have been applied to achieve automation for traditional manufacturing and practices. For this reason, Smart Manufacturing (SM) environments utilize collaborative robots for process optimization by integrating the Internet of Things (IoT). Cobots are equipped with sensors and/or other devices to be able to transmit data in real-time while performing their tasks. Consequently, such SM implementations improves the decision making and business development, such as supply chain and operations, by sharing real-time data from a plant operational level. The collaborative robots are also designed to safely interact and collaborate with humans to perform tasks and optimize …

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …

Smartphone Control Of Rc Cars, Weston R. Fitzgerald

Electrical Engineering

The smartphone-controlled RC (remote-controlled) car is an inexpensive remote-controlled car designed to be fast and portable. Instead of manufacturing, packaging, and shipping a separate controller, the remote control is implemented in a phone application, which saves time and money in both the design process and the manufacturing process. Utilizing the user’s smartphone is more cost-effective since mobile devices are a common recurrence, and packaging fewer devices results in overall better portability of the product.

This smartphone-controlled car is speedy and intuitive to learn for typical smartphone users. The user can change the car’s speed and direction wirelessly using their phone; …

Automated Robotic Light Bulb Testing Platform, Agha I. Akram, Muhammad Ali Ummy

Publications and Research

The main purpose of this project is to create a functional prototype of a multilayered system that incorporates aspects of electrical, mechanical, and computer engineering technology. The main objective of the system is to be able to determine whether a light bulb is working or not. The building blocks of this system are a robotic arm that is able to slide along a rail (for added mobility), a conveyor belt, and an electromechanical device that holds and tests light bulbs. Initially, the robot arm picks up a light bulb and places it into the holder which then tests it. A …

A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert

Student Research

Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …

Society Dilemma Of Computer Technology Management In Today's World, Iwasan D. Kejawa Ed.D

School of Computing: Faculty Publications

Abstract - Is it true that some of the inhabitants of the world’s today are still hesitant in using computers? Research has shown that today many people are still against the use of computers. Computer technology management can be said to be obliterated by security problems. Research shows that some people in society feel reluctant or afraid to use computers because of errors and exposure of their privacy and their sophistication, which sometimes are caused by computer hackers and malfunction of the computers. The dilemma of not utilizing computer technology at all or, to its utmost, by certain people in …

Challenges Of The Industrial Revolution Era 1.0 To 5.0 : University Digital Library In Indoensia, Merlin Apriliyanti, Ilham M

Library Philosophy and Practice (e-journal)

This study explains the development of the world of libraries to establish a very close relationship with the world of information technology. For this reason, facilities and infrastructure are needed to facilitate data and information retrieval quickly and accurately. Facing the challenges of the Industrial Revolution 5.0 era by utilizing information technology, libraries must also adapt to the times. Because the library has an important role, among others, as a source of information and the development of knowledge. Used libraries are still conventional to be converted into digital libraries. In essence, this development represents the desire of library users for …

The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami

Future Computing and Informatics Journal

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …

Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban

Future Computing and Informatics Journal

The telecommunication sector has been developed rapidly and with large amounts of data obtained as a result of increasing in the number of subscribers, modern techniques, data-based applications, and services. As well as better awareness of customer requirements and excellent quality that meets their satisfaction. This satisfaction raises rivalry between firms to maintain the quality of their services and upgrade them. These data can be helpfully extracted for analysis and used for predicting churners. Researchers around the world have conducted important research to understand the uses of Data mining (DM) that can be used to predict customers' churn. This …