Robotics Commons^™

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 …

Hand Movement Analysis For Surgical Suturing Skill Assessment, Amir Mehdi Shayan

All Theses

To enhance patient safety, surgical education is increasingly incorporating simulation for formative skills assessment and training. However, many standardized assessment tools rely on human raters for performance assessment, which is resource-intensive and subjective. Simulators that provide automated and objective metrics from sensor data can address this limitation. This thesis presents an instrumented bench suturing simulator, patterned after the Clock Face (CF) radial suturing model from the Fundamentals of Vascular Surgery (FVS), for automated and objective assessment of open suturing skills by particularly focusing on biomechanical analysis of hand movements. For this research, 97 participants (35 attending surgeons and fellows, 32 …

Developing Resilient Defense Strategies Against Pheromone-Based Attacks In Foraging Robot Swarms, Ryan A. Luna

Theses and Dissertations

This thesis delves into the security of stochastic pheromone-based foraging algorithms within swarm robotic systems, a subset of foraging algorithms distinguished by their reliance on probabilistic decision-making mechanisms inspired by the natural world. Such algorithms face vulnerabilities in stigmergic communication that threaten to disrupt swarm operations. This research investigates these vulnerabilities, presenting two distinct contributions.

The first contribution examines the implementation of quarantine strategies as a defensive measure to isolate and mitigate the impact of fake resource attacks. By simulating these attacks, this study quantitatively assesses their detrimental effects on swarm efficiency and explores the efficacy …

Human-Machine Communication: Complete Volume. Volume 7 Special Issue: Mediatization

Human-Machine Communication

This is the complete volume of HMC Volume 7. Special Issue on Mediatization

Artificial Sociality, Simone Natale, Iliana Depounti

Human-Machine Communication

This article proposes the notion of Artificial Sociality to describe communicative AI technologies that create the impression of social behavior. Existing tools that activate Artificial Sociality include, among others, Large Language Models (LLMs) such as ChatGPT, voice assistants, virtual influencers, socialbots and companion chatbots such as Replika. The article highlights three key issues that are likely to shape present and future debates about these technologies, as well as design practices and regulation efforts: the modelling of human sociality that foregrounds it, the problem of deception and the issue of control from the part of the users. Ethical, social and cultural …

Mediatization And Human-Machine Communication: Trajectories, Discussions, Perspectives, Andreas Hepp, Göran Bolin, Andrea L. Guzman, Wiebke Loosen

Human-Machine Communication

As research fields, mediatization and Human-Machine Communication (HMC) have distinct historical trajectories. While mediatization research is concerned with the fundamental interrelation between the transformation of media and communications and cultural and societal changes, the much younger field of HMC delves into human meaning-making in interactions with machines. However, the recent wave of “deep mediatization,” characterized by an increasing emphasis on general communicative automation and the rise of communicative AI, highlights a shared interest in technology’s role within human interaction. This introductory article examines the trajectories of both fields, demonstrating how mediatization research “zooms out” from overarching questions of societal and …

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

Doctoral Dissertations and Master's Theses

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

State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems, Chris Hays

Doctoral Dissertations and Master's Theses

Resiliency in multi-agent system navigation is reliant on the inherent ability of the system to withstand, overcome, or recover from adverse conditions and disturbances. In large part, resiliency is achieved through reducing the impact of critical failure points to the success and/or performance of the system. In this view, decentralized multi-agent architectures have become an attractive solution for multi-agent navigation, but decentralized architectures place the burden of information acquisition directly on the agents themselves. In fact, the design of distributed estimators has been a growing interest to enable complex multi-sensor/multi-agent tasks. In such scenarios, it is important that each local …

Human Motion-Inspired Inverse Kinematics Algorithm For A Robotics-Based Human Upper Body Model, Urvish Trivedi

USF Tampa Graduate Theses and Dissertations

The goal of this research is to develop a human motion-inspired inverse kinematics algorithm framework specifically designed for a Robotics-Based Human Upper Body Model (RHUBM). This framework offers solutions to challenges in various fields. In humanoid robotics, the framework addresses the problem of unnatural robot movement by enabling the development of motion planning algorithms that incorporate human-like movements. For prosthetics, the framework tackles the challenge of amputee difficulty in learning and controlling prosthetics by providing a user-friendly interface that predicts and visualizes upper limb movements, enabling learning and practice. In rehabilitation therapy, the framework tackles …

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 …

Love Machina, John C. Lyden

Journal of Religion & Film

This is a film review of Love Machina (2024), directed by Peter Sillen.

Securing Edge Computing: A Hierarchical Iot Service Framework, Sajan Poudel, Nishar Miya, Rasib Khan

Posters-at-the-Capitol

Title: Securing Edge Computing: A Hierarchical IoT Service Framework

Authors: Nishar Miya, Sajan Poudel, Faculty Advisor: Rasib Khan, Ph.D.

Department: School of Computing and Analytics, College of Informatics, Northern Kentucky University

Abstract:

Edge computing, a paradigm shift in data processing, faces a critical challenge: ensuring security in a landscape marked by decentralization, distributed nodes, and a myriad of devices. These factors make traditional security measures inadequate, as they cannot effectively address the unique vulnerabilities of edge environments. Our research introduces a hierarchical framework that excels in securing IoT-based edge services against these inherent risks.

Our secure by design approach prioritizes …

A Framework-Based Cross-Institutional Cpd For Academic Staff In Gen-Ai Literacy, Critical Inquiry And Authentic Assessment, Roisin Donnelly, Ita Kennelly

Books/Book Chapters

Generative-Artificial Intelligence (Gen-AI) has emerged as a transformative force profoundly influencing, if not revolutionizing the way we now teach and how students learn in higher education (HE). Despite the initial flurry of early research studies following the raising of public awareness of Gen-AI (and in particular ChatGPT), enduring pragmatic questions remain for academic staff on how best to protect and promote student learning, how to meaningfully support assessment integrity from a curriculum perspective, and additionally how to effectively use Gen-AI technologies to aid learning and foster deeper critical thinking.

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 …

Algorithms For Safe And Robust Motion Control Of Autonomous Ground Robots And Vehicles, Manavendra Desai

Wayne State University Dissertations

This dissertation explores, investigates, develops and experimentally validates algorithms for safe and robust motion control of ground robots and vehicles. The emphasis is on design of controllers for ground autonomy with safety either embedded by design or enforced by appropriately wrapping a safety net around an existing nominal controller.

Ground robots have been considered for their importance in compensating for labour or personnel shortage for material handling in the manufacturing, logistics and healthcare sectors. On the other hand, ground vehicles have been considered for the existing potential of making driver assistance systems safer and more intelligent, particularly in at-the-limit driving …

Manifold Learning In Robotics: A Tutorial And Survey, Marcus Hawkins

Computer Science and Engineering Theses - Archive

In this article, we hope to represent the current state of the art of manifold learning in an understandable and approachable way. The authors will present a general overview core algorithms associated with linear and nonlinear dimensionality reduction techniques, give rudimentary definitions from differential geometry, and tenets of robotic perception, manipulation and path planning. Some of the historical applications of these algorithms will be presented, as well as conjectures about future uses, through examples from peer-reviewed journals.

A Learning-Based Framework For Autonomous Robotic Operations In Resource-Denied Environments, Joseph M. Cloud

Computer Science and Engineering Dissertations - Archive

Establishing a sustained human presence beyond Earth necessitates the development of autonomous systems capable of extracting and utilizing local resources. On the Moon, in-situ resource utilization (ISRU) is essential to reduce the dependency on Earth-based supplies. Leveraging lunar resources such as water ice for life support and fuel production or regolith for surface construction will enable long-term lunar missions and future deep space exploration. NASA's Artemis program is targeting the lunar south pole (LSP), an area with raw, yet abundant resources available. The harsh environmental conditions present significant challenges for humans operating and installing surface infrastructure. Autonomous robotic systems are …

Magnetometer-Less State-Estimation Of A Mobile Robot Using Cascaded Kalman Filters, Tommy Le

Graduate Research Theses & Dissertations

Localization, or state-estimation algorithms, are one of the most important aspects inthe development of autonomous mobile robots. Typical localization requires an IMU (Inertial Measurement Unit) along with an external reference, such as GPS (Global Positioning System) for outdoor applications. In indoor applications, the GPS data is not accessible so many mobile robot implementations turn to magnetometers to provide additional pose information. However, in the context of miniaturizing robotic systems, magnetometers are not always reliable due to their proximity to motors and other electronics, causing magnetic distortion and in turn, incorrect pose information. To address this issue, this thesis proposes a …

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 …

An Approach For Robotic Pollination That Utilizes Imitation Learning, Ronald Michael Butts Ii

Graduate Theses, Dissertations, and Problem Reports (ETD)

The global decline in pollinator populations poses a significant threat to agriculture, motivating the development of robotic pollination systems. Previous works demonstrated successful robotic pollination of bramble flowers using visual servoing; however, pollination was limited to specific flower orientations. As such, the objective of this work is to develop a robotic pollination system that is capable of pollinating a wider range of orientations.

This research introduces an imitation learning-based framework for robotic pollination that positions the manipulator to view chosen flowers in specific orientations. The developed model leverages object detection (YOLOv8) to identify individual flowers and a convolutional neural network …