Robotics Commons^™

Mosaic Swarm Robotics: Emulating Natural Collective Behaviors For Efficient Task Execution With Custom Mobile Robots, Jonathan Ridley, Arielle Charles, Charles Koduru, Muhammad Hassan Tanveer, Razvan Voicu

Symposium of Student Scholars

Mosaics, as an artistic expression, involves the meticulous arrangement of diverse tiles to form a unified composition. Drawing inspiration from this concept, the field of swarm robotics seeks to emulate nature’s collective behaviors observed in ant colonies, fish schools, and bird flocks, employing multiple agents to accomplish tasks efficiently. Our research explores the concept of mosaic swarm robotics, where numerous nodes with specialized functions are deployed across various domains, including applications for outdoor data capture and environment mapping. We utilized custom mobile robots operated by Raspberry Pi microcontrollers. By establishing an elaborate web of client-to-client communications to enable true localized …

Securing The Skies: Safety-Constrained Decentralized Multi-Uav Coordination With Deep Reinforcement Learning, Jean-Elie Pierre

Electrical and Computer Engineering ETDs

In the dynamic landscape of autonomous aerial systems, the integration of uncrewed aerial vehicles (UAVs) has sparked a paradigm shift, offering unprecedented opportunities and challenges in collaborative decision-making and navigation. This thesis explores the application of multi-agent reinforcement learning (MARL) for the planning and coordination of UAVs in complex environments.

The first part of this thesis provides an introduction to single-agent reinforcement learning and MARL. We provide examples of the use of MARL for countering uncrewed aerial systems (C-UAS). We formulate the Counter-UAS problem as a multiagent partially observable Markov decision process (MAPOMDP), and we propose Multi-AGent partial observable deep …

Generalized Model To Enable Zero-Shot Imitation Learning For Versatile Robots, Yongshuai Wu

Master's Theses

The rapid advancement in Deep Learning (DL), especially in Reinforcement Learning (RL) and Imitation Learning (IL), has positioned it as a promising approach for a multitude of autonomous robotic systems. However, the current methodologies are predominantly constrained to singular setups, necessitating substantial data and extensive training periods. Moreover, these methods have exhibited suboptimal performance in tasks requiring long-horizontal maneuvers, such as Radio Frequency Identification (RFID) inventory, where a robot requires thousands of steps to complete.

In this thesis, we address the aforementioned challenges by presenting the Cross-modal Reasoning Model (CMRM), a novel zero-shot Imitation Learning policy, to tackle long-horizontal robotic …

Flexible Strain Gauge Sensors As Real-Time Stretch Receptors For Use In Biomimetic Bpa Muscle Applications, Rochelle Jubert

Student Research Symposium

This work presents a novel approach to real-time length sensing for biomimetic Braided Pneumatic Actuators (BPAs) as artificial muscles in soft robotics applications. The use of artificial muscles enables the development of more interesting robotic designs that no longer depend on single rotation joints controlled by motors. Developing robots with these capabilities, however, produces more complexities in control and sensing. Joint encoders, the mainstay of robotic feedback, can no longer be used, so new methods of sensing are needed to get feedback on muscle behavior to implement intelligent controls. To address this need, flexible strain gauge sensors from Portland company, …

Simulating And Training Autonomous Rover Navigation In Unity Engine Using Local Sensor Data, Christopher Pace

Senior Honors Theses

Autonomous navigation is essential to remotely operating mobile vehicles on Mars, as communication takes up to 20 minutes to travel between the Earth and Mars. Several autonomous navigation methods have been implemented in Mars rovers and other mobile robots, such as odometry or simultaneous localization and mapping (SLAM) until the past few years when deep reinforcement learning (DRL) emerged as a viable alternative. In this thesis, a simulation model for end-to-end DRL Mars rover autonomous navigation training was created using Unity Engine, using local inputs such as GNSS, LiDAR, and gyro. This model was then trained in navigation in a …

Multi-Domain Secure Dds Networks For Aerial And Ground Vehicle Communications, Daniel Pendleton

All Theses

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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) …

Design And Development Of A Radiation Survey And Rescue Robot With Shielding Of Electronic Equipment From Radiation Damage With Image Radiation Mapping Facility, Md. Sifatul Muktadir, Md. Nazmul Hassan, Md. Saimon Siddique, Dewan Nazmun Nur, Altab Hossain, Ahnaf Tahmid Chowdhury

International Journal of Nuclear Security

The use of remote-controlled robots in emergency fields is a necessary requirement at present, which includes the nuclear engineering field because the radioactive environment creates adverse effects on human health. This work describes the development of a remotely controlled rover capable of detecting ionizing radiation, isolating radiation sources using a robotic arm, and sufficient shielding for its internal components. A custom-made Geiger–Muller counter has been used to detect ionizing radiation. The radioactive environment is not only harmful for humans but also can cause severe damage to the electronic circuit mounted on the robot. Therefore, a custom concrete material sandwiched between …

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 …

Investigating Autonomous Ground Vehicles For Weed Elimination, Abraham Mitchell

Computer Science and Computer Engineering Undergraduate Honors Theses

The management of weeds in crop fields is a continuous agricultural problem. The use of herbicides is the most common solution, but herbicidal resistance decreases effectiveness, and the use of herbicides has been found to have severe adverse effects on human health and the environment. The use of autonomous drone systems for weed elimination is an emerging solution, but challenges in GPS-based localization and navigation can impact the effectiveness of these systems. The goal of this thesis is to evaluate techniques for minimizing localization errors of drones as they attempt to eliminate weeds. A simulation environment was created to model …

Particle Swarm Optimization For Training Quadrotor Pid Controller, Eric Xavier Rodriguez

Theses and Dissertations

The objective of this research is to establish a fundamental approach to tuning PID (Proportional-Integral-Derivative) parameters for a simulated quadrotor drone. Implementing a PID controller for autonomous flight provides a straightforward and efficient method for monitoring and correcting robotic movement based on the robot's current state. However, applying a PID approach to a quadrotor's flight controller poses challenges, such as assigning multiple parameters to control an inherently under-actuated system. This includes the need to find optimal parameter values that reduce the likelihood of large overshoots and lengthy adjustment times. Ineffectively tuning PID parameters can have detrimental effects on autonomously …

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 …

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 …

Deep Learning Using Vision And Lidar For Global Robot Localization, Brett E. Gowling

Master's Theses

As the field of mobile robotics rapidly expands, precise understanding of a robot’s position and orientation becomes critical for autonomous navigation and efficient task performance. In this thesis, we present a snapshot-based global localization machine learning model for a mobile robot, the e-puck, in a simulated environment. Our model uses multimodal data to predict both position and orientation using the robot’s on-board cameras and LiDAR sensor. In an effort to minimize localization error, we explore different sensor configurations by varying the number of cameras and LiDAR layers used. Additionally, we investigate the performance benefits of different multimodal fusion strategies while …

Mav Localization In Gps-Denied Environments And Synthetic Data Collection In Challenging Simulated Conditions, Julio A. Reyes Munoz

Open Access Theses & Dissertations

The development of unmanned aerial systems presents an opportunity for conducting industrial inspections in environments where traditional navigation systems, such as the Global Navigation Satellite System (GNSS), are compromised. This dissertation investigates the implementation of a micro aerial vehicle (MAV) capable of autonomous data acquisition in complex, GNSS-degraded industrial settings. The primary challenge addressed is the robust localization of MAVs, a critical aspect in ensuring reliable operation under varying and uncertain environmental conditions.

The work is divided into two main parts. The first part focuses on the design and integration of a MAV system specifically for power plant inspections in …

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 …

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.