Engineering Commons^™

Precision Grasp Planning For Integrated Arm-Hand Systems, Shuwei Qiu

Electronic Thesis and Dissertation Repository

The demographic shift has caused labor shortages across the world, and it seems inevitable to rely on robots more than ever to fill the widening gap in the workforce. The robotic replacement of human workers necessitates the ability of autonomous grasping as the most natural but rather a vital part of almost all activities. Among different types of grasping, fingertip grasping attracts much attention because of its superior performance for dexterous manipulation. This thesis contributes to autonomous fingertip grasping in four areas including hand-eye calibration, grasp quality evaluation, inverse kinematics (IK) solution of robotic arm-hand systems, and simultaneous achievement of …

Leveraging Machine Learning Techniques Towards Intelligent Networking Automation, Cesar A. Gomez

Electronic Thesis and Dissertation Repository

In this thesis, we address some of the challenges that the Intelligent Networking Automation (INA) paradigm poses. Our goal is to design schemes leveraging Machine Learning (ML) techniques to cope with situations that involve hard decision-making actions. The proposed solutions are data-driven and consist of an agent that operates at network elements such as routers, switches, or network servers. The data are gathered from realistic scenarios, either actual network deployments or emulated environments. To evaluate the enhancements that the designed schemes provide, we compare our solutions to non-intelligent ones. Additionally, we assess the trade-off between the obtained improvements and the …

Mechanical Design And Development Of A Compliant 5-Dof Manipulator Using Magneto-Rheological Actuators, Sergey Pisetskiy

Electronic Thesis and Dissertation Repository

Compliance in robotic systems became a very important and desirable characteristic in recent years. Existing compliant actuation approaches have either limited performance or significant mechanical and control complexity. Keeping high performance while maintaining the necessary level of compliance at low cost and minimum complexity is a challenging goal that should be achieved to boost the propagation of human-safe robots and systems capable to perform delicate tasks in an unknown environment.

This study presents a novel five degrees-of-freedom compliant manipulator. The compliancy of the manipulator is achieved using antagonistically working pairs of magneto-rheological (MR) clutches in each joint of the robot. …

Visual Cues For Semi-Autonomous Control Of Transradial Prosthetics, Mena S.A. Kamel

Electronic Thesis and Dissertation Repository

Upper-limb prosthetics are typically driven exclusively by biological signals, mainly electromyography (EMG), where electrodes are placed on the residual part of an amputated limb. In this approach, amputees must control each arm joint iteratively, in a proportional manner. Research has shown that sequential control of prosthetics usually imposes a cognitive burden on amputees, leading to high abandonment rates. This thesis presents a control system for upper-limb prosthetics, leveraging a computer vision module capable of simultaneously predicting objects in a scene, their segmentation mask, and a ranked list of the optimal grasping locations. The proposed system shares control with an amputee, …

Deep Learning For High-Impedance Fault Detection And Classification, Khushwant Rai

Electronic Thesis and Dissertation Repository

High-Impedance Faults (HIFs) are a hazard to public safety but are difficult to detect because of their low current amplitude and diverse characteristics. Supervised machine learning techniques have shown great success in HIF detection; however, these approaches rely on resource-intensive signal processing techniques and fail in presence of non-HIF disturbances and even for scenarios not included in training data. This thesis leverages unsupervised learning and proposes a Convolutional Autoencoder framework for HIF Detection (CAE-HIFD). In CAE-HIFD, Convolutional Autoencoder learns only from HIF signals by employing cross-correlation; consequently, eliminating the need for diverse non-HIF scenarios in training. Furthermore, this thesis proposes …

A Black-Box Approach For Containerized Microservice Monitoring In Fog Computing, Shi Chang

Electronic Thesis and Dissertation Repository

The goal of the Internet of Things (IoT) is to convert the physical world into a smart space in which physical objects, called things, are equipped with computing and communication capabilities. Those things can connect with anything, anyone at any time, any space via any network or service. The predominant Internet of Things (IoT) system model today is cloud centric. This model introduces latencies into the application execution, as data travels first upstream for processing and secondly the results, i.e., control commands, travel downstream to the devices. In contrast with the cloud-model, the cloud-fog-based model pushes computing capability to the …

A Technique For Evaluating The Health Status Of A Software Module Using Process Metrics, . Ria

Electronic Thesis and Dissertation Repository

Identifying error-prone files in large software systems has been an area where significant attention has been paid over the years. In this thesis, we propose a process-metrics based method for predicting the health status of a file based on its commit profile in its GitHub repository. Precisely, for each file and each bug fixing commit a file participates, we compute a dependency score of the committed file with its other co-committed files. The calculated score is appropriately decayed if the file does not participate in the new bug-fixing commits in the system. By examining the trend of the dependency score …

Development Of A Wearable Haptic Feedback Device For Upper Limb Prosthetics Through Sensory Substitution, Marco B.S. Gallone

Electronic Thesis and Dissertation Repository

Haptics can enable a direct communication pipeline between the artificial limb and the brain; adding haptic sensory feedback for prosthesis wearers is believed to improve operation without drawing too much of the user's attention. Through neuroplasticity, the brain can become more cognizant of the information delivered through the skin and may eventually interpret it as inherently as other natural senses. In this thesis, a wearable haptic feedback device (WHFD) is developed to communicate prosthesis sensory information. A 14-week, 6-stage, between subjects study was created to investigate the learning trajectory as participants were stimulated with haptic patterns conveying joint proprioception. 37 …

Deep Neural Networks For Human Activity Recognition With Wearable Sensors, Davoud Gholamiangonabadi

Electronic Thesis and Dissertation Repository

Human Activity Recognition (HAR) has been attracting significant research attention because of a wide range of applications from healthcare to security. Recently, deep learning approaches have demonstrated great success in the HAR area. However, these models are often evaluated on the same subjects as those used to train the model; thus, the provided accuracy estimates do not pertain to new subjects. Consequently, this thesis examines the generalization capability of different machine learning architectures using Leave-One-Subject-Out Cross-Validation (LOSOCV) and then proposes a personalized model. The accuracy is improved by considering two feature selection directions, time- and frequency-domain, and by dynamically selecting …