Hardware Systems Commons^™

The Integration Of Neuromorphic Computing In Autonomous Robotic Systems, Md Abu Bakr Siddique

Dissertations, Master's Theses and Master's Reports

Deep Neural Networks (DNNs) have come a long way in many cognitive tasks by training on large, labeled datasets. However, this method has problems in places with limited data and energy, like when planetary robots are used or when edge computing is used [1]. In contrast to this data-heavy approach, animals demonstrate an innate ability to learn by communicating with their environment and forming associative memories among events and entities, a process known as associative learning [2-4]. For instance, rats in a T-maze learn to associate different stimuli with outcomes through exploration without needing labeled data [5]. This learning paradigm …

Statically Controlled Synchronized Lane Architectures, Scott K. Pomerville

Dissertations, Master's Theses and Master's Reports

Modern superscalar processors dominate the field of computing. While dynamic execution allows for versatility in code, these processors are complex. Statically scheduled code has historically enabled simpler processor designs, but static scheduling cannot account for variables that are unknown at compile time. Furthermore, static scheduling has many inefficiencies, such as the need to insert a large number of nops for code in traditional Very Long Instruction Word (VLIW) processors. In this dissertation, we explore a novel architectural approach for statically scheduled code by breaking the code into several synchronous instruction streams. By representing code in a fundamentally new way, we …

Implementing Associative Learning Using Neuromorphic Robot, Vinay Kumar Pillalamarri

Dissertations, Master's Theses and Master's Reports

Associative learning, a key cognitive process seen across the animal kingdom, enables organisms to form connections between stimuli and adapt their behaviors based on past experiences. A particularly powerful example is fear conditioning, where animals learn to associate a neutral stimulus with an aversive one, allowing them to predict and avoid potential threats. Inspired by this mechanism, this project implements associative learning on an unmanned ground vehicle (UGV) to develop adaptive behavior through neuromorphic principles. Utilizing Nengo for neural modeling, the UGV learns to associate visual (red color) and tactile (vibration) stimuli through Hebbian learning, a biologically inspired synaptic adaptation …

Adapting Deep Learning For Underwater Acoustic Communication Channel Modeling, Li Wei

Dissertations, Master's Theses and Master's Reports

The recent emerging applications of novel underwater systems lead to increasing demand for underwater acoustic (UWA) communication and networking techniques. However, due to the challenging UWA channel characteristics, conventional wireless techniques are rarely applicable to UWA communication and networking. The cognitive and software-defined communication and networking are considered promising architecture of a novel UWA system design. As an essential component of a cognitive communication system, the modeling and prediction of the UWA channel impulse response (CIR) with deep generative models are studied in this work.

Firstly, an underwater acoustic communication and networking testbed is developed for conducting various simulations and …

Integration Of Robotic And Electro-Pneumatic Systems Using Advanced Control And Communication Schemes, Chinmay Kondekar

Dissertations, Master's Theses and Master's Reports

Modern industrial automation systems are designed by interconnecting various subsystems which work together to perform a process. The thesis project aims to integrate fragmented subsystems into a flexible and reconfigurable system through advanced communication protocols and perform a process to demonstrate the effectiveness of interconnected systems.

The system consists of three six-axis robots, one electro-pneumatic robot, and two conveyors connected using EthernetIP communication and hardwired connections. The interconnected system works together to perform machining of a workpiece using advanced control methods of CAD to robot path generation, central control through a PLC, and process control through HMI.

Standardized programming blocks …

Demand-Driven Execution Using Future Gated Single Assignment Form, Omkar Javeri

Dissertations, Master's Theses and Master's Reports

This dissertation discusses a novel, previously unexplored execution model called Demand-Driven Execution (DDE), which executes programs starting from the outputs of the program, progressing towards the inputs of the program. This approach is significantly different from prior demand-driven reduction machines as it can execute a program written in an imperative language using the demand-driven paradigm while extracting both instruction and data level parallelism. The execution model relies on an executable Single Assignment Form which serves both as the internal representation of the compiler as well as the Instruction Set Architecture (ISA) of the machine. This work develops the instruction set …

Investigation Of The Use Of 3-D Printer Platform As Building Block For Rapid Design Of Research And Manufacturing Tool, Handy Chandra

Dissertations, Master's Theses and Master's Reports

This thesis attempts to show how an open source 3-D printer platform, the self replicating rapid prototype (RepRap), could be used to accelerate the development of research and manufacturing tools. Two projects are shown as examples, both utilizing components of the 3-D printer platform.

The first project is to develop an instrument capable of performing automated large-area four-point probe measurements. A modified RepRap 3-D Printer with a four-point probe in place of the 3-D printer head is utilized as a precision positioning platform. The printer together with custom designed measurement circuit and software performs automated measurement on multiple points on …

Design Automation For Carbon Nanotube Circuits Considering Performance And Security Optimization, Lin Liu

Dissertations, Master's Theses and Master's Reports

As prevailing copper interconnect technology advances to its fundamental physical limit, interconnect delay due to ever-increasing wire resistivity has greatly limited the circuit miniaturization. Carbon nanotube (CNT) interconnects have emerged as promising replacement materials for copper interconnects due to their superior conductivity. Buffer insertion for CNT interconnects is capable of improving circuit timing of signal nets with limited buffer deployment. However, due to the imperfection of fabricating long straight CNT, there exist significant unidimensional-spatially correlated variations on the critical CNT geometric parameters such as the diameter and density, which will affect the circuit performance.

This dissertation develops a novel timing …

Open Source Database And Website To Provide Free And Open Access To Inactive U.S. Patents In The Public Domain, Yuenyong Nilsiam, Joshua M. Pearce

Department of Materials Science and Engineering Publications

Although theoretically the patent system is meant to bolster innovation, the current United States Patent and Trademark Office (USPTO) is cumbersome and involves a significant time investment to locate inactive patents less than 20 years old. This article reports on the development of an open source database to find these public domain ideas. First, a search strategy is explained. Then the operation and use of free and open source software are detailed to meet the needs of open hardware innovators. Finally, a case study is presented to demonstrate the utility of the approach with 3-D printing. The results showed how …