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Full-Text Articles in Electrical and Computer Engineering

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries Jan 2023

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …


Adapting Deep Learning For Underwater Acoustic Communication Channel Modeling, Li Wei Jan 2022

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 Jan 2021

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 …


Estimation Of Atmospheric Conditions Over A Long Horizontal Path Using Multi-Frame Blind Deconvolution (Mfbd) Techniques In Comparison With Delayed Tilt Anisoplanatism (Delta) Software, Hannah Stoll Jan 2020

Estimation Of Atmospheric Conditions Over A Long Horizontal Path Using Multi-Frame Blind Deconvolution (Mfbd) Techniques In Comparison With Delayed Tilt Anisoplanatism (Delta) Software, Hannah Stoll

Dissertations, Master's Theses and Master's Reports

The potential to track and view objects in space from the ground with greater near real time knowledge of the intervening turbulence would be a revolutionary capability. The objective of this thesis is to cross-validate two separate methods used to estimate the Fried parameter. This verification is a step toward a commercial grade product that would make real-time estimates of the turbulence strength along an optical path from a ground-based observatory to a satellite in orbit around the Earth. Michigan Technological University has developed a multi-frame blind deconvolution (MFBD) algorithm used to estimate r0 and it was tested against MZA’s …


Video Frame Reduction In Autonomous Vehicles, Gaurav R. Bagwe Jan 2018

Video Frame Reduction In Autonomous Vehicles, Gaurav R. Bagwe

Dissertations, Master's Theses and Master's Reports

Camera sensors are emerging in many applications such as Smart Buildings and autonomous driving. The Data generated by multiple cameras in a smart building and autonomous driving applications is usually transmitted through an edge box to a cloud terminal. This transmitted information requires a considerable channel bandwidth, which is not available through current communication standards. The report proposes a Camera Sensor Frame Reduction method to decrease the required channel bandwidth for applications such as autonomous driving.

Here, we propose a method that incorporates cross frame similarity measurement method to reduce the redundant frames and decrease the data rate of each …


Cyber-Based Contingency Analysis And Insurance Implications Of Power Grid, Zhiyuan Yang Jan 2018

Cyber-Based Contingency Analysis And Insurance Implications Of Power Grid, Zhiyuan Yang

Dissertations, Master's Theses and Master's Reports

Cybersecurity for power communication infrastructure is a serious subject that has been discussed for a decade since the first North American Electric Reliability Corporation (NERC) critical infrastructure protection (CIP) initiative in 2006. Its credibility on plausibility has been evidenced by attack events in the recent past. Although this is a "very high impact, rare probability" event, the establishment of quantitative measures would help asset owners in making a series of investment decisions. First, this dissertation tackles attackers' strategies based on the current communication architecture between remote IP-based (unmanned) power substations and energy control centers. Hypothetically, the identification of intrusion paths …


Anomaly Inference Based On Heterogeneous Data Sources In An Electrical Distribution System, Yachen Tang Jan 2018

Anomaly Inference Based On Heterogeneous Data Sources In An Electrical Distribution System, Yachen Tang

Dissertations, Master's Theses and Master's Reports

Harnessing the heterogeneous data sets would improve system observability. While the current metering infrastructure in distribution network has been utilized for the operational purpose to tackle abnormal events, such as weather-related disturbance, the new normal we face today can be at a greater magnitude. Strengthening the inter-dependencies as well as incorporating new crowd-sourced information can enhance operational aspects such as system reconfigurability under extreme conditions. Such resilience is crucial to the recovery of any catastrophic events. In this dissertation, it is focused on the anomaly of potential foul play within an electrical distribution system, both primary and secondary networks as …


Performance Comparison Of Binarized Neural Network With Convolutional Neural Network, Lopamudra Baruah Jan 2017

Performance Comparison Of Binarized Neural Network With Convolutional Neural Network, Lopamudra Baruah

Dissertations, Master's Theses and Master's Reports

Deep learning is a trending topic widely studied by researchers due to increase in the abundance of data and getting meaningful results with them. Convolutional Neural Networks (CNN) is one of the most popular architectures used in deep learning. Binarized Neural Network (BNN) is also a neural network which consists of binary weights and activations. Neural Networks has large number of parameters and overfitting is a common problem to these networks. To overcome the overfitting problem, dropout is a solution. Randomly dropping some neurons along with its connections helps to prevent co-adaptations which finally help in reducing overfitting. Many researchers …


Feature And Decision Level Fusion Using Multiple Kernel Learning And Fuzzy Integrals, Anthony Pinar Jan 2017

Feature And Decision Level Fusion Using Multiple Kernel Learning And Fuzzy Integrals, Anthony Pinar

Dissertations, Master's Theses and Master's Reports

The work collected in this dissertation addresses the problem of data fusion. In other words, this is the problem of making decisions (also known as the problem of classification in the machine learning and statistics communities) when data from multiple sources are available, or when decisions/confidence levels from a panel of decision-makers are accessible. This problem has become increasingly important in recent years, especially with the ever-increasing popularity of autonomous systems outfitted with suites of sensors and the dawn of the ``age of big data.'' While data fusion is a very broad topic, the work in this dissertation considers …


Position Control Of An Unmanned Aerial Vehicle From A Mobile Ground Vehicle, Astha Tiwari Jan 2017

Position Control Of An Unmanned Aerial Vehicle From A Mobile Ground Vehicle, Astha Tiwari

Dissertations, Master's Theses and Master's Reports

Quadcopters have been developed with controls providing good maneuverability, simple mechanics, and the ability to hover, take-off and land vertically with precision. Due to their small size, they can get close to targets of interest and furthermore stay undetected at lower heights. The main drawbacks of a quadcopter are its high-power consumption and payload restriction, due to which, the number of onboard sensors is constrained. To overcome this limitation, vision-based localization techniques and remote control for the quadcopter are essential areas of current research. The core objective of this research is to develop a closed loop feedback system between an …


3d Printing, Open-Source Technology And Their Applications In Research, Chenlong Zhang Jan 2015

3d Printing, Open-Source Technology And Their Applications In Research, Chenlong Zhang

Dissertations, Master's Theses and Master's Reports

Open-source software received tremendous success as it drives down the cost of software and expand the distribution. Open-source hardware, as part of the open-source movement, has just risen into public attention for its potential to further drive down the cost of all kinds of manufacturing goods and reshape the manufacture chain. In this report we explores the history, development and the future of open-source hardware project, summarizing the opportunities, challenges and possible solutions. 3D printing is demonstrated as a booster to assist open-source hardware’s development. Low-cost 3D printer enables at-home and in-time fabrication, the download-print-use-improve-distribute cycle is established to encourage …