Computer Engineering Commons^™

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 …

A Study Of Random Partitions Vs. Patient-Based Partitions In Breast Cancer Tumor Detection Using Convolutional Neural Networks, Joshua N. Ramos

Master's Theses

Breast cancer is one of the deadliest cancers for women. In the US, 1 in 8 women will be diagnosed with breast cancer within their lifetimes. Detection and diagnosis play an important role in saving lives. To this end, many classifiers with varying structures have been designed to classify breast cancer histopathological images. However, randomly partitioning data, like many previous works have done, can lead to artificially inflated accuracies and classifiers that do not generalize. Data leakage occurs when researchers assume that every image in a dataset is independent of each other, which is often not the case for medical …

Identifying And Minimizing Underspecification In Breast Cancer Subtyping, Jonathan Cheuk-Kiu Tang

Master's Theses

In the realm of biomedical technology, both accuracy and consistency are crucial to the development and deployment of these tools. While accuracy is easy to measure, consistency metrics are not so simple to measure, especially in the scope of biomedicine where prediction consistency can be difficult to achieve. Typically, biomedical datasets contain a significantly larger amount of features compared to the amount of samples, which goes against ordinary data mining practices. As a result, predictive models may fail to find valid pathways for prediction during training on such datasets. This concept is known as underspecification.

Underspecification has been more accepted …

A Nano-Drone Safety Architecture, Connor J. Sexton

Master's Theses

As small-form factor drones grow more intelligent, they increasingly require more sophisticated capabilities to record sensor data and system state, ensuring safe and improved operation. Already regulations for black boxes, electronic data recorders (EDRs), for determining liabilities and improving the safety of large-form factor autonomous vehicles are becoming established. Conventional techniques use hardened memory storage units that conserve all sensor (visual) and system operational state; and N-way redundant models for detecting uncertainty in system operation. For small-form factor drones, which are highly limited by weight, power, and computational resources, these techniques become increasingly prohibitive. In this paper, we propose a …

Impact Of Teaching Practices And Communication Climates On Participation In Computer Science Education, Jackie Krone

Master's Theses

One way to understand teaching is to view it as a people process rather than a presentation of knowledge. It follows that the role of an educator often extends beyond the primary subject matter and into the realm of classroom management. With this in mind, our research aimed to capture the various teaching practices, participation patterns, and communication climates that occur in virtual computer science classrooms. We sought to answer the following research questions related to virtual computer science classrooms at our institution: Who participates in virtual computer science classrooms, and is participation proportional to student demographics? Is there any …

An Analysis Of Camera Configurations And Depth Estimation Algorithms For Triple-Camera Computer Vision Systems, Jared Peter-Contesse

Master's Theses

The ability to accurately map and localize relevant objects surrounding a vehicle is an important task for autonomous vehicle systems. Currently, many of the environmental mapping approaches rely on the expensive LiDAR sensor. Researchers have been attempting to transition to cheaper sensors like the camera, but so far, the mapping accuracy of single-camera and dual-camera systems has not matched the accuracy of LiDAR systems. This thesis examines depth estimation algorithms and camera configurations of a triple-camera system to determine if sensor data from an additional perspective will improve the accuracy of camera-based systems. Using a synthetic dataset, the performance of …

Scalable Cognitive Radio Network Testbed In Real Time, Kevin Z. Yu

Master's Theses

Modern society places an increasingly high demand on data transmission. Much of that data transmission takes place through communication over the frequency spectrum. The channels on the spectrum are limited resources. Researchers realize that at certain times of day some channels are overloaded, while others are not being fully utilized. A spectrum management system may be beneficial to remedy this efficiency issue. One of the proposed systems, Cognitive Radio Network (CRN), has progressed over the years thanks to studies on a wide range of subjects, including geolocation, data throughput rate, and channel handoff selection algorithm, which provide fundamental support for …

Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le

Master's Theses

In this thesis, the viability of decentralized, noncooperative multi-robot path planning algorithms is tested. Three algorithms based on the Batch Informed Trees (BIT*) algorithm are presented. The first of these algorithms combines Optimal Reciprocal Collision Avoidance (ORCA) with BIT*. The second of these algorithms uses BIT* to create a path which the robots then follow using an artificial potential field (APF) method. The final algorithm is a version of BIT* that supports replanning. While none of these algorithms take advantage of sharing information between the robots, the algorithms are able to guide the robots to their desired goals, with the …

Involuntary Signal-Based Grounding Of Civilian Unmanned Aerial Systems (Uas) In Civilian Airspace, Keith Conley

Master's Theses

This thesis investigates the involuntary signal-based grounding of civilian unmanned aerial systems (UAS) in unauthorized air spaces. The technique proposed here will forcibly land unauthorized UAS in a given area in such a way that the UAS will not be harmed, and the pilot cannot stop the landing. The technique will not involuntarily ground authorized drones which will be determined prior to the landing. Unauthorized airspaces include military bases, university campuses, areas affected by a natural disaster, and stadiums for public events. This thesis proposes an early prototype of a hardware-based signal based involuntary grounding technique to handle the problem …

An Application Of Sliding Mode Control To Model-Based Reinforcement Learning, Aaron Thomas Parisi

Master's Theses

The state-of-art model-free reinforcement learning algorithms can generate admissible controls for complicated systems with no prior knowledge of the system dynamics, so long as sufficient (oftentimes millions) of samples are available from the environ- ment. On the other hand, model-based reinforcement learning approaches seek to leverage known optimal or robust control to reinforcement learning tasks by mod- elling the system dynamics and applying well established control algorithms to the system model. Sliding-mode controllers are robust to system disturbance and modelling errors, and have been widely used for high-order nonlinear system control. This thesis studies the application of sliding mode control …

Utilizing Trajectory Optimization In The Training Of Neural Network Controllers, Nicholas Kimball

Master's Theses

Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum …

Multi-Vector Tracking Of Wifi And Zigbee Devices, Calvin Andrew Laverty

Master's Theses

Location privacy preservation has shifted to the forefront of discussions about next generation wireless networks. While pseudonym-changing schemes have been proposed to preserve an individual's privacy, simulation has shown that new association attack models render these schemes useless. The major contribution of this thesis is the implementation of a tracking network with commodity hardware on the California Polytechnic State University campus which leverages the combination of de-anonymization strategies on captured wireless network data to show the effectiveness of a pseudonym-changing scheme for wireless identification across WiFi and Zigbee protocols.

Smart Dc Wall Outlet Design With Improved Load Voltage Detection, Patrick Donovon Granieri

Master's Theses

A standard home in the United States has access to the 120V AC power grid for use with home appliances. Many electronics used at home are powered by a DC power supply, which loses energy in the conversion from AC power. The DC House project avoids any conversion between AC and DC by storing energy in batteries as DC power and supplying it directly to DC appliances. While AC systems feature a standardized output voltage, no such standard exists for DC systems. The Smart DC Wall Outlet solves this by automatically adjusting its output voltage to meet any required DC …

Logging, Visualization, And Analysis Of Network And Power Data Of Iot Devices, Neal Huynh Nguyen

Master's Theses

There are approximately 23.14 billion IoT(Internet of Things) devices currently in use worldwide. This number is projected to grow to over 75 billion by 2025. Despite their ubiquity little is known about the security and privacy implications of IoT devices. Several large-scale attacks against IoT devices have already been recorded.

To help address this knowledge gap, we have collected a year’s worth of network traffic and power data from 16 common IoT devices. From this data, we show that we can identify different smart speakers, like the Echo Dot, from analyzing one minute of power data on a shared power …

Corridor Navigation For Monocular Vision Mobile Robots, Matthew James Ng

Master's Theses

Monocular vision robots use a single camera to process information about its environment. By analyzing this scene, the robot can determine the best navigation direction. Many modern approaches to robot hallway navigation involve using a plethora of sensors to detect certain features in the environment. This can be laser range finders, inertial measurement units, motor encoders, and cameras.

By combining all these sensors, there is unused data which could be useful for navigation. To draw back and develop a baseline approach, this thesis explores the reliability and capability of solely using a camera for navigation. The basic navigation structure begins …

Artificial Neural Network-Based Robotic Control, Justin Ng

Master's Theses

Artificial neural networks (ANNs) are highly-capable alternatives to traditional problem solving schemes due to their ability to solve non-linear systems with a nonalgorithmic approach. The applications of ANNs range from process control to pattern recognition and, with increasing importance, robotics. This paper demonstrates continuous control of a robot using the deep deterministic policy gradients (DDPG) algorithm, an actor-critic reinforcement learning strategy, originally conceived by Google DeepMind. After training, the robot performs controlled locomotion within an enclosed area. The paper also details the robot design process and explores the challenges of implementation in a real-time system.

Towards Autonomous Localization Of An Underwater Drone, Nathan Sfard

Master's Theses

Autonomous vehicle navigation is a complex and challenging task. Land and aerial vehicles often use highly accurate GPS sensors to localize themselves in their environments. These sensors are ineffective in underwater environments due to signal attenuation. Autonomous underwater vehicles utilize one or more of the following approaches for successful localization and navigation: inertial/dead-reckoning, acoustic signals, and geophysical data. This thesis examines autonomous localization in a simulated environment for an OpenROV Underwater Drone using a Kalman Filter. This filter performs state estimation for a dead reckoning system exhibiting an additive error in location measurements. We evaluate the accuracy of this Kalman …

Developing, Evaluating, And Demonstrating An Open Source Gateway And Mobile Application For The Smartfarm Decision Support System, Caleb D. Fink

Master's Theses

The purpose of this research is to design, develop, evaluate, and demonstrate an open source gateway and mobile application for the SmartFarm open source decision support system to improve agricultural stewardship, environmental conservation, and provide farmers with a system that they own. There are very limited options for an open source gateway for collecting data on the farm. The options available are: expensive, require professional maintenance, are not portable between systems, improvements are made only by the manufacturer, limited in customization options, difficult to operate, and data is owned by the company rather than the farmer. The gateway is designed …

Vehicle Pseudonym Association Attack Model, Pierson Yieh

Master's Theses

With recent advances in technology, Vehicular Ad-hoc Networks (VANETs) have grown in application. One of these areas of application is Vehicle Safety Communication (VSC) technology. VSC technology allows for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that enhance vehicle safety and driving experience. However, these newly developing technologies bring with them a concern for the vehicular privacy of drivers. Vehicles already employ the use of pseudonyms, unique identifiers used with signal messages for a limited period of time, to prevent long term tracking. But can attackers still attack vehicular privacy even when vehicles employ a pseudonym change strategy? The major contribution …

The Design, Building, And Testing Of A Constant On Discreet Jammer For The Ieee 802.15.4/Zigbee Wireless Communication Protocol, Alexandre J. Marette

Master's Theses

As wireless protocols become easier to implement, more products come with wireless connectivity. This latest push for wireless connectivity has left a gap in the development of the security and the reliability of some protocols. These wireless protocols can be used in the growing field of IoT where wireless sensors are used to share information throughout a network. IoT is being implemented in homes, agriculture, manufactory, and in the medical field. Disrupting a wireless device from proper communication could potentially result in production loss, security issues, and bodily harm. The 802.15.4/ZigBee protocol is used in low power, low data rate, …

A Lidar Based Semi-Autonomous Collision Avoidance System And The Development Of A Hardware-In-The-Loop Simulator To Aid In Algorithm Development And Human Studies, Thomas F. Stevens

Master's Theses

In this paper, the architecture and implementation of an embedded controller for a steering based semi-autonomous collision avoidance system on a 1/10^th scale model is presented. In addition, the development of a 2D hardware-in-the-loop simulator with vehicle dynamics based on the bicycle model is described. The semi-autonomous collision avoidance software is fully contained onboard a single-board computer running embedded GNU/Linux. To eliminate any wired tethers that limit the system’s abilities, the driver operates the vehicle at a user-control-station through a wireless Bluetooth interface. The user-control-station is outfitted with a game-controller that provides standard steering wheel and pedal controls along …

An Investigation Into Partitioning Algorithms For Automatic Heterogeneous Compilers, Antonio M. Leija

Master's Theses

Automatic Heterogeneous Compilers allows blended hardware-software solutions to be explored without the cost of a full-fledged design team, but limited research exists on current partitioning algorithms responsible for separating hardware and software. The purpose of this thesis is to implement various partitioning algorithms onto the same automatic heterogeneous compiler platform to create an apples to apples comparison for AHC partitioning algorithms. Both estimated outcomes and actual outcomes for the solutions generated are studied and scored. The platform used to implement the algorithms is Cal Poly’s own Twill compiler, created by Doug Gallatin last year. Twill’s original partitioning algorithm is chosen …

Telepresence: Design, Implementation And Study Of An Hmd-Controlled Avatar With A Mechatronic Approach, Darren Michael Chan

Master's Theses

Telepresence describes technologies that allow users to remotely experience the sensation of being present at an event without being physically present. An avatar exists to represent the user whilst in a remote location and is tasked to collect stimuli from its immediate surroundings to be delivered to the user for consumption. With the advent of recent developments in Virtual Reality technology, viz., head-mounted displays (HMDs), new possibilities have been enabled in the field of Telepresence. The main focus of this thesis is to develop a solution for visual Telepresence, where an HMD is used to control the direction of a …

Synthetic Aperture Radar: Rapid Detection Of Target Motion In Matlab, Daniel S. Kassen

Master's Theses

Synthetic Aperture Radar (SAR) has come into widespread use in several civilian and military applications. The focus of this paper is the military application of imaging point targets captured by an airborne SAR platform. Using the traditional SAR method of determining target motion by analyzing the difference between subsequent images takes a relatively large amount of processing resources. Using methods in this thesis, target motion can be estimated before even a single image is obtained, reducing the amount of time and power used by a significantly large amount. This thesis builds on work done by Brain Zaharri and David So. …

Mos Current Mode Logic (Mcml) Analysis For Quiet Digital Circuitry And Creation Of A Standard Cell Library For Reducing The Development Time Of Mixed Signal Chips, David Marusiak

Master's Theses

Many modern digital systems use forms of CMOS logical implementation due to the straight forward design nature of CMOS logic and minimal device area since CMOS uses fewer transistors than other logic families. To achieve high-performance requirements in mixed-signal chip development and quiet, noiseless circuitry, this thesis provides an alternative toCMOSin the form of MOS Current Mode Logic (MCML). MCML dissipates constant current and does not produce noise during value changing in a circuit CMOS circuits do. CMOS logical networks switch during clock ticks and with every device switching, noise is created on the supply and ground to deal with …

High-Speed Mobile Networks For Modern Farming And Agricultural Systems, Santos Najar

Master's Theses

ABSTRACT

High-Speed Mobile Networks for Modern Farming and Agricultural Systems

J.Santos Najar-Ramirez

High-speed mobile networks are necessary for agriculture to inventory individual plant health, maximize yield and minimize the resources applied. More specifically, real-time information on individual plant status is critical to decisions regarding the management of resources reserved and expended. This necessity can be met by the availability of environmental sensors (such as humidity, temperature, and pH) whose data is kept on storage servers connected to static and mobile local area networks. These static and mobile local area networks are connected to cellular, core and satellite networks. For …

A Comparison Of Image Processing Techniques For Bird Detection, Elsa Reyes

Master's Theses

Orchard fruits and vegetable crops are vulnerable to wild birds and animals. These wild birds and animals can cause critical damage to the produce. Traditional methods of scaring away birds such as scarecrows are not long-term solutions but short-term solutions. This is a huge problem especially near areas like San Luis Obispo where there are vineyards. Bird damage can be as high as 50% for grapes being grown in vineyards. The total estimated revenue lost annually in the 10 counties in California due to bird and rodent damage to 22 selected crops ranged from $168 million to $504 million (in …

Virtual Reality Engine Development, Varun Varahamurthy

Master's Theses

With the advent of modern graphics and computing hardware and cheaper sensor and display technologies, virtual reality is becoming increasingly popular in the fields of gaming, therapy, training and visualization. Earlier attempts at popularizing VR technology were plagued by issues of cost, portability and marketability to the general public. Modern screen technologies make it possible to produce cheap, light head-mounted displays (HMDs) like the Oculus Rift, and modern GPUs make it possible to create and deliver a seamless real-time 3D experience to the user. 3D sensing has found an application in virtual and augmented reality as well, allowing for a …

Design Of A Low Power Cargo Security Device Using A Micropower Ultra-Wideband Impulse Radar, Brian M. Wihl

Master's Theses

Each year, thousands of cargo containers are broken into during shipping, costing billions of dollars in lost and damaged goods. In addition to removing its contents, intruders can also add unwanted and dangerous materials to a container, posing a threat to National Security. The possibilities of cargo container break-ins require that the containers go through check points at which they are physically searched. These searches often require the opening of the container, unloading and inspecting all cargo, and then loading the container and resealing it. This is a long and costly process.

Because of the high costs of break-ins and …

Digital Control Board For Phased Array Antenna Beam Steering In Adaptive Communication Applications, Mayur Bansal

Master's Theses

The application of adaptive communication techniques for mobile communications has attracted considerable interest in the last decade. One example of these techniques is spatial filtering through planar antenna array beam forming.

This thesis describes the development of a digital system that adaptively controls a phased array antenna. The radiating structure of the phased antenna array is tetrahedral-shaped and contains four antenna elements on each of its three faces. The overall system comprises of a digital control board with an external computer interface, an RF control board, and the phased antenna array. The RF controls the main lobe direction on the …