Computer Engineering Commons^™

Open-Source Cubesat Flight Software And Simulation, James Gruber

Computer Engineering

An open-source FreeRTOS-based flight software framework for CubeSats, with an example flight software package and simulation demonstrating real-time attitude control.

Reverse Engineering Bring Up And Profiling Of Multi-Fpga Systems, Henry A. Evans

Master's Theses

FPGAs have long been used for prototyping and verifying high-speed digital designs in industry and in academic research. As ASIC designs have grown in complexity and size, prototyping those designs on FPGAs has required multiple FPGAs that sometimes span multiple servers. Western Digital donated multiple FPGA-based systems to Cal Poly in 2023. These servers contain multiple high-end AMD FPGAs that are ideal for prototyping large high-speed digital designs, however the full documentation on how to use the servers and how the servers work was not provided. The servers did not come with any information on how to program the FPGAs, …

Assessment Of The Imx7ulp Heterogeneous Soc For Use In A Next Generation Student Cubesat Obc, Lorenzo A. Pedroza

Master's Theses

CubeSats represent a rapidly evolving platform for space research, industry, and education, demanding increasingly sophisticated onboard computing solutions that balance performance, fault tolerance, size, weight, and power constraints. Although the design of the Cal Poly's CubeSat Lab's (PolySat) current On-Board Computer (OBC) keeps up with many of these factors, the demands of modern workloads like fine attitude determination will start to outpace available compute. While the selection of a more capable processor to address this would have traditionally resulted in increased energy usage, modern system-on-chip (SoC) architectures offer novel ways to trade available compute for power savings on-the-fly. With this …

Griddle: A Novel Hardware Based Matrix Multiplier Architecture, Seth Kiefer

Master's Theses

Matrix multiplication is a computational cornerstone in modern artificial intelligence and scientific computing, yet general-purpose processors struggle to perform these operations efficiently at scale. This thesis presents Griddle, a novel hardware architecture for matrix multiplication implemented on a Xilinx Artix-7 FPGA. Griddle focuses on flexibility and scalability by adopting a purely iterative approach that supports arbitrarily shaped input matrices without requiring padding or strict dimensional constraints. The architecture uses computational pipelines to execute a multiplication operation. Each pipe consists of a multiplication core and accumulation buffer that compute matrix products in parallel. The multiplication core contains a set of multiplier …

Deeppanorf: Deep Prior For Neural 3d Reconstruction From Sparse Panoramas, Edward Du

Master's Theses

Advances in neural field representations have led to a significant improvement in view synthesis quality. However, many current novel view synthesis methods rely on a dense set of input views, which can be impractical and inefficient in real-world applications. We propose DeepPanoRF, a novel method for 360◦ scene reconstruction from a sparse set of input equirectangular panoramas. Built upon K-Planes, a radiance field representation that encodes explicit features on orthogonal feature planes, our method does not directly learn feature grids. Instead, we parameterize the feature grids to enable sparse view reconstruction without pretraining or additional regularization. We implement a custom …

Adversarial Deep Reinforcement Learning For Tank Duel Simulation Using Lidar-Based Observations, Braedan Kennedy

Master's Theses

Previous research has demonstrated that reinforcement learning agents can learn to steer differential-drive robots around obstacles using 2D lidar scans as observations. However, these studies typically treat all range returns as undifferentiated obstacles—objects to avoid—without distinguishing between different object types. This thesis builds upon previous research by introducing an adversarial task in which an agent must interpret raw range readings to both avoid static obstacles and identify, pursue, and engage a hostile target.

To investigate this problem, this thesis introduces TankGame, a novel, lightweight 2D tank duel simulator. Each agent receives a 360° lidar scan, controls its motion via tread …

Sentry V3: Extending Context Switches On A Trusted Secure Coprocessor, Mark Kong

Master's Theses

Software correctness and integrity is only ensured through trust in the un- derlying hardware. However, modern computer systems are complex to design and secure. Thus, given the choice between performance and security, companies will often prioritize performance, resulting in vulnerable systems. This creates exploitable systems that must be patched retroactively because business value performance over security. One approach to this issue is to separate the root of security from the rest of the system to create a minimal trusted computing base. Trustguard is one instance of this. Trustguard implements a Containment Architecture with Ver- ified Output (CAVO) model which shows …

Simulated Live Studio Audience, Theodore David Shellenberger

Computer Engineering

The Simulated Live Studio Audience is a Python based application that utilizes Vosk, Roboflow, and Llama 3.2 to provide a user with auditory feedback based upon both visual and audible input from their device's microphone and camera. This system functions with a custom trained computer vision model to detect a specified object and when individuals walk in and out of the camera frame, outputting sitcom style simulated crowd reaction sounds accordingly. The simulated studio audience program also takes in vocal input from users, converts it to text, and, using a large language model, analyzes it for content that can be …

Framework For Multi-Agent Coordination And Distributed Localization In Micro-Uavs, Minwoo Park, Nikolas Tambornini

Electrical Engineering

Micro-UAVs (unmanned aerial vehicles) due to their inexpensive nature and compact form factor have shown an increase in prevalence throughout a multitude of applications including, but not limited to: search and rescue, military reconnaissance, and agriculture monitoring. However, for a majority of these high impact applications, a swarm of micro-UAVs are required and furthermore mandate that they are able to cooperatively and autonomously coordinate with each other. For long, controlling and communicating between a user and a singular micro-UAV has been a well known and solved problem, however the same can't be said for swarms of micro-UAVs. This project seeks …

Autonomous Mapping Rover, Garrett Jones, Timothy Kyle Chu, Eugenio Caruso Pasos

Electrical Engineering

This report details the design, implementation, and evaluation of "Rovero," an autonomous mapping rover developed as a senior project. Rovero integrates state-of-the-art technologies, including ROS2 for communication, SLAM algorithms for mapping, and sensor fusion for accurate navigation. The project aimed to achieve robust autonomous operation in indoor environments, leveraging a combination of LiDAR, IMU, and encoder data for real-time decision-making. Key challenges addressed include path planning, obstacle avoidance, and integration of multiple sensor inputs. Results demonstrate successful mapping capabilities and efficient navigation performance.

Design Principles For Robotic-Controlled 3d Printing Of Soft Tissue-Mimicking Materials, Karina Mealey

Master's Theses

Geometrically and physically accurate 3D models are emerging as essential tools for surgeons in pre-operative planning and training, but current methods of producing these models are not sufficient. Existing solutions have downsides such as high costs, long and tedious production times, high complexity resulting in a lack of scalability, or an inability to meet material requirements for accurately simulating human tissue.

The objective of this work is to develop principles for a low-cost, easy-to-use 3D printing system capable of prototyping with soft tissue-mimicking materials. To pursue this goal, a MyCobot280 robot arm was used as the mechanism to explore the …

A Turtlebot3 Hardware Testbed For Distributed Kalman Filter Localization, Dmitri Dobrynin, Indigo T. Garcia

Electrical Engineering

This report presents the preliminary design for a distributed localization framework for a multi-robot system. Many robotics research papers provide simulations of proposed algorithms in regards to formation control and task allocation. However, it is often that these proposals are without hardware experiments, being limited only to simulation. The objective of this framework is to provide a hardware implementation of a distributed Kalman filtering algorithm for multi-agent localization, as well as provide grounds for future multi-agent experiments. The framework is implemented on a swarm of three Turtlebot3 mobile robots. The robots can accurately localize themselves with respect to other agents …

Conversational Social Robot, Julianna M. Christopoulos, Mackenzie Goldman, Cece E. Hujanen, Jared Hunter

Mechanical Engineering

Background: Social robots are used in various settings to reduce burden on human workers and expand opportunities for people in need of assistance.

Challenge: Design a humanoid robot head and torso capable of holding conversations and interacting with a user using a LLM and motion. Conversations are limited to discussing Cal Poly resources and opportunities with visitors to the Bently Research Center on campus.

Implementation Of Area-Based Aggregation On Multivariate Continuous Uncertain Data, Rahul Nair

Master's Theses

Uncertain data is incredibly widespread - from sensor data to AI-based learned information, there exists a need to associate information with a certain probability of its veracity. Traditional relational databases lack a built-in functionality to support uncertain data, instead assigning them boilerplate values. Probabilistic databases tackle this problem by assigning non-deterministic data with an associated, often discrete, probability. Variants of probabilistic databases, namely continuous uncertain databases, are used to better model data represented through ranges and distributions. This is especially applicable with sensor-based geographic data as most commercial equipment contains some inherent margin of error.

While uncertain and probabilistic databases …

Analyzing Player Difficulty Perception In Platformers Through Procedural Level Generation, Sasank Madineni

Master's Theses

Games utilizing Procedural Level Generation (PLG), such as Roguelikes, are becoming increasingly popular in today's gaming sphere. In games employing PLG, levels are generated randomly or pseudo-randomly, and aim to retain player attention through variance in levels between playthroughs. However, when generating levels with variance in structure and design, player enjoyment is often a mixed bag. With low enjoyment, player retention for these games can dwindle. This study explores the efficacy of real-time difficulty adjustment in procedurally generated platformers, as a method for maintaining stable player enjoyment without causing frustration. This thesis focuses on creating a short user experience, MIMEVA, …

Fault Tolerant Dynamic Task Allocation For Heterogeneous Multi-Robot Systems, Jack R. Cline

Master's Theses

This research presents a novel approach to dynamic task allocation in heterogeneous multi-robot systems with integrated fault detection capabilities. As multiple industries are becoming more reliant on multi-robot systems for tasks, maintaining operational efficiency despite robot failures becomes critical. We propose a framework that combines optimization-based task allocation with a Kalman filter that estimates task progress for anomaly detection to identify unreliable agents and dynamically redistribute tasks. Observing values such as the normalized innovation squared (NIS), covariance, and progress rate, the algorithm can designate a robot as faulty. Embedding information about which robots are faulty in the task algorithm allows …

Distributed Formation Control Of Nonholonomic Mobile Robots: Safety-Critical Leader-Follower Approach With Obstacle Avoidance And Dynamic Reconfiguration, Kelvin C. Villago

Master's Theses

Networked control systems for multi-agent robotics have emerged as a critical paradigm for executing complex coordinated tasks in diverse environments. While formation control serves as the backbone of such systems, real-world deployment introduces significant challenges including communication constraints, environmental obstacles, and the need for adaptive reconfiguration. This research addresses these challenges by developing a novel unified framework that seamlessly integrates obstacle avoidance algorithms with dynamic formation reconfiguration capabilities, specifically designed for communication-limited networked control architectures. The proposed framework represents a significant advancement over existing approaches by simultaneously handling both static and dynamic obstacles while maintaining system cohesion under communication constraints. …

Optimizing Web Servers With Io_Uring, Mihika Nigam

Master's Theses

Modern web servers face unprecedented demands for high throughput and low latency [10] [11]. Yet, even the state-of-the-art optimizations often fail under heavy workloads on existing infrastructure. Despite advancements in hardware, communication between applications and the kernel remains a critical bottleneck.

Industry surveys reveal that over 50% of production servers still rely on traditional epoll-based architectures [5]. This research aims to investigate and characterize Linux’s new io_uring subsystem, which has the potential to overcome these challenges. Through controlled load testing of various existing architectures like event-driven, multi-process, and multi-threaded architectures (including other commercial servers), we demonstrate how io_uring can help …

A Fault-Tolerant, Multi-Heap Dynamic Memory Allocator For Freertos, Garrett E. O'Neill

Master's Theses

The use of dynamic memory allocation presents a significant challenge for embedded systems, particularly in applications that require high reliability. The software controlling these systems needs to perform critical operations within strict timing constraints, and memory management plays a critical role in a system’s ability to meet these constraints. Dynamic memory allocation is inherently non-deterministic: if a task requests memory, it is impossible to predict how long it will take for the memory to be allocated. If a critical task were to rely on dynamically allocated memory, its execution could become stalled leading to a missed deadline and system failure. …

Open Source Asic Design Curriculum, Francisco Wilken

Master's Theses

The ever-growing importance of Application-Specific Integrated Circuits (ASICs) in a high-compute world necessitates that college graduates entering the workforce are well prepared to design them. This thesis details the design of novel ASIC curriculum, using open source tools to teach at the undergraduate level. By moving to a higher level of abstraction than classical transistor-focused coursework, chip design material can be made accessible earlier in an undergraduate degree. Additionally, open source tools provide a powerful, free, and portable platform for students to create their own designs, solving assignments focused on industry readiness. Finally, this thesis studies the results and challenges …

Aiops–Driven Adaptive Anomaly Detection In Evolving Cloud Environments Using Transfer Learning, Mayur Shivakumar

Master's Theses

As cloud-based microservice architectures have become the foundation of contempo- rary enterprise solutions, performance interference, wherein co-located services com- pete for shared resources, remains a significant challenge. This phenomenon, often referred to as the noisy neighbor problem, manifests when one workload unexpect- edly increases the CPU, memory, disk I/O, or network consumption, resulting in latency spikes or throughput degradation for other services. While existing isolation mechanisms (e.g., cgroups and QoS policies) provide some mitigation, they rarely prevent contention entirely, particularly in dynamic, rapidly evolving environments with frequent code deployments.

This thesis proposes an AIOps-driven adaptive anomaly detection framework that integrates …

Peerproxy: A Webrtc Proxy For Http, Nathan Li-En Lee

Master's Theses

Advances in networking technologies have empowered individuals to easily self-host digital services such as websites and smart home systems. However, accessing these services externally often requires port forwarding, which requires manual router configuration, technical expertise in networking, and is sometimes restricted by internet service providers. Proxy-based services such as Ngrok and Cloudflare Tunnels simplify external access by using publicly hosted proxy servers, but introduce increased infrastructure costs and privacy concerns due to reliance on third-party servers that can inspect or store traffic.

This thesis presents PeerProxy, a novel framework that simplifies access to self-hosted web services without manual network configuration, …

Efficacy Of Immersive Virtual Reality Gameplay In Environmental Attitude Change: The Case Of Abandoned Offshore Oil Platforms In Santa Barbara, Arun Prasad Srinivasan Manoharan

Master's Theses

Public perception plays an important role in shaping conservation policies and decisions, especially in contested environmental spaces. Offshore oil platforms, historically viewed as environmental hazards, have been found to serve as marine habitats that support diverse marine life. However, public perception remains largely negative, influenced by concerns over pollution from past oil spill accidents. Traditional environmental education methods, such as lectures and documentaries, often fail to engage audiences effectively or shift entrenched opinions. This study explores the efficacy of immersive Virtual Reality (VR) gameplay in changing environmental attitudes, specifically in the context of abandoned offshore oil platforms in Santa Barbara, …

Bonsai Merkle Tree Streams: Bulk Memory Verification Unit For Trusted Program Verification System, Richard J. Rios

Master's Theses

Today, all modern computing systems are undoubtedly vulnerable to numerous types of attacks that could be targeted toward any layer of the system from dedicated hardware to highly abstracted software. Unfortunately, many devices and systems naturally contain inadequately protected components or software modules that un- dermine their security as a whole. Additionally, security is heavily variable system to system, and has a huge dependence on adequate implementation and ongoing support from device and software manufacturers. To address these various security issues in a very general way, TrustGuard, a containment security system utilizing an external device called the Sentry that would …

Pseudo Gps For Romi, Emmanuel Baez, Owen Guinane, Gabriel Coria, Conor Schott

Mechanical Engineering

The Pseudo-GPS system for Romi robots addresses the need for precise real-time location tracking in Cal Poly's Mechatronics lab. This project, developed by Emmanuel Baez, Gabriel Coria, Owen Guinane, and Conor Schott, under the guidance of instructor Charlie Refvem, provides a proof-of-concept system to enhance the Romi robots' geolocation capabilities for advanced robotic algorithms.

The proposed system uses a Raspberry Pi 4 equipped with a Pi camera module and ArUco markers to track the position and orientation of Romi robots within a lab environment. Custom 3D-printed stands secure markers on the robots, and a designated origin marker defines the coordinate …

Optimizing Resume Authenticity And Ats Compatibility With Llm Feedback Integration, Katie He, Justin Lau

College of Engineering Summer Undergraduate Research Program

Resume generation using Large Language Models (LLMs) like ChatGPT is becoming increasingly popular for automating the creation of customized resumes, but significant user modification is often required before submission. Common issues include poor alignment with job descriptions, inflated qualifications, and lack of authenticity, which undermine the effectiveness of LLM-generated resumes. This project addresses these challenges by integrating feedback from Applicant Tracking Systems (ATS) to guide LLMs in producing resumes that accurately reflect an applicant’s qualifications and better align with job-specific requirements. By optimizing the model's output through ATS feedback, the project aims to create more authentic, tailored, and ATS-compatible resumes, …

Enhancing Semantic Search With Human-Crafted Knowledge In Sentence Embeddings, Zachary Weinfeld

College of Engineering Summer Undergraduate Research Program

Semantic search plays a critical role in many domains, with numerous algorithms developed to address it. A common approach involves using sentence transformers to generate embeddings for both search queries and documents, allowing for the comparison of their vectors. While many different embedding models are widely used, our approach integrates these models with human-crafted knowledge in a novel way, resulting in an improvement in the Mean Average Precision (MAP) scores. Traditional embeddings often rely heavily on the specific words used in a query or document. Our technique mitigates this dependency by refining the vectors to capture the overall semantic meaning, …

Advanced Grasping Sensor Technologies For Autonomous Robotic Apple Harvesting Using Tactile Data And Cnns, Chris Bae

College of Engineering Summer Undergraduate Research Program

This research investigates how to achieve an optimal grasp of an apple using a four-finger soft robotic grasper equipped with force-resistive sensors. Specifically, we sought to determine whether a convolutional neural network (CNN) could accurately classify the grasper's state and recommend adjustments ("in," "out," or "good" grasp) based on tactile data from the sensors. Spatiotemporal tactile images were developed from the sensors and fed into our CNN, achieving near 100% accuracy on unseen test data. This work suggests that CNN-based processing of tactile images can be a powerful tool for real-time control of soft robotic grippers.

Incorporation Of Gnss Technology For Water-Level Instruments, Armaan S. Oberai, Toma Grundler, Serena B. Lee, Stefan A. Talke

College of Engineering Summer Undergraduate Research Program

Our goal was to take an existing water-level measuring embedded system and upgrade the GNSS module for the purpose of getting the elevation of the device within an error of 1 cm. Main milestones for the project included deploying a successful field test at a known survey point, using software-based post processing to improve the GNSS solution point, and implementing robust hardware and software for the water-level embedded system such that it was easily scalable.

Ai Integration For Intellisar, Eric Lee

College of Engineering Summer Undergraduate Research Program

IntelliSAR aims to integrate AI techniques into Search and Rescue (SAR) operations, building on the foundation laid by previous SURP initiatives. IntelliSAR’s core elements include a front-end for SAR forms, a comprehensive command center dashboard, and AI-driven components designed to enhance SAR decision-making. During summer, our efforts focused on streamlining the user interface by integrating various machine learning models into a unified, interactive dashboard. Our models predict critical factors such as missing persons’ behavior, potential locations, and resource requirements, with the goal of optimizing response times and improving the effectiveness of SAR teams.