Due to monumental advancements in large language models (LLMs), such as OpenAI's ChatGPT, there is widespread interest in integrating this general AI’s capabilities into various applications, including robotics. However, the rush to deploy this technology has left safety as an afterthought, if at all. This study investigates the potential for LLM-fused robots to operate safely in real-world settings. This study begins with a review of ChatGPT, highlighting its capabilities and current challenges, particularly with integrating LLMs into robotics, and continues with similar applications as AI agents though APIs. To assess the safety implications of LLM-driven robots, the study presents experimental methods involving the navigation of a TurtleSim robot in 2D environments when given different scenarios. Various parameters are analyzed to determine the current capabilities of ChatGPT to understand how to adjust any agents it possesses based on the situation. Current findings reveal that ChatGPT-driven robots demonstrate adaptive behavior based on the scenario provided, indicating their potential for real-time safety adjustments and eliciting further research to ensure safe and successful integration of these robots into diverse work environments.

Manufacturing production is limited by three main factors, cost, both overall and on a per unit basis, final product quality, and process repeatability or frequency. Even producing small objects through the casting of epoxy resin, a liquid substance capable of hardening when in contact with a catalyst material presents these same issues. There are three distinct areas of epoxy resin casting influenced by each of these manufacturing factors, the material used to create molds, the air process applied to minimize defects, and resin demold time. This investigation was designed to determine the impact the three factors of manufacturing production have on the casting epoxy resin. Each category had numerous tests conducted to determine the best combination of production in terms of low cost, high quality, and high levels of repeatability. Ultimately, the best combination was the use of a platinum silicone called Mold Star 15, a pressure chamber, and an epoxy resin with a 12-hour cure time, called Amazing Resin. The final cost to create 100 products is $410.85. However, it should be noted for the highest quality dice, the utilization of a pressure chamber is required while the mold materials are interchangeable.

Bicycles and motorcycles offer maneuverability, energy efficiency and acceleration that four wheeled vehicles cannot offer given similar budget for. Two wheeled vehicles have drastically different dynamics from four wheeled vehicles due to their instability and gyroscopic effect from their wheels.

This thesis focuses on self-stabilization of a motorcycle using an active control momentum gyroscope (CMG) and validation of this multi-degree-of-freedom system’s mathematical model. Physical platform was created to mimic the simulation as accurately as possible and all components used were justified. This process involves derivation of a 3 Degree-of-Freedom (DOF) system’s forward kinematics and its Jacobian matrix, simulation analysis of different controller algorithms, setting the system and subsystem specifications, and real system experimentation and data analysis.

A Jacobian matrix was used to calculate accurately decomposed resultant angular velocities which are used to create the dynamics model of the system torque using the Euler-Lagrange method. This produces a nonlinear second order differential equation that is modeled using MATLAB/Simulink. PID, and cascaded feedback loop are tested in this Simulink model. Cascaded feedback loop shows most promises in the simulation analysis. Therefore, system specifications are calculated according to the data produced by this controller method. The model validation is executed using the Vicon motion capture system which captured the roll angle of the motorcycle. This work contributes to creating a set of procedures for creating a validated dynamic model for a CMG stabilized motorcycle which can be used to create variants of other self-stabilizing motorcycle system.