Implementation of Natural Language UAV Control Using OpenAI's ChatGPT in a Simulated University Environment

This study explores how Microsoft AirSim and OpenAI's Natural Language Processing capabilities can enable drone navigation within a campus simulation. Utilizing Unreal Engine, we create a 3D simulation of Georgia State University's campus to investigate language-based drone control. Our implementation integrates three key technologies: (1) Microsoft's AirSim platform for simulating drone physics, (2) OpenAI's ChatGPT API for natural language interpretation and command processing, and (3) a detailed campus environment within Unreal Engine. This integration replaces traditional drone control interfaces, allowing users to operate simulated drones through natural language instructions. By translating user commands into navigation directions, this technology showcases the practical applications of language models. Our findings indicate that this approach enhances campus navigation simulations and provides a secure environment for testing drone operations in urban settings. This study highlights the potential of combining language processing with drone control systems, particularly in educational simulations.