The intersection of LLMs (Large Language Models) and UAV (Unoccupied Aerial Vehicles) technology represents a promising field of research with the potential to enhance UAV capabilities significantly. This study explores the application of LLMs in UAV control, focusing on the opportunities for integrating advanced natural language processing into autonomous aerial systems. By enabling UAVs to interpret and respond to natural language commands, LLMs simplify the UAV control and usage, making them accessible to a broader user base and facilitating more intuitive human-machine interactions. The paper discusses several key areas where LLMs can impact UAV technology, including autonomous decision-making, dynamic mission planning, enhanced situational awareness, and improved safety protocols. Through a comprehensive review of current developments and potential future directions, this study aims to highlight how LLMs can transform UAV operations, making them more adaptable, responsive, and efficient in complex environments. A template development framework for integrating LLMs in UAV control is also described. Proof of Concept results that integrate existing LLM models and popular robotic simulation platforms are demonstrated. The findings suggest that while there are substantial technical and ethical challenges to address, integrating LLMs into UAV control holds promising implications for advancing autonomous aerial systems.

翻译：大型语言模型（LLMs）与无人机（UAVs）技术的交叉领域是一个前景广阔的研究方向，有望显著提升无人机的能力。本研究探讨了LLMs在无人机控制中的应用，重点关注将先进自然语言处理技术集成到自主空中系统中的机遇。通过使无人机能够理解和响应自然语言指令，LLMs简化了无人机的控制与使用，使其能够被更广泛的用户群体所接受，并促进了更直观的人机交互。本文讨论了LLMs可能影响无人机技术的几个关键领域，包括自主决策、动态任务规划、增强态势感知以及改进安全协议。通过对当前进展和未来潜在方向的全面综述，本研究旨在阐明LLMs如何变革无人机操作，使其在复杂环境中更具适应性、响应性和效率。文中还描述了一个用于集成LLMs到无人机控制的模板开发框架，并展示了集成现有LLM模型与主流机器人仿真平台的概念验证结果。研究结果表明，尽管存在大量技术和伦理挑战有待解决，将LLMs集成到无人机控制中对于推进自主空中系统的发展具有重要的积极意义。