用大模型让无人机听懂人话，实现自然语言控制。
Integrating Large Language Models for UAV Control in Simulated Environments: A Modular Interaction Approach
- 构建模块化交互框架，将大模型接入无人机控制系统。
- 在仿真环境中验证了自然语言指令的可行响应，提升操控直观性。
- 适合对智能飞行、人机交互感兴趣的开发者与研究者。
大语言模型（LLM）与无人飞行器（UAV）技术的融合是极具潜力的研究方向，有望显著提升无人机的自主能力。本文探讨了将大语言模型应用于无人机控制的可能性，重点在于通过先进自然语言处理技术增强自主空中系统的能力。通过使无人机能够理解并响应自然语言指令，大模型简化了操作流程，扩大了用户群体，并促进更直观的人机交互。论文分析了大模型在自主决策、动态任务规划、态势感知和安全协议等方面的应用前景。基于现有大模型与主流机器人仿真平台的集成，展示了概念验证结果。研究指出，尽管面临技术和伦理挑战，但该融合方案为复杂环境中无人机系统的智能化发展提供了重要方向。
原文摘要 · Abstract (English)
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.
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