This paper investigates the possibility of intuitive human-robot interaction through the application of Natural Language Processing (NLP) and Large Language Models (LLMs) in mobile robotics. We aim to explore the feasibility of using these technologies for edge-based deployment, where traditional cloud dependencies are eliminated. The study specifically contrasts the performance of GPT-4-Turbo, which requires cloud connectivity, with an offline-capable, quantized version of LLaMA 2 (LLaMA 2-7B.Q5 K M). Our results show that GPT-4-Turbo delivers superior performance in interpreting and executing complex commands accurately, whereas LLaMA 2 exhibits significant limitations in consistency and reliability of command execution. Communication between the control computer and the mobile robot is established via a Raspberry Pi Pico W, which wirelessly receives commands from the computer without internet dependency and transmits them through a wired connection to the robot's Arduino controller. This study highlights the potential and challenges of implementing LLMs and NLP at the edge, providing groundwork for future research into fully autonomous and network-independent robotic systems. For video demonstrations and source code, please refer to: https://tinyurl.com/RobocupSym2024.

翻译：本文研究了通过应用自然语言处理（NLP）与大型语言模型（LLM）技术实现直观人机交互在移动机器人领域的可能性。我们旨在探索将这些技术用于边缘部署的可行性，从而消除对传统云服务的依赖。本研究特别对比了需要云端连接的GPT-4-Turbo与具备离线能力、量化版本的LLaMA 2（LLaMA 2-7B.Q5_K_M）的性能。实验结果表明，GPT-4-Turbo在准确解析与执行复杂指令方面表现更优，而LLaMA 2在指令执行的一致性与可靠性上存在显著局限。控制计算机与移动机器人之间的通信通过树莓派Pico W实现，该设备以无线方式（不依赖互联网）接收计算机指令，并通过有线连接传输至机器人的Arduino控制器。本研究揭示了在边缘端部署LLM与NLP技术的潜力与挑战，为未来实现完全自主且不依赖网络的机器人系统提供了研究基础。视频演示与源代码请访问：https://tinyurl.com/RobocupSym2024。