This paper introduces a "proof of concept" for a new approach to assistive robotics, integrating edge computing with Natural Language Processing (NLP) and computer vision to enhance the interaction between humans and robotic systems. Our "proof of concept" demonstrates the feasibility of using large language models (LLMs) and vision systems in tandem for interpreting and executing complex commands conveyed through natural language. This integration aims to improve the intuitiveness and accessibility of assistive robotic systems, making them more adaptable to the nuanced needs of users with disabilities. By leveraging the capabilities of edge computing, our system has the potential to minimize latency and support offline capability, enhancing the autonomy and responsiveness of assistive robots. Experimental results from our implementation on a robotic arm show promising outcomes in terms of accurate intent interpretation and object manipulation based on verbal commands. This research lays the groundwork for future developments in assistive robotics, focusing on creating highly responsive, user-centric systems that can significantly improve the quality of life for individuals with disabilities.

翻译：本文提出了一种辅助机器人技术的新方法"概念验证"，通过将边缘计算与自然语言处理（NLP）及计算机视觉技术相结合，以增强人类与机器人系统之间的交互。我们的"概念验证"展示了联合使用大语言模型（LLMs）和视觉系统来解析与执行自然语言复杂指令的可行性。该集成方案旨在提升辅助机器人系统的直观性与可访问性，使其能更好地适应残障用户的细微需求。通过利用边缘计算能力，本系统有望降低延迟并支持离线操作，从而增强辅助机器人的自主性与响应能力。在机器人手臂上实施的实验结果表明，该系统在基于语音指令的意图准确解析与物体操控方面取得了良好成效。本研究为辅助机器人技术的未来发展奠定了基础，重点关注创建高响应性、以用户为中心的系统，从而显著改善残障人士的生活质量。