将大模型引入医疗机器人，提升人机交互与智能决策能力
The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare
- 结合大模型与医疗机器人，实现多模态交互与语义理解
- 提出面向医疗场景的机器人系统设计需求与任务规划框架
- 探讨伦理挑战与未来研究方向，适合医疗AI与机器人交叉研究者
大型语言模型（LLMs）在医疗领域的应用有望缓解全球老龄化带来的医疗系统压力以及医护人员短缺问题。尽管LLMs已用于辅助临床医生和患者，但在医疗机器人中的集成尚未在临床环境中深入探索。本文从系统性视角分析机器人与大模型的前沿进展，聚焦于通过人机交互（HRIs）实现多模态通信、语义推理与任务规划等关键能力，提出面向医疗场景的专用大模型驱动机器人所需的核心系统要求。同时，讨论该新兴领域面临的伦理问题、开放挑战及潜在研究方向。
原文摘要 · Abstract (English)
The potential use of large language models (LLMs) in healthcare robotics can help address the significant demand put on healthcare systems around the world with respect to an aging demographic and a shortage of healthcare professionals. Even though LLMs have already been integrated into medicine to assist both clinicians and patients, the integration of LLMs within healthcare robots has not yet been explored for clinical settings. In this perspective paper, we investigate the groundbreaking developments in robotics and LLMs to uniquely identify the needed system requirements for designing health specific LLM based robots in terms of multi modal communication through human robot interactions (HRIs), semantic reasoning, and task planning. Furthermore, we discuss the ethical issues, open challenges, and potential future research directions for this emerging innovative field.
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