下一代博物馆导览员：具身智能机器人的自主导航与游客交互
Next-Gen Museum Guides: Autonomous Navigation and Visitor Interaction with an Agentic Robot
- Italian Institute of Technology（意大利理工学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出博物馆导览机器人Alter-Ego，融合大语言模型问答与SLAM自主导航，经34人实地测试验证其提升游客体验的潜力与现存局限。
AI中文摘要：
自主机器人正越来越多地被部署到公共空间以提升用户体验，尤其是在文化和教育场景中。本文介绍了自主博物馆导览机器人Alter-Ego的设计、实现与评估，该机器人配备了先进的导航和交互能力。该机器人利用最先进的大语言模型（LLMs）提供实时、上下文感知的问答（Q&A）交互，使游客能够就展品展开对话。它还采用了稳健的同步定位与建图（SLAM）技术，使其能够在博物馆空间内无缝导航，并根据用户请求进行路线调整。该系统在一个真实的博物馆环境中进行了测试，共有34名参与者，结合了对游客与机器人对话的定性分析以及对交互前后调查问卷的定量分析。结果表明，尽管在理解能力和响应速度方面存在一些局限性，该机器人总体上受到了好评，并为营造引人入胜的博物馆体验做出了贡献。本研究揭示了文化空间中人机交互（HRI）的现状，不仅凸显了人工智能驱动机器人在支持无障碍访问和知识获取方面的潜力，也指出了在复杂的真实世界环境中部署此类技术当前的局限性与挑战。
英文摘要：
Autonomous robots are increasingly being tested into public spaces to enhance user experiences, particularly in cultural and educational settings. This paper presents the design, implementation, and evaluation of the autonomous museum guide robot Alter-Ego equipped with advanced navigation and interactive capabilities. The robot leverages state-of-the-art Large Language Models (LLMs) to provide real-time, context aware question-and-answer (Q&A) interactions, allowing visitors to engage in conversations about exhibits. It also employs robust simultaneous localization and mapping (SLAM) techniques, enabling seamless navigation through museum spaces and route adaptation based on user requests. The system was tested in a real museum environment with 34 participants, combining qualitative analysis of visitor-robot conversations and quantitative analysis of pre and post interaction surveys. Results showed that the robot was generally well-received and contributed to an engaging museum experience, despite some limitations in comprehension and responsiveness. This study sheds light on HRI in cultural spaces, highlighting not only the potential of AI-driven robotics to support accessibility and knowledge acquisition, but also the current limitations and challenges of deploying such technologies in complex, real-world environments.
