VoicePilot：利用LLMs作为物理辅助机器人的语音接口
VoicePilot: Harnessing LLMs as Speech Interfaces for Physically Assistive Robots
AI总结：
本文提出VoicePilot框架，将大型语言模型作为物理辅助机器人的语音接口，通过迭代测试和老年人评估验证其有效性，并提供设计指南。
摘要：
物理辅助机器人为运动障碍或其他形式残疾、无法完成日常生活活动的个体提供了显著提升福祉和独立性的机会。语音接口，尤其是利用大型语言模型（LLMs）的语音接口，能够使个体有效且自然地传达高级指令和细微偏好给机器人。已有研究提出了将LLMs集成作为机器人接口用于高级任务规划和代码生成的框架，但这些框架未能纳入以人为本的考量，而这些考量在开发辅助接口时至关重要。在本工作中，我们提出了一个将LLMs作为物理辅助机器人语音接口的框架，该框架通过3个阶段的测试迭代构建，涉及一个喂食机器人，最终在独立生活设施中对11名老年人进行了评估。我们利用最终研究中的定量和定性数据来验证我们的框架，并额外提供了使用LLMs作为辅助机器人语音接口的设计指南。视频和支持文件位于我们的项目网站：https://sites.google.com/andrew.cmu.edu/voicepilot/
英文摘要：
Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who are unable to complete activities of daily living. Speech interfaces, especially ones that utilize Large Language Models (LLMs), can enable individuals to effectively and naturally communicate high-level commands and nuanced preferences to robots. Frameworks for integrating LLMs as interfaces to robots for high level task planning and code generation have been proposed, but fail to incorporate human-centric considerations which are essential while developing assistive interfaces. In this work, we present a framework for incorporating LLMs as speech interfaces for physically assistive robots, constructed iteratively with 3 stages of testing involving a feeding robot, culminating in an evaluation with 11 older adults at an independent living facility. We use both quantitative and qualitative data from the final study to validate our framework and additionally provide design guidelines for using LLMs as speech interfaces for assistive robots. Videos and supporting files are located on our project website: https://sites.google.com/andrew.cmu.edu/voicepilot/
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
