用模板变量让机器人理解不确定任务，实现远程协作。
Remote Life Support Robot Interface System for Global Task Planning and Local Action Expansion Using Foundation Models
- 将不确定信息转为可填充的模板变量，指导机器人行动
- 通过提示生成与反馈机制，实现人机动态交互
- 适用于远程协助场景，提升复杂任务执行可靠性
能够根据语言指令执行任务的机器人系统正受到广泛关注。然而，仅靠单一语言指令难以向机器人传达需现场确认的不确定信息。本研究提出一种系统，将模糊内容作为语言指令中的模板变量，用于传递待采集信息及可供选择的选项，以应对可预测的不确定性事件。系统基于模板变量为每个机器人动作功能生成提示，实现信息收集；同时构建反馈机制，供用户在人机交互中呈现并选择选项。该系统的有效性通过真实生活支持任务的应用得到验证。
原文摘要 · Abstract (English)
Robot systems capable of executing tasks based on language instructions have been actively researched. It is challenging to convey uncertain information that can only be determined on-site with a single language instruction to the robot. In this study, we propose a system that includes ambiguous parts as template variables in language instructions to communicate the information to be collected and the options to be presented to the robot for predictable uncertain events. This study implements prompt generation for each robot action function based on template variables to collect information, and a feedback system for presenting and selecting options based on template variables for user-to-robot communication. The effectiveness of the proposed system was demonstrated through its application to real-life support tasks performed by the robot.
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