RI: Small: Natural Language-Based Human Instruction for Task Embedded Robots

RI：小型：基于自然语言的任务嵌入式机器人人类指令

• 批准号: 1218932
• 负责人: Manuela Veloso
• 金额: $ 30万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1218932&HistoricalAwards=false
• 关键词: RI; Small; Natural; Language; Based

This project will advance the scientific state of the art in social service robots by introducing a novel approach for performing, composing, and correcting tasks using spatial language, and for handling the challenges of long-term interaction with people. The team of investigators will leverage prior work on CoBot service robots as a scientific platform. CoBots can transport objects, deliver messages, escort people and go to places, continuously executing these tasks over multiple weeks in a multi-floor building. The team will collaborate to research, develop, and evaluate algorithms for learning, composing, and correcting the execution of tasks via natural language. The proposed research will enable any person to train the robot; we will use the CoBot robots to perform evaluation and testing of our proposed algorithms.The vision of a continuously operating robot in a real-world environment that can update its behavior in response to human instruction will have a broad impact on the way students, faculty and visitors interact with and view the usefulness of robots. Some examples include: (1) Customizable intelligent robots will give people the creative power to simply and intuitively update robot behavior, making the system broadly accessible to non-experts. (2) Outreach to the community will transform the view that robots are static unchangeable systems by creating an awareness towards robots co-inhabiting our environment. We will invite children of different age groups and people from different cultures to interact with our co-robot through language-based instruction. (3) Synergistic activities across multiple research groups have and will continue to be explored and encouraged (e.g., continuous environmental measurement and monitoring).

该项目将通过引入一种使用空间语言执行、编写和纠正任务的新方法，以及处理与人长期互动的挑战，来推进社会服务机器人的科学发展水平。研究团队将利用CoBot服务机器人的前期工作作为科学平台。协作机器人可以运输物体、传递信息、护送人员和前往某个地方，在多层建筑物中连续数周执行这些任务。该团队将合作研究、开发和评估用于通过自然语言学习、编写和纠正任务执行的算法。我们将使用CoBot机器人对我们提出的算法进行评估和测试。在现实环境中持续运行的机器人的愿景可以根据人类指令更新其行为，这将对学生、教师和游客与机器人的互动方式产生广泛影响。一些例子包括：（1）可定制的智能机器人将赋予人们创造力，使其能够简单直观地更新机器人行为，从而使系统广泛地为非专家所用。(2)对社区的宣传将改变机器人是静态不可改变的系统的观点，通过创造对机器人共同居住在我们的环境中的意识。我们将邀请不同年龄段的儿童和来自不同文化的人通过基于语言的教学与我们的合作机器人互动。(3)已经并将继续探索和鼓励跨多个研究小组的协同活动（例如，持续的环境测量和监测）。