NRI-Small: Contextually Grounded Collaborative Discourse for Mediating Shared Basis in Situated Human Robot Dialogue

NRI-Small：基于情境的协作话语，用于调解情境人类机器人对话中的共享基础

• 批准号: 1208390
• 负责人: Joyce Chai
• 金额: $ 95.7万
• 依托单位: Michigan State 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: 2012-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1208390&HistoricalAwards=false
• 关键词: NRI; Small; Contextually; Grounded; Collaborative

In human robot dialogue, although human partners and robots are co-present in a shared environment, they have completely mismatched capabilities in perceiving and reasoning about the environment. Their knowledge and representations of the shared world are drastically different. In addition, the shared environment is full of uncertainties and unexpected events. Humans and robots may have different capabilities in attending and responding to these uncertainties. All of these contribute to a misaligned perceptual basis between a human and a robot, which jeopardizes their collaborative activities and task performance. To enable situated human robot dialogue, a critical component is to develop techniques that will support mediating the shared perceptual basis for effective conversation and task completion. The objective of this National Robotics Initiative project is to develop a novel framework that tightly integrates high level language and dialogue processing with low level sensing and control systems and contextually grounds the collaborative discourse to mediate shared perceptual basis. By capturing grounded symbolic representations as well as continuous representations of the internal configuration of a robotic system and continuous information sensed from the changing environment, the framework allows the robot to promptly modify its execution without interrupting the on-going tasks. It further enables collaborations between humans and robots to mediate a shared perceptual basis and support efficient interaction in a highly dynamic environment.This project will provide insight as to how the misaligned perceptual basis between a human and a robot should be mediated through a collaborative process and how such a process should be integrated to produce intelligent and collaborative robot behaviors. The expected results will benefit many applications such as manufacturing, service, assistive technology, and search and rescue.

在人机对话中，虽然人类伙伴和机器人共存于一个共享的环境中，但他们对环境的感知和推理能力完全不匹配。他们的知识和对共享世界的表述截然不同。此外，共享环境充满不确定性和突发事件。人类和机器人在关注和应对这些不确定性方面可能具有不同的能力。所有这些都会导致人类和机器人之间的感知基础不一致，从而危及他们的协作活动和任务表现。为了实现情境人类机器人对话，一个关键部分是开发支持调解共享感知基础的技术，以实现有效对话和任务完成。该国家机器人计划项目的目标是开发一种新颖的框架，将高级语言和对话处理与低级传感和控制系统紧密集成，并根据上下文建立协作话语以调解共享的感知基础。通过捕获基础符号表示以及机器人系统内部配置的连续表示以及从不断变化的环境中感知的连续信息，该框架允许机器人迅速修改其执行，而不会中断正在进行的任务。它进一步使人类和机器人之间的协作能够调解共享的感知基础并支持高度动态环境中的有效交互。该项目将提供关于如何通过协作过程调解人类和机器人之间不一致的感知基础以及如何集成这样的过程以产生智能和协作机器人行为的见解。预期结果将有利于制造、服务、辅助技术以及搜索和救援等许多应用。