Levels of interaction allowing humans to command, interrogate and teach a communicating object: lessons learned from two robotic platform

Peter Ford Dominey, A. Weitzenfeld
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Abstract

As robotic systems become increasingly capable of complex sensory, motor and information processing functions, the ability to interact with them in an ergonomic, real-time and adaptive manner becomes an increasingly pressing concern. In this context, the physical characteristics of the robotic device should become less of a direct concern, with the device being treated as a system that receives information, acts on that information, and produces information. Once the input and output protocols for a given system are well established, humans should be able to interact with these systems via a standardized spoken language interface that can be tailored if necessary to the specific system.The objective of this research is to develop a generalized approach for human-machine interaction via spoken language that allows interaction at three levels. The first level is that of commanding or directing the behavior of the system. The second level is that of interrogating or requesting an explanation from the system. The third and most advanced level is that of teaching the machine a new form of behavior. The mapping between sentences and meanings in these interactions is guided by a neuropsychologically inspired model of grammatical construction processing. We explore these three levels of communication on two distinct robotic platforms. The novelty of this work lies in the use of the construction grammar formalism for binding language to meaning extracted from video in a generative and productive manner, and in thus allowing the human to use language to command, interrogate and modify the behavior of the robotic systems.
允许人类指挥、询问和教授交流对象的互动水平:从两个机器人平台学到的经验
随着机器人系统越来越具有复杂的感觉、运动和信息处理功能,以符合人体工程学、实时和自适应的方式与它们进行交互的能力成为一个日益紧迫的问题。在这种情况下,机器人设备的物理特性应该不再是一个直接关注的问题,而是将设备视为一个接收信息、对该信息采取行动并产生信息的系统。一旦给定系统的输入和输出协议得到很好的建立,人类应该能够通过标准化的口语接口与这些系统进行交互,该接口可以根据特定系统的需要进行定制。本研究的目的是开发一种通过口语进行人机交互的通用方法,该方法允许在三个层次上进行交互。第一个层次是命令或指导系统的行为。第二级是询问或要求系统作出解释。第三个也是最先进的层次是教会机器一种新的行为形式。在这些相互作用中句子和意义之间的映射是由语法结构加工的神经心理学启发模型指导的。我们在两个不同的机器人平台上探索这三个层次的交流。这项工作的新颖之处在于使用结构语法形式主义,以生成和生产的方式将语言与从视频中提取的意义绑定在一起,从而允许人类使用语言来命令,询问和修改机器人系统的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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