Deep understanding of everyday activity commands for household robots

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Semantic Web Pub Date : 2022-05-13 DOI:10.3233/sw-222973

Sebastian Höffner, R. Porzel, Maria M. Hedblom, M. Pomarlan, Vanja Sophie Cangalovic, Johannes Pfau, J. Bateman, R. Malaka

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引用次数: 1

Abstract

Going from natural language directions to fully specified executable plans for household robots involves a challenging variety of reasoning steps. In this paper, a processing pipeline to tackle these steps for natural language directions is proposed and implemented. It uses the ontological Socio-physical Model of Activities (SOMA) as a common interface between its components. The pipeline includes a natural language parser and a module for natural language grounding. Several reasoning steps formulate simulation plans, in which robot actions are guided by data gathered using human computation. As a last step, the pipeline simulates the given natural language direction inside a virtual environment. The major advantage of employing an overarching ontological framework is that its asserted facts can be stored alongside the semantics of directions, contextual knowledge, and annotated activity models in one central knowledge base. This allows for a unified and efficient knowledge retrieval across all pipeline components, providing flexibility and reasoning capabilities as symbolic knowledge is combined with annotated sub-symbolic models.

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对家用机器人日常活动指令的深刻理解

从自然语言指示到家用机器人的完全指定的可执行计划涉及各种具有挑战性的推理步骤。本文提出并实现了一种处理管道来处理这些步骤。它使用活动的本体论社会物理模型(SOMA)作为其组件之间的公共接口。该管道包括一个自然语言解析器和一个用于自然语言基础的模块。几个推理步骤制定了仿真计划，其中机器人的行动由使用人类计算收集的数据指导。作为最后一步，管道在虚拟环境中模拟给定的自然语言方向。使用总体本体框架的主要优点是，它断言的事实可以与方向语义、上下文知识和注释活动模型一起存储在一个中心知识库中。这允许跨所有管道组件进行统一和有效的知识检索，提供灵活性和推理能力，因为符号知识与带注释的子符号模型相结合。

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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来源期刊

Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

8.30

自引率

6.70%

发文量

期刊介绍： The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.