Enhancing awareness of industrial robots in collaborative manufacturing

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

Semantic Web Pub Date : 2023-06-08 DOI:10.3233/sw-233394

A. Umbrico, A. Cesta, Andrea Orlandini

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引用次数: 0

Abstract

The diffusion of Human-Robot Collaborative cells is prevented by several barriers. Classical control approaches seem not yet fully suitable for facing the variability conveyed by the presence of human operators beside robots. The capabilities of representing heterogeneous knowledge representation and performing abstract reasoning are crucial to enhance the flexibility of control solutions. To this aim, the ontology SOHO (Sharework Ontology for Human-Robot Collaboration) has been specifically designed for representing Human-Robot Collaboration scenarios, following a context-based approach. This work brings several contributions. This paper proposes an extension of SOHO to better characterize behavioral constraints of collaborative tasks. Furthermore, this work shows a knowledge extraction procedure designed to automatize the synthesis of Artificial Intelligence plan-based controllers for realizing flexible coordination of human and robot behaviors in collaborative tasks. The generality of the ontological model and the developed representation capabilities as well as the validity of the synthesized planning domains are evaluated on a number of realistic industrial scenarios where collaborative robots are actually deployed.

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增强工业机器人在协同制造中的意识

人-机器人协作细胞的扩散受到若干障碍的阻碍。经典的控制方法似乎还不完全适合面对人类操作员在机器人旁边的存在所传达的可变性。表示异构知识和执行抽象推理的能力对于提高控制方案的灵活性至关重要。为此，SOHO(人机协作共享本体)是专门为表示人机协作场景而设计的，遵循基于上下文的方法。这项工作带来了几个贡献。本文提出了SOHO的扩展，以更好地表征协作任务的行为约束。此外，本工作展示了一种知识提取程序，旨在自动合成基于人工智能计划的控制器，以实现协作任务中人与机器人行为的灵活协调。在实际部署协作机器人的实际工业场景中，评估了本体模型的通用性和开发的表示能力以及综合规划域的有效性。

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.