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.

中文翻译：

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增强工业机器人在协同制造中的意识

摘要

人机协作细胞的扩散受到多种障碍的阻碍。经典控制方法似乎尚不完全适合应对机器人旁边人类操作员的存在所带来的变化。异构知识表示和执行抽象推理的能力对于增强控制解决方案的灵活性至关重要。为此，本体 SOHO（人机协作共享工作本体）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。这项工作带来了一些贡献。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，这项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类和机器人行为的灵活协调。本体模型的通用性和所开发的表示能力以及综合规划域的有效性在实际部署协作机器人的许多实际工业场景中进行了评估。