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A framework and method for Human-Robot cooperative safe control based on digital twin
参考中译:基于数字孪生的人-机器人协同安全控制框架与方法


          

刊名：Advanced engineering informatics
作者：Hao Li（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
Wenfeng Ma（SIPPR Engineering Group Co., Ltd）
Haoqi Wang（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
Gen Liu（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
Xiaoyu Wen（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
Yuyan Zhang（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
Miying Yang（College of Engineering, Mathematics and Physical Sciences, University of Exeter）
Guofu Luo（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
Guizhong Xie（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
Chunya Sun（Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry）
刊号：738C0037
ISSN：1474-0346
出版年：2022
年卷期：2022, vol.53
页码：101701-1--101701-14
总页数：14
分类号：TP18; TP3
关键词：Human-robot collaboration；Digital twin；Safety control；Machine vision；Convolutional neural network
参考中译：人机协作；数字孪生；安全控制；机器视觉；卷积神经网络
语种：eng
文摘：Human-robot collaboration (HRC) combines the robot's mechanical properties and predictability with human experience, logical thinking, and strain capabilities to alleviate production efficiency. However, ensuring the safety of the HRC process in-real time has become an urgent issue. Digital twin extends functions of virtual models in the design phase of the physical counterpart in the production phase through virtual-real interactive feedback, data fusion analysis, advanced computational features, etc. This paper proposes an HRC safety control framework and corresponding method based on the digital twin. In the design phase, virtual simulation and virtual reality technology are integrated to construct virtual twins of various HRC scenarios for testing and analyzing potential safety hazards. In the production phase, the safety distance between humans and robots of the HRC scene is monitored and calculated by an iterative algorithm according to machine vision and a convolutional neural network. Finally, the virtual twin is driven based on real-scene data, real-time online visual monitoring, and optimization of the HRC's overall process. A case study using ABB-IRB1600 is presented to verify the feasibility of the proposed approach.
参考中译：人-机器人协作(HRC)将机器人的机械特性和可预测性与人类的经验、逻辑思维和应变能力相结合，以降低生产效率。然而，确保人权委员会进程的实时安全已成为一个紧迫的问题。数字孪生模型通过虚实交互反馈、数据融合分析、先进的计算特性等扩展了虚拟模型在生产阶段物理模型设计阶段的功能，提出了一种基于数字孪生模型的HRC安全控制框架和方法。在设计阶段，将虚拟仿真和虚拟现实技术相结合，构建了各种HRC场景的虚拟双胞胎，用于测试和分析潜在的安全隐患。在生产阶段，根据机器视觉和卷积神经网络的迭代算法，对HRC场景中人与机器人之间的安全距离进行监测和计算。最后，基于实时场景数据、实时在线视觉监控和人权委员会整体流程的优化来驱动虚拟孪生兄弟。以ABB-IRB1600为例，验证了该方法的可行性。



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