A framework and method for Human-Robot cooperative safe control based on digital twin. (August 2022)

• Record Type: Journal Article
• Authors: Li, Hao; Ma, Wenfeng; Wang, Haoqi; Liu, Gen; Wen, Xiaoyu; Zhang, Yuyan; Yang, Miying; Luo, Guofu; Xie, Guizhong; Sun, Chunya
• Is Part Of: Advanced engineering informatics. Volume 53(2022)
• Publication Date: 2022-08
• Subjects: Human-robot collaboration -- Digital twin -- Safety control -- Machine vision -- Convolutional neural network; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2022.101701
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: 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.