A visual reasoning-based approach for mutual-cognitive human-robot collaboration. Issue 1 (2022)

• Record Type: Journal Article
• Authors: Zheng, Pai; Li, Shufei; Xia, Liqiao; Wang, Lihui; Nassehi, Aydin
• Is Part Of: CIRP annals. Volume 71:Issue 1(2022)
• Page Start: 377
• Page End: 380
• Publication Date: 2022
• Subjects: Human robot collaboration -- Manufacturing system -- Visual reasoning; Production engineering -- Research -- Periodicals; 670.5
• DOI: 10.1016/j.cirp.2022.04.016
• Languages: English
• ISSNs: 0007-8506

Abstract

Abstract: Human-robot collaboration (HRC) allows seamless communication and collaboration between humans and robots to fulfil flexible manufacturing tasks in a shared workspace. Nevertheless, existing HRC systems lack an efficient integration of robotic and human cognitions. Empowered by advanced cognitive computing, this paper proposes a visual reasoning-based approach for mutual-cognitive HRC. Firstly, a domain-specific HRC knowledge graph is established. Next, the holistic manufacturing scene is perceived by visual sensors as a temporal graph. Then, a collaborative mode with similar instructions can be inferred by graph embedding. Lastly, mutual-cognitive decisions are immersed into the Augmented Reality execution loop for intuitive HRC support.