A visual reasoning-based approach for mutual-cognitive human-robot collaboration

Pai Zheng, Shufei Li, Liqiao Xia, Lihui Wang, Aydin Nassehi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

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.

Original languageEnglish
JournalCIRP Annals
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Human robot collaboration
  • Manufacturing system
  • Visual reasoning

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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