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A Systematic Review on Vision-Based Proactive Human Assembly Intention Recognition for Human-Centric Smart Manufacturing in Industry 5.0

  • Dongxu Ma
  • , Chao Zhang
  • , Guanghui Zhou
  • , Qingfeng Xu
  • , Jinqiang Li
  • , Dan Zhao
  • , Jiewu Leng
  • Xi'an Jiaotong University
  • Guangdong University of Technology

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Proactive human–robot collaborative (HRC) assembly has caught great attention as emerging paradigm for flexible mass personalization in manufacturing with respect to Industry 5.0. To realize adaptive and ergonomic collaboration, it is essential to enable robots recognize human assembly intention based on context-aware information precisely at edge side with Industrial Internet of Things, also known as human assembly intention recognition (HAIR). For this purpose, this article systematically reviewed the most relevant papers from major digital databases, where 127 papers are investigated with designed search procedure that published until July 2024. And reviewed papers are summarized from the perspective of: 1) assembly scene perception based on multimodalities data; 2) understanding of HAIR based on machine learning; and 3) HAIR application for HRC process. In addition, four current challenges and future research trends are also discussed to facilitate full-adaptive and mutual-cognitive HRC assembly environments.

Original languageEnglish
Pages (from-to)32493-32515
Number of pages23
JournalIEEE Internet of Things Journal
Volume12
Issue number16
DOIs
StatePublished - 2025

Keywords

  • Human assembly intention recognition (HAIR)
  • Industry 5.0
  • human-centric smart manufacturing
  • human–robot collaboration (HRC)
  • multimodalities data

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