TY - JOUR
T1 - A Systematic Review on Vision-Based Proactive Human Assembly Intention Recognition for Human-Centric Smart Manufacturing in Industry 5.0
AU - Ma, Dongxu
AU - Zhang, Chao
AU - Zhou, Guanghui
AU - Xu, Qingfeng
AU - Li, Jinqiang
AU - Zhao, Dan
AU - Leng, Jiewu
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Human assembly intention recognition (HAIR)
KW - Industry 5.0
KW - human-centric smart manufacturing
KW - human–robot collaboration (HRC)
KW - multimodalities data
UR - https://www.scopus.com/pages/publications/105005233130
U2 - 10.1109/JIOT.2025.3570510
DO - 10.1109/JIOT.2025.3570510
M3 - 文章
AN - SCOPUS:105005233130
SN - 2327-4662
VL - 12
SP - 32493
EP - 32515
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 16
ER -