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Human-in-the-Loop Robot Learning for Smart Manufacturing: A Human-Centric Perspective
Chen, Hongpeng Li, Shufei Fan, Junming Duan, Anqing Yang, Chenguang Navarro-Alarcon, David
Chen, Hongpeng
Li, Shufei
Fan, Junming
Duan, Anqing
Yang, Chenguang
Navarro-Alarcon, David
Supervisor
Department
Robotics
Embargo End Date
Type
Journal article
Date
2025
License
Language
English
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Research Projects
Organizational Units
Journal Issue
Abstract
Robot learning has attracted an ever-increasing attention by automating complex tasks, reducing errors, and increasing production speed and flexibility, which leads to significant advancements in manufacturing intelligence. However, its low training efficiency, limited real-time feedback, and challenges in adapting to untrained scenarios hinder its applications in smart manufacturing. Introducing a human role in the training loop, a practice known as human-in-the-loop (HITL) robot learning, can improve the performance of robots by leveraging human prior knowledge. Nonetheless, the exploration of HITL robot learning within the context of human-centric smart manufacturing remains in its infancy. This study provides a holistic literature review for understanding HITL robot learning within an industrial context from a human-centric perspective. A united structure is presented to encompass different aspects of human intelligence in HITL robot learning, highlighting perception, cognition, behavior, and notably, empathy. Then, the typical applications in manufacturing scenarios are analyzed to expand the research landscape for smart manufacturing. Finally, it introduces the empirical challenges and future directions for HITL robot learning in the next industrial revolution era.
Citation
H. Chen et al., "Human-in-the-Loop Robot Learning for Smart Manufacturing: A Human-Centric Perspective," in IEEE Transactions on Automation Science and Engineering, doi: 10.1109/TASE.2025.3528051
Source
IEEE Transactions on Automation Science and Engineering
Conference
Keywords
Robots, Robot learning, Smart manufacturing, Service robots, Automation, Training, Human intelligence, Cognition, Production, Robot sensing systems
Subjects
Source
Publisher
IEEE