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dc.contributor.authorDong, Wenhang
dc.contributor.authorLi, Shufei
dc.contributor.authorZheng, Pai
dc.date.accessioned2025-08-20T09:29:54Z
dc.date.available2025-08-20T09:29:54Z
dc.date.copyright4/2/2025 12:00:00 AM
dc.date.issued2025
dc.identifier.issn1530-9827
dc.identifier.otherjcise-24-1358.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4308377
dc.description.abstractHuman–robot collaborative manufacturing is crucial in modern production landscapes for flexible automation. However, existing human–robot systems face several challenges, including a lack of human-centric autonomy for adjustments, limited generalization for production variants, and ineffective synchronous teamwork with feedback. Emerging large language models (LLMs) offer a viable solution. Despite the growing interest in LLMs, their deployment within the manufacturing domain remains unexplored. This article delves into the potential of LLMs for embodied intelligence-enabled human–robot symbiotic manufacturing (HRSM). HRSM is a paradigm characterized by human centricity, generalizability, and seamless integration. LLMs can facilitate human-centric interactions, generalizable collaboration, and ensure seamless execution, paving the way for realizing HRSM. Finally, the main challenges and potential opportunities are further discussed to enable the readiness toward HRSM.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleToward Embodied Intelligence-Enabled Human–Robot Symbiotic Manufacturing: A Large Language Model-Based Perspective
dc.typeJournal Paper
dc.journal.volume25
dc.journal.issue5
dc.journal.titleJournal of Computing and Information Science in Engineering
dc.identifier.doi10.1115/1.4068235
dc.journal.fristpage50801-1
dc.journal.lastpage50801-15
dc.page15
dc.treeJournal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue: 005
dc.contenttypeFulltext


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