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    Toward Embodied Intelligence-Enabled Human–Robot Symbiotic Manufacturing: A Large Language Model-Based Perspective

    Source: Journal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue: 005::page 50801-1
    Author:
    Dong, Wenhang
    ,
    Li, Shufei
    ,
    Zheng, Pai
    DOI: 10.1115/1.4068235
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Human–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.
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      Toward Embodied Intelligence-Enabled Human–Robot Symbiotic Manufacturing: A Large Language Model-Based Perspective

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4308377
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    contributor authorDong, Wenhang
    contributor authorLi, Shufei
    contributor authorZheng, Pai
    date accessioned2025-08-20T09:29:54Z
    date available2025-08-20T09:29:54Z
    date copyright4/2/2025 12:00:00 AM
    date issued2025
    identifier issn1530-9827
    identifier otherjcise-24-1358.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4308377
    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.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleToward Embodied Intelligence-Enabled Human–Robot Symbiotic Manufacturing: A Large Language Model-Based Perspective
    typeJournal Paper
    journal volume25
    journal issue5
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4068235
    journal fristpage50801-1
    journal lastpage50801-15
    page15
    treeJournal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue: 005
    contenttypeFulltext
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