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

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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Publication Details

Journal
Journal of Computing and Information Science in Engineering
Published
2025-03-18
DOI
https://doi.org/10.1115/1.4068235
Citations
12
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
14.57
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article

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

Wenhang Dong, Shufei Li, Pai Zheng
12 citations
Journal of Computing and Information Science in Engineering
Robot Manipulation and Learning
14.57
article

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

Wenhang Dong, Shufei Li, Pai Zheng
article en
12 citations

Abstract

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.

Journal of Computing and Information Science in EngineeringVol. 25(5)
Hong Kong Polytechnic University (HK), City University of Hong Kong (HK), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 1%
Robot Manipulation and Learning
14.57
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