Show simple item record

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


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record