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.
Authors
- Wenhang Dong
- Shufei Li (ORCID: https://orcid.org/0000-0002-5684-6756)
- Pai Zheng
Institutions
- Hong Kong Polytechnic University (HK)
- City University of Hong Kong (HK)
- Huazhong University of Science and Technology (CN)
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