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

Wenhang Dong, Shufei Li, Pai Zheng

Year
2025
Citations
18
Access
Open access

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.

Keywords

Embodied cognitionPerspective (graphical)RobotHuman–computer interactionComputer scienceArtificial intelligenceEngineeringEngineering drawing

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