Large Models Empowering Embodied Intelligent Manufacturing: Theoretical Foundations, Key Technologies, and Future Prospects
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摘要: 随着人工智能技术的快速发展, 传统以单点自动化为特征的制造体系, 在应对高度动态化、个性化与系统级协同需求方面日益显现局限. 大模型与具身智能作为新一代人工智能的重要方向, 正在为制造业的智能化转型提供全新路径. 大模型具备跨模态表征、知识泛化和持续学习能力, 具身智能强调智能体与物理环境的动态交互与闭环反馈, 两者融合不仅强化了多模态感知与知识驱动决策的统一性, 还提升了虚实迁移的稳定性与群体智能的协同能力, 从而为复杂工业场景下的自主优化与系统级智能提供系统性支撑. 基于此, 系统梳理相关理论与关键技术, 结合流程制造与离散制造的典型场景, 探讨机理知识融合、多模态感知、符号−神经推理、数字孪生演化和人机共融交互等前沿方向, 为工业人工智能构建结构化框架和系统化方案提供参考, 推动制造业由局部探索迈向系统级深度融合.Abstract: With the rapid advancement of artificial intelligence technology, traditional manufacturing systems characterized by point-based automation are increasingly revealing their limitations in addressing highly dynamic, personalized, and system-level collaboration requirements. Large models and embodied intelligence, as key directions in the next generation of artificial intelligence, are providing a new pathway for the intelligent transformation of the manufacturing industry. Large models possess cross-modal representation, knowledge generalization, and continuous learning capabilities, while embodied artificial intelligence emphasizes dynamic interaction and closed-loop feedback between agents and the physical environment. The integration of these two approaches not only strengthens the unity of multimodal perception and knowledge-driven decision-making but also enhances the stability of virtual-to-physical transfer and the collaborative capabilities of swarm intelligence, thereby providing systematic support for autonomous optimization and system-level intelligence in complex industrial scenarios. Based on this, the paper systematically reviews relevant theories and key technologies. By integrating typical scenarios from process manufacturing and discrete manufacturing, it explores cutting-edge directions such as the fusion of mechanistic knowledge, multimodal perception, symbolic-neural reasoning, digital twin evolution, and human-machine collaborative interaction. This provides a reference for constructing a structured framework and systematic solutions for industrial artificial intelligence, driving the manufacturing industry from localized exploration toward system-level deep integration.
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图 2 大模型赋能具身智能制造框架
Fig. 2 Framework of large models empowering embodied intelligent manufacturing
图 3 大模型技术路线与产业落地的协同演进示意图
Fig. 3 Schematic diagram of the co-evolution between large model technology roadmaps and industrial adoption
图 4 大模型与具身智能系统的交互示意图
Fig. 4 Schematic diagram of interactions between large model and embodied AI system
图 5 大模型赋能多模态融合感知及应用框架
Fig. 5 Framework of large models empowering multimodal perception and applications
图 6 大模型赋能知识驱动决策与控制框架
Fig. 6 Framework of large models empowering knowledge-driven decision and control
图 7 大模型赋能在线自适应持续学习框架
Fig. 7 Framework of large models empowering online adaptive continuous learning
图 8 大模型赋能群体协同与分布式智能框架
Fig. 8 Framework of large models empowering swarm collaboration and distributed intelligence
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