用视觉语言动作模型实现机器人在工厂中的智能协作与自适应制造。
Human Centric General Physical Intelligence for Agile Manufacturing Automation
- 通过多模态融合与上下文推理，让机器人理解复杂工业场景。
- 系统梳理六类技术进展，评估其在真实工厂中的部署可行性。
- 适合关注智能制造、机器人自主决策的研究者与工程师。
敏捷的人本制造亟需具备在非结构化工厂环境中安全高效交互能力的机器人解决方案。尽管多模态传感器融合提供了全面的情境感知，但机器人还需具备上下文推理能力以实现对复杂场景的深层语义理解。基础模型，尤其是视觉-语言-动作（VLA）模型，已成为整合多样感知模态与时空推理能力、将物理行为具身化以实现通用物理智能（GPI）的有前景方法。尽管GPI在文献中已有概念性讨论，但其在敏捷制造中的关键作用与实际应用仍待深入探索。为此，本文从GPI视角系统综述了近期VLA模型的进展，通过对比分析主流实现方案，并基于结构化消融实验评估其工业就绪度。当前技术被归纳为六大主题支柱：多感官表征学习、模拟到现实迁移、规划与控制、不确定性与安全机制、基准测试。最后，论文指出了集成GPI至工业生态系统的开放挑战与未来方向，以契合工业5.0所倡导的智能化、自适应与协同制造愿景。
原文摘要 · Abstract (English)
Agile human-centric manufacturing increasingly requires resilient robotic solutions that are capable of safe and productive interactions within unstructured environments of modern factories. While multi-modal sensor fusion provides comprehensive situational awareness yet robots must also contextualize their reasoning to achieve deep semantic understanding of complex scenes. Foundation model particularly Vision-Language-Action (VLA) models have emerged as promising approach on integrating diverse perceptual modalities and spatio-temporal reasoning abilities to ground physical actions to realize General Physical Intelligence (GPI) across various robotic embodiments. Although GPI has been conceptually discussed in literature but its pivotal role and practical deployment in agile manufacturing remain underexplored. To address this gap, this practical review systematically surveys recent advances in VLA models through the lens of GPI by offering comparative analysis of leading implementations and evaluating their industrial readiness via structured ablation study. The state of the art is organized into six thematic pillars including multisensory representation learning, sim2real transfer, planning and control, uncertainty and safety measures and benchmarking. Finally, the review highlights open challenges and future directions for integrating GPI into industrial ecosystems to align with the vision of Industry 5.0 for intelligent, adaptive and collaborative manufacturing ecosystem.
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