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<p>Computer-aided design (CAD) and automation are advancing the high-precision restoration of damaged masonry structures. This paper proposes a scalable, repeatable workflow, evaluated on a historic screen wall in China, to demonstrate the feasibility and efficiency of these techniques. Our framework consists of two primary systems to improve mortar-brick construction. The Historic-led Restorative System (HLRS) provides an architect-friendly digital interface for handling input images and generating 3D restoration models, utilising pixel-to-voxel basics and integrated retrieval modules. The second system, the Extended Automation System (EAS), bridges the gap between modelling and physical prototyping. It integrates extended reality (XR) and robotic assembly for hybrid additive manufacturing requirements, allowing seamless data transfer for physically augmented assembly. This multi-terminal digital workflow uses iterative algorithms to make the restoration process more interactive and visually accessible. The initial case study evaluated each system iteration indicator and confirmed the framework’s high accuracy and efficiency in a real-world application.</p>

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Integrating CAD and extended robotics for masonry restoration: a scalable workflow for historic and heritage buildings (HHBs)

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月18日

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  • Boyuan Yu,
  • Yuemin Gong,
  • Jianing Luo,
  • Adam Fingrut

摘要

Computer-aided design (CAD) and automation are advancing the high-precision restoration of damaged masonry structures. This paper proposes a scalable, repeatable workflow, evaluated on a historic screen wall in China, to demonstrate the feasibility and efficiency of these techniques. Our framework consists of two primary systems to improve mortar-brick construction. The Historic-led Restorative System (HLRS) provides an architect-friendly digital interface for handling input images and generating 3D restoration models, utilising pixel-to-voxel basics and integrated retrieval modules. The second system, the Extended Automation System (EAS), bridges the gap between modelling and physical prototyping. It integrates extended reality (XR) and robotic assembly for hybrid additive manufacturing requirements, allowing seamless data transfer for physically augmented assembly. This multi-terminal digital workflow uses iterative algorithms to make the restoration process more interactive and visually accessible. The initial case study evaluated each system iteration indicator and confirmed the framework’s high accuracy and efficiency in a real-world application.