This research presents a robotic-centric digital construction workflow, in which a six-axis robotic system orchestrates the fabrication and assembly of puzzle-joined freeform architectural components using castable and sustainable building materials. The robot is not only the primary executor of physical tasks but also serves as the data node in a closed-loop digital twin framework, enabling intelligent control across all phases of design-to-assembly. Developed on the Rhino-Grasshopper platform, the system employs parametric design strategies to segment complex surface geometries into interlocking units with built-in alignment and self-locking features. Each unit is produced via CNC-milled formwork and cast using materials such as ultra-high-performance concrete (UHPC) or fiber-reinforced composites, ensuring durability and environmental compliance. Fabrication is executed by a six-axis robotic arm that handles mold preparation, material pouring, and component finishing with high precision. A digital twin environment built in Unity simulates the full assembly process, evaluating sequence optimization, spatial constraints, and tolerance propagation. A series of full-scale wall prototypes were constructed to validate the system, achieving a 32% reduction in manual labor, 21% reduction in material waste, and joint accuracy within ±2 mm. This study delivers a replicable methodology for bridging computational design with automated construction, contributing to scalable and intelligent building systems aligned with Industry 4.0 standards.
Yuan et al. (Fri,) studied this question.