Gradient porous structures (GPS) offer significant mechanical and functional advantages over homogeneous counterparts. This paper proposes a computational design framework utilizing spatial Voronoi diagrams to create lightweight, stress-responsive spatial frames optimized for architectural double-curvature arched shell roofing components. The method integrates Solid Isotropic Material with Penalization (SIMP)-based topology optimization (TO) to establish initial stress-informed material distributions, adaptive Voronoi control point (CP) placement guided by localized stress data, and a bi-objective genetic algorithm (GA) optimizing maximum and average displacement. Following optimization, a weighted Lloyd relaxation (LR) refines Voronoi cells into spatial frameworks with varying densities corresponding to stress gradients. Finite Element Analysis (FEA) demonstrates that the optimized Voronoi-driven GPS achieves notable improvements, revealing up to 79.7% material volume reduction and significant improvement in structural efficiency, achieving a stiffness-to-weight ratio (SWR) exceeding 2200 in optimized configurations. Furthermore, optimized structures consistently maintain maximum von Mises (MVM) stresses below 20 MPa, well within the allowable yield strength of the Polyethylene Terephthalate Glycol (PETG) material (53 MPa). The developed framework effectively bridges structural performance, material efficiency, and aesthetic considerations, offering substantial potential for application in advanced, high-performance architectural systems.

In recent years, the AEC industry has increasingly sought sustainable solutions to enhance productivity and reduce environmental pollution, with wood emerging as a key renewable material due to its excellent carbon sequestration capability and low ecological footprint. Despite significant advances in digital fabrication technologies for timber construction, on-site assembly still predominantly relies on manual operations, thereby limiting efficiency and precision. To address this challenge, this study proposes an automated on-site timber construction process that integrates a mobile construction platform (MCP), a fiducial marker system (FMS) and a UWB/IMU integrated navigation system. By deconstructing traditional modular stacking methods and iteratively developing the process in a controlled laboratory environment, the authors formalize raw construction experience into an effective workflow, supplemented by a self-feedback error correction system to achieve precise, real-time end-effector positioning. Extensive experimental results demonstrate that the system consistently achieves millimeter-level positioning accuracy across all test scenarios, with translational errors of approximately 1 mm and an average repeat positioning precision of up to 0.08 mm, thereby aligning with on-site timber construction requirements. These findings validate the method’s technical reliability, robustness and practical applicability, laying a solid foundation for a smooth transition from laboratory trials to large-scale on-site timber construction.

In the architecture, engineering, and construction (AEC) industry, the positioning technology for a mobile construction platform (MCP) is critical to achieve on-site, continuous, large-scale construction. During construction, MCP movement and construction actions seldom occur simultaneously. Therefore, this paper categorizes the MCP into stationary and moving states for positioning studies, respectively. When the platform is stationary, it is positioned using an improved ultra-wideband (UWB) sensor. When the platform is in motion, a single UWB positioning technique cannot meet the required accuracy for positioning, and fusion positioning using both UWB and an inertial measurement unit (IMU) is considered. The experimental results show that compared with only UWB positioning, the improved UWB positioning algorithm improves the positioning accuracy by 53% in the stationary state, and the fused UWB/IMU positioning improves the positioning accuracy by 46% in the moving state. As a result, the positioning accuracy of the MCP is significantly improved regardless of whether it is in a stationary or moving state. Furthermore, this paper integrates the positioning technique with the robotic arm construction technique to successfully simulate an on-site continuous construction of a wooden cabin, which provides the potential for large-scale continuous construction in real-world scenarios in the future.

Although robotic spatial printing (RSP) has demonstrated a new way of fabricating building components with a good stiffness-to-weight ratio, the complexity of the applied geometries is still limited. Among them are branching geometries, which refer to the bio-inspired branching structures (BIBSs) in the building industry. This paper presents a cutting-edge approach to tackle this bottleneck problem, in which we propose an automated printing path generation (APPG) approach for the RSP of branching geometries, including an original hierarchical framework of printing node permutations and a linear workflow that incorporates five core algorithms: the heat method, graph generation, graph traversal, curve adjustment, and lattice generation. Through the execution of this workflow, a lattice structure and its corresponding printing path can be generated. This work is validated by the simulation of three prototypes: two-branch geometry, multi-branch geometry, and multi-level-branch geometry. Printing expenses are compared with each of the related algorithms to validate the efficiency of this proposed approach. Along with the appropriate APPG solutions, an analytical tool for topological type is also presented in this paper.