In the field of construction, human-robot collaboration and mixed reality (MR) open new possibilities. However, safety and reliability issues persist. The lack of flexibility and adaptability in current preprogrammed systems hampers real-time human-robot collaboration. A key gap in this area lies in the ability of the robot to interpret and accurately execute operations based on the real-time visual instructions and restrictions provided by the human collaborator and the working environment. This paper focuses on an MR-based human-robot collaboration method through visual feedback from a vision-based collaborative industrial robot system for use in wood stereotomy which we are developing. This method is applied to an alternating workflow in which a skilled carpenter lays out the joinery on the workpiece, and the robot cuts it. Cutting operations are instructed to the robot only through lines and conventional “carpenter’s marks”, which are drawn on the timbers by the carpenter. The robot system’s accuracy in locating and interpreting marks as cutting operations is evaluated by automatically constructing a 3D model of the cut shape from the vision system data. A digital twin of the robot allows the carpenter to previsualize all motions that are required by the robot for task validation and to know when to enter the collaborative workspace. Our experimental results offer some insights into human-robot communication requirements for collaborative robot system applications in timber frame construction.

Three dimensional-printing construction is an emerging technology with significant potential for faster building execution and more precise, controllable designs. This technology utilizes material deposition managed by computer data, enabling additive construction of shapes. This research aims to develop a generative design system for 3D-printed houses in Chile, addressing the country’s growing demand for housing across diverse geographical locations and social groups, also present in other parts of the world. The development process involves synthesizing the external form features of existing Chilean houses and analyzing prototypes of 3D-printed houses worldwide to establish a set of geometric characteristics suitable for 3D-printed homes in Chile. A procedure is then outlined to create design alternatives using parametric programming on a BIM platform, followed by toolpath development for printing the building components. Various models are generated to demonstrate housing shapes’ versatility and adaptability to Chilean contexts and 3D-printed construction methods. Finally, a detailed design is created and printed to construct a housing prototype, testing the entire digital workflow. This experience highlights the variety of 3D-printed housing shapes that can be developed while assessing their feasibility for the Chilean context. This research complements the flexible design capabilities of 3D printing construction, resulting in buildings better suited to various locations and occupancy needs.

Additive manufacturing in construction is expanding production possibilities for housing, however its integration into architectural design workflows remains limited. This research proposes a computational workflow for the early-stage form-finding of housing volumes intended for additive construction. A parametric design system was developed to generate a wide range of residential volumetric configurations based on geometric parameters derived from conventional housing typologies and emerging 3D-printed construction practices. The design space was explored through user-driven experimentation and automated evolutionary optimization targeting predefined surface area conditions. Besides design alternatives were visualized using AI-assisted image generation to support comparative evaluation, translated into BIM models for further architectural development, and tested through physical 3D-printed scale models to assess material expression and constructability. Five design exploration activities involving architects and graduate students produced nearly 200 volumetric alternatives, in order to review its use and possibilities. The results show that the parametric system enables efficient exploration of both conventional and novel housing forms potentially compatible with additive construction. Vertically articulated volumes with curved envelopes and spatial variation emerged as promising alternatives. The study demonstrates the potential of integrating parametric modeling, evolutionary search, AI-assisted visualization, and physical prototyping to support architectural decision-making and facilitate the incorporation of 3D printing into housing design processes.