The advancement of digital fabrication technologies and computational design has expanded the possibilities in architecture and construction. These technologies enable the creation of innovative structures and the exploration of non-standard materials, resulting in a new understanding of the design process and the development of advanced digital tools. Among these innovations, coreless filament winding, a robotic fabrication process, has facilitated new applications of fiber-polymer composites in architecture over the past decade. Coreless wound structures are characterized by a sequential and emergent nature, where the final geometry is shaped by material behavior. As a result, these structures are inherently difficult to predict, requiring constant feedback between digital models and physical prototypes due to the limited availability of fast, accessible simulation methods. This paper presents a simulation method developed to address this gap by supporting the early design stage of coreless wound fiber structures. The method incorporates relevant design and fabrication parameters while maintaining a necessary level of abstraction to ensure efficiency and accessibility. A case study was conducted to evaluate the simulation's accuracy and examine the influence of different parameters on the final geometry. The study benchmarks a set of digitally simulated fiber specimens against their physical counterparts. The physical behavior of the fiber elements was captured using a monitoring method that scans the structure after each fiber segment is wound, enabling the observation of material behavior throughout the process. The results demonstrate the method's efficacy, showing an average displacement deviation of -20 mm and high precision in fiber interaction, with 73% of specimens achieving 100% accuracy in generating intersection points. Furthermore, the study assesses the influence of design and fabrication parameters on fiber behavior, enabling informed decisions in early-stage design. By introducing an accessible and computationally efficient simulation method, the research aims to contribute to the field by providing efficient, early-stage feedback and an initial understanding of material behavior in coreless filament winding, while also identifying current limitations and directions for future research.

The reuse of load-bearing reinforced concrete elements represents a promising approach to reducing CO2 emissions and resource consumption in the construction industry. This paper presents the holistic process of modular reuse, ranging from the identification of suitable donor structures through element extraction and characterization to the assembly of new load-bearing structures. Attention is paid to the development of systematic methods for element identification using Scan-to-BIM, as well as to the evaluation of different separation methods in terms of their impact on element quality. Experimental investigations combine non-destructive and semi-destructive testing methods to determine material properties and structural integrity. The results show that, although selective demolition methods require greater effort, they contribute significantly to the preservation of element quality. In addition, a digital element catalogue with a semantic data structure is presented, which enables consistent documentation and further processing of element information. The approaches developed are validated in full-scale demonstration projects and contribute to the establishment of circular construction methods. Modulare Wiederverwendung bestehender Tragstrukturen: Vom Konzept bis zur Demonstration im Originalma ss stabDie Wiederverwendung von tragenden Stahlbetonbauteilen stellt einen vielversprechenden Ansatz zur Reduzierung von CO2-Emissionen und des Ressourcenverbrauchs in der Bauindustrie dar. Dieser Beitrag stellt den ganzheitlichen Prozess der modularen Wiederverwendung vor, der von der Identifizierung geeigneter Spendergeb & auml;ude & uuml;ber die Entnahme und Charakterisierung der Bauteile bis hin zum Aufbau neuer Tragkonstruktionen reicht. Ein Schwerpunkt liegt auf der Entwicklung systematischer Methoden zur Elementidentifizierung mittels Scan-to-BIM sowie auf der Bewertung verschiedener Trennverfahren hinsichtlich ihrer Auswirkungen auf die Elementqualit & auml;t. Experimentelle Untersuchungen kombinieren zerst & ouml;rungsfreie und halbzerst & ouml;rende Pr & uuml;fverfahren zur Bestimmung der Materialeigenschaften und der strukturellen Integrit & auml;t. Die Ergebnisse zeigen, dass selektive Abbruchverfahren zwar einen h & ouml;heren Aufwand erfordern, aber wesentlich zur Erhaltung der Elementqualit & auml;t beitragen. Dar & uuml;ber hinaus wird ein digitaler Elementkatalog mit einer semantischen Datenstruktur vorgestellt, der eine konsistente Dokumentation und Weiterverarbeitung von Elementinformationen erm & ouml;glicht. Die entwickelten Ans & auml;tze werden in Demonstrationsprojekten im Realma ss stab validiert und tragen zur Etablierung zirkul & auml;rer Bauweisen bei.

An agent-based modelling (ABM) approach is proposed which allows for simulating the spinning of cocoon structures based on a set of behaviours abstracted from theBombyx morisilkworm. ABMs are aimed at the simulation and modelling of autonomous agents which can interact with their environment based on a set of behaviours and boundary conditions. While previous computational approaches address mainly the simulation of tracking data gathered from the silkworm itself, the suggested ABM approaches uses already established data as input for a computational model generation. In biology, such an agent-based framework can support the inverse understanding of patterns occurring in biological systems. It can also serve as an interface for biological materials science and architectural design by allowing the translation of biological processes into algorithmic procedures for architecture-scale structures. The proposed project is thus situated at the intersection of biological materials science and computational design. The current state of research on the spinning behaviour of the silkwormBombyx moriis covered in literature. This is taken as a starting point to extract the motion patterns which are then translated into an ABM in a parametric modelling environment using a custom-written ABM framework. Two different ABM approaches are developed: one which simulates the trajectory of the silk-filament as it is laid by the silkworm and one which simulates the enclosed volume and its articulation through the movement trajectories. Comparison with the biological system shows that with a simple set of behaviours both models can create cocoon architectures similar to the biological model system. Meanwhile they allow direct, adaptive transfer into design and construction processes. Conversely, they open up the possibility to infer relations between spinning behaviour, structural organisation and functional properties. As an outlook, applications of the proposed ABMs in biomaterials science as well as architecture are discussed.

Digital Twins (DTs) hold promise for Construction 4.0, yet current applications remain fragmented, especially at the fabrication and construction level, where heterogeneous machines and workflows must be coordinated in real time. This paper addresses this gap in two steps. First, by understanding what the requirements are for developing a DT architecture for fabrication and construction. Second, using the derived requirements to propose a DT architecture for digital fabrication and construction structured around three components: tasks with a semi-structured data schema, virtual-physical pairs that bridge machines through protocol-specific virtual actors, and modular services for monitoring, simulation, and adaptive control. An execution engine coordinates these components via an event-driven mechanism, ensuring real-time task management and robust traceability. The DT architecture is validated through three case studies: prefabricated timber assembly, collective robotic construction, and large-scale 3D printing, demonstrating its capacity to integrate diverse machines, manage sequential and adaptive processes, and support on-the-fly task injection. By combining flexibility, interoperability, and data integration, the proposed framework contributes a generalisable foundation for DT-enabled fabrication and construction workflows, advancing towards more adaptive and resilient Construction 4.0 practices.

Natural fiber polymer composites have emerged as bio-based alternatives to synthetic materials in load-bearing fiber structures. Their integration with other natural materials enables the creation of hybrid systems that enhance structural performance, resource efficiency, and architectural design. This paper introduces Embedded Frame Filament Winding, a fabrication method that integrates timber frames into the coreless filament winding process. In this case, timber serves both as a support during the fabrication and as a permanent structure, sharing load transmission with the fibers. The interdependence of natural fiber polymer composites and timber introduces uncertainties, requiring higher tolerances and tailored fabrication strategies. This paper focuses on the required robotic adaptations, including customized strategies for anchoring fibers into timber, a path-planning method to address distinct geometry types, and a dual-robot setup that enables simultaneous winding. A comprehensive computational framework linked design, structural analysis, and fabrication, resulting in a research pavilion that demonstrates the potential of bio-based hybrid systems in architecture.

We present the co-development and integration of a fully automated, multi-robot screw-press gluing cyber-physical production system for the prefabrication of a Multi-Story Timber Building System (MSTBS). The system integrates Hardware Setup, Task Planning, and Control Communication, ensuring compliance with the strict requirements for adhesive time. Two containerized robots collaborate in a shared workspace to execute glue application, component placement, and torque-controlled pressing. Precomputed kinematic reachability informs placement and setup co-optimization, followed by motion planning and hierarchical scheduling. A level-based barrier protocol enables safe, asynchronous execution with supervisory traceability and logging for quality assurance and quality control (QA/QC). A full-scale physical prototype validates the feasibility and traceability of this system, demonstrating a scalable and efficient pathway for industrially viable large-format timber slab prefabrication.

Rising global construction demand calls for greater economic efficiency and ecological sustainability. Precast concrete construction (PCC) can reduce on-site errors and waste by using controlled production environments. However, PCC remains limited by traditional, labour-intensive methods ill-suited to automation and individualised elements. Advances in digital fabrication enable customised concrete modules at scale, but realising this potential requires consistent digital representations that integrate design and production. This paper presents an integrated framework leveraging Industry 4.0 concepts to overcome these limitations, specifically employing the Asset Administration Shell (AAS) to implement modular Digital Twins (DTs). Drawing on perspectives from multiple disciplines, this research outlines design and optimisation methods that demonstrate the potential for highly differentiated, precise concrete modules from various digital production processes. Based on a conceptual multi-storey building as a case study, this work explores advances in the design and production of precast concrete modules to highlight the diverse requirements and use cases for DTs in PCC. Three DT case studies are developed, which support design, production, and quality control. These include the simulation-based geometric modularisation of building elements to support early design phases, the monitoring and structuring of production data for analytical insights, and the management of geometric deviations of individual building modules, assessed in relation to their cumulative effect on the overall structural assembly. The results demonstrate the feasibility and effectiveness of integrating the DT concept via the AAS to manage complexity across design and production phases of individualised precast structures, paving the way for more sustainable and efficient construction practices in concrete.

Automating large-scale manufacturing in domains like timber construction requires multi-robot systems to manage tightly coupled spatiotemporal constraints, such as collision avoidance and process-driven deadlines. This paper introduces LASER (Level-based Asynchronous Scheduling and Execution Regime), a complete framework for scheduling and executing complex assembly tasks, demonstrated on a screw-press gluing application for timber slab manufacturing. Our central contribution is to integrate a barrier-based mechanism into a constraint programming (CP) scheduling formulation that partitions tasks into spatiotemporally disjoint sets, which we define as levels. This structure enables robots to execute tasks in parallel and asynchronously within a level, synchronizing only at level barriers, which guarantees collision-free operation by construction and provides robustness to timing uncertainties. To solve this formulation for large problems, we propose two specialized algorithms: an iterative temporal-relaxation approach for heterogeneous task sequences and a bi-level decomposition for homogeneous tasks that balances workload. We validate the LASER framework by fabricating a full-scale 2.4m x 6m timber slab with a two-robot system mounted on parallel linear tracks, successfully coordinating 108 subroutines and 352 screws under tight adhesive time windows. Computational studies show our method scales steadily with size compared to a monolithic approach.

Prefabricated timber construction offers major productivity benefits, yet on-site assembly, while largely machinic, remains human-controlled and ad-hoc. This paper presents an integrated multi-scalar construction framework for automated on-site assembly of point-supported cross-laminated timber floor slabs. Precise placement of large timber panels with cranes is currently hindered by occlusions, limited sensing, and unreliable pose verification during final alignment. The proposed system combines a digitally controlled tower crane with compact distributed robots embedded into timber elements. Each robot performs onboard vision-based detection of inherent building system features and transmits observations to a central coordinator, which fuses multi-view data to estimate the panel's pose. The fused estimate guides crane motion during placement, while passive alignment features enable force-guided final insertion. Large-scale outdoor experiments demonstrate reliable markerless multi-camera pose estimation and mechanical self-alignment. The results indicate that distributed robotic perception can enable robust crane-based assembly under realistic site conditions.

This project develops computational design methods for the modularization of digitally fabricated concrete elements. By integrating fabrication constraints and structural feedback into an agent-based model for early design stages it addresses a central challenge in industrialized construction: translating the formal freedom and structural capabilities enabled by digital fabrication processes with concrete into discrete, producible building modules. The presented method models each potential module as an autonomous agent that negotiates its size, shape, and position in a goal-oriented manner within a volumetric representation of a given design geometry. Through this behavioral simulation process, feasible modularization variants that balance material efficiency, structural logic, and fabrication requirements are identified. Behavior weights are optimized through reinforcement-learning based policy optimization, thus augmenting manual parameter tuning with data-driven search. By integrating various design objectives within one consistent interactive simulation process, this project presents a design method to foster flexible and sustainable precast concrete construction from digital fabrication methods. Agentenbasierte Methoden f & uuml;r die fertigungsgerechte Planung adaptiver Modulbauweisen aus BetonfertigteilenDieses Projekt entwickelt rechnergest & uuml;tzte Entwurfsmethoden zur Modularisierung digital gefertigter Betonelemente. Durch die Integration von Fertigungsrandbedingungen und strukturellem Feedback in ein agentenbasiertes Modell f & uuml;r fr & uuml;he Entwurfsphasen adressiert es eine zentrale Herausforderung des industriellen Bauens: die & Uuml;berf & uuml;hrung der durch digitale Fertigungsprozesse mit Beton erm & ouml;glichten formalen Freiheit und strukturellen Leistungsf & auml;higkeit in diskrete, produzierbare Bauteile. Die vorgestellte Methode modelliert jedes Modul als autonomen Agenten, der seine Gr & ouml;ss e, Form und Position innerhalb einer volumetrischen Repr & auml;sentation einer gegebenen Entwurfsgeometrie zielorientiert aushandelt. Durch diesen verhaltensbasierten Simulationsprozess werden geeignete Modularisierungsvarianten identifiziert, die Materialeffizienz, strukturelle Logik und Fertigungsanforderungen in Einklang bringen. Die Gewichtung der Verhaltensparameter wird mittels reinforcement-learning-basierter Policy-Optimierung optimiert und erg & auml;nzt damit die manuelle Parametrisierung durch eine datengetriebene Suche. Durch die Integration verschiedener Entwurfsziele in einen konsistenten, interaktiven Simulationsprozess pr & auml;sentiert dieses Projekt eine Entwurfsmethode zur F & ouml;rderung der flexiblen und nachhaltigen Vorfertigung von Betonbauteilen auf Basis digitaler Fertigungsmethoden.

Agent-based modeling and simulation (ABMS) has been widely employed to study emergent processes in collective robotic construction (CRC), where global architectural structures arise from local agent interactions. While these approaches reveal how complex assemblies can emerge without centralized control, they remain limited when an architectural goal is known but the behaviors required to achieve it are not. Most CRC workflows still depend on handcrafted heuristics. This paper presents a hybrid CRC workflow that integrates large language models (LLM) into the ABMS behavior design process. The system enables human–AI co-creation of robot behaviors, allowing an LLM agent to generate and negotiate behavioral strategies toward user-defined construction goals under partial observability. The approach is evaluated in simulation, comparing an LLM–heuristic hybrid against a heuristic-only baseline behavior. For well-documented swarm patterns, the LLM matches heuristic performance; for geometrically novel tasks, handcrafted heuristics retain an advantage. By embedding language-based reasoning within ABMS, this work expands participation in CRC behavior design and demonstrates a pathway for translating high-level design intent into adaptive, goal-oriented multiagent construction processes.

This research investigates methods for combining lightweight construction and sensor-based actuation for structural adaptation of architectural elements. If successful, structurally adaptive elements have the potential to achieve considerable resource savings. Given that research on this topic has recently expanded to include applications in architecture, this paper investigates ways to make its underlying methods and principles accessible to the architectural community. This is approached through the development of a design-to-operation method that augments architect-driven experimentation and speculation with strategies for structural design, actuator placement and control. In addition, the paper applies this method to the development of an interactive installation that showcases the concept of structural adaptation through a furniture-scale object conceived to engage non-experts with the intrinsic behaviors of adaptive structures in a safe and playful manner.

The construction sector significantly contributes to global greenhouse gas emissions, primarily from cement production. To mitigate this, a strategy focusing on reusing structural components from existing reinforced concrete structures is being explored. This study highlights challenges and presents initial results in designing new structures from reused elements. The objective is to develop methods for designing load-bearing structures using available elements from demolished buildings, categorized in a construction kit. The challenge is to find a structure that meets load-bearing capacity and architectural demands under the constraints of available elements. The feasibility of integrating existing foundations into the design process is investigated. Non-destructive measurements and simulations characterize the foundation and soil properties, while methods for strengthening or adjusting the foundation are developed. The design process considers the constraints of the foundation and construction kit, with the coordinated arrangement of reused elements and connection types controlling stress distribution. The structural reliability of the proposed structure is assessed, quantifying the effect of uncertainties related to individual elements. Modulare Strukturen aus wiederverwendeten Bauteilen: Herausforderungen bei der Nutzung von Bestandsgr & uuml;ndungenDie Bauwirtschaft tr & auml;gt durch die Zementproduktion erheblich zu den globalen Treibhausgasemissionen bei. Zur Reduktion soll eine Strategie zur Wiederverwendung von Stahlbetonbauteilen vorgestellt werden. In diesem Beitrag wird die Entwicklung von Methoden f & uuml;r den Tragwerksentwurf unter Verwendung verf & uuml;gbarer Bauteile, die aus abzurei ss enden Geb & auml;uden entnommen wurden und in einem Baukasten-System kategorisiert sind, pr & auml;sentiert. Die zentrale Herausforderung besteht darin, eine Struktur zu finden, die eine ausreichende Tragf & auml;higkeit aufweist und den architektonischen Anforderungen gen & uuml;gt. Hierbei sollen bestehende Fundamente in den Entwurfsprozess integriert werden. Dazu werden zerst & ouml;rungsfreie Messungen mit Simulationen kombiniert, um die Eigenschaften von Fundament und Boden zu charakterisieren. Weiterhin wird die M & ouml;glichkeit einer Verst & auml;rkung durch Biozementierung untersucht. Im optimierungsgesteuerten Entwurfsprozess werden die Fundamente und verf & uuml;gbaren Bauteile als Randbedingungen ber & uuml;cksichtigt, wobei der Kraftfluss durch die gezielte Anordnung der Bauteile und entsprechender Verbindungstypen gesteuert werden kann. Die Zuverl & auml;ssigkeit der abgeleiteten Tragstrukturen wird durch nichtlineare Simulationen bewertet und Unsch & auml;rfen werden bez & uuml;glich des Bauteilzustands quantifiziert.

This paper presents the co-design methods for a new hybrid load-bearing system as a strategy for advancing bio-based architecture. Timber and natural fiber polymer composites (NFPC) are combined into a hybrid system, offering opportunities to leverage their strengths while balancing the use of natural resources. The system performs synergistically, with each material fulfilling complementary roles. Timber extrapolates its structural function by acting as an embedded frame for the fibers to be wound on. The paper presents computational methods designed to optimize material performance while integrating functionalities and fabrication opportunities. A dual-robot winding method is presented as a solution for balancing winding tension in the structure during fabrication. The hybrid system is demonstrated through the design and construction of a pavilion, the first to combine flax fibers with a partially bio-based resin and timber into a dual-robotically fabricated structure on an architectural scale. The project represents further advancements in multi-robot fabrication and a novel material approach toward bio-based hybrid systems in architecture.

This paper presents the development of a co-designed timber assembly system with a mobile robotic platform for collective robotic construction (CRC) across three successive demonstrations. Iterative advances in the relationship between material, mechanical robot design, architectural design, and robotic control enable the system to advance from showcasing robotic capabilities, to realizing the planar assembly of timber struts, and finally to achieving the spatial construction of truss-like structures. The first two demonstrations established a foundation for scalable coordination between multiple small mobile robotic actuators and standardized, linear timber building elements they manipulate for 2D assembly. The third demonstration extended this CRC system to the construction of spatial assemblies, demonstrating real-time planning adjustments and the coordination of homogeneous robotic agents. This research argues that co-design, linking the various research aspects in CRC, can be leveraged in the development of systems to progressively meet more complex fabrication goals. The outcomes highlight the potential of CRC as an alternative approach to architectural construction compared to centralized, large-scale machinery workflows.

Building disassembly is critical for circular economy material reuse, yet remains rare due to cost and safety constraints, leading to demolition and material downcycling. Automation could improve both efficiency and safety, but currently available technology does not yet enable full automation. We propose a human–robot collaboration system architecture that uses agentic large language models. We test this approach in building disassembly—an unstructured, safety–critical domain where conventional pre-programmed robotics are inadequate. The agentic architecture combines curated domain knowledge, physics simulation for stability validation, and natural language interfaces, enabling the robot to participate through proactive reasoning rather than follow control commands. We evaluated the architecture through three progressively complex scenarios: collaborative spatial adaptation, collaborative decision-making, and learning. The main contribution is a modular, data-grounded HRC methodology in which specialized LLM agents perform agentic reasoning: the robot assesses situations, retrieves relevant procedural knowledge, validates decisions through simulation, and negotiates solutions with human operators. This proof of concept demonstrates that agentic multi-agent LLM systems can enable adaptive human–robot collaboration under uncertainty, beyond natural language interfaces through integrated domain knowledge, physics validation, and agentic reasoning.

Large-scale 3D printing promises major benefits for the architecture, engineering and construction (AEC) industry but faces challenges including variable material behaviour, multi-machine coordination and dynamic process control. This paper presents a data-driven digital twin that couples real-time monitoring, predictive modelling and adaptive feedback. Machine parameters are continuously linked to material rheology and print outcomes, forming a virtual representation of the process. A clustering-based analysis classifies material mixtures and drives feedback control of printing parameters, improving stability, accuracy and efficiency. The digital twin is demonstrated on a large-scale setup with two machines operating in parallel and five services forming a closed feedback loop. Experiments show reduced material consumption by 7.5% and more consistent, higher-quality prints when using the predictive digital twin. These results indicate that integrating digital twins into large-scale 3D printing can support more robust, adaptive and scalable production.

Collective robotic construction (CRC) is an emerging subset of on-site construction robotics, which, despite its interdisciplinary nature, remains predominantly centered within the field of engineering. The goal of this research is to create a highly accessible workflow for developing and working with CRC systems that allows for their cyber-physical control. To demonstrate this concept, a low complexity robotic system was created in conjunction with an agent-based model (ABM) and associated software framework, enabling direct design and control of a swarm of mobile robots. The proposed system consists of a team of homogenous mobile robots that can actively rearrange a set of identical custom digital materials. The developed robotic system was conceptually extended, and the provided workflow was experimentally tested in a workshop setting with architectural students. The results of the workshop, which included four different conceptualizations of the provided robotic system, investigated various research topics within CRC, demonstrating the ability of architects to aid further conceptualization of research in the field.