The vision of the Cluster of Excellence Integrative Computational Design and Construction for Architecture (EXC IntCDC) is to harness the full potential of digital technologies in order to rethink design, fabrication and construction based on integration and interdisciplinarity, with the goal of enabling game-changing innovation in the building sector as it can only occur through highly integrative fundamental research in an interdisciplinary, large-scale research undertaking.

The Cluster aims to lay the methodological foundations for a profound rethinking of the design and building process and related building systems by adopting an integrative computational approach based on interdisciplinary research encompassing architecture, structural engineering, building physics, engineering geodesy, manufacturing and system engineering, computer science and robotics, social sciences and humanities. We aim to bundle the internationally recognised competencies in these fields of the University of Stuttgart and the Max Planck Institute for Intelligent Systems to accomplish our research mission.

The Cluster’s Industry Consortium will ensure direct knowledge exchange, transfer and rapid impact. Taking into account the significant difference between the building industry and other industries, we will tackle the related key challenges of achieving a higher level of integration, performance and adaptability, and we will address the most important building typologies of multi-storey buildings, long-span buildings, and the densification of urban areas.

The Cluster’s broad methodological insights and interdisciplinary findings are expected to result in comprehensive approaches to harnessing digital technologies, which will help to address the ecological, economic and social challenges that current incremental approaches cannot solve.

We envision IntCDC to significantly shape the future of architecture and the building industry through a higher-level integration of computational design and engineering methods, effective cyber-physical (tightly interlinked computational and material) robotic construction processes and new forms of human-machine collaboration, efficient and sustainable next-generation building systems, and socio-cultural and ethical reflection. Thus, the Cluster will have significant impact on creating the conditions required for a liveable and sustainable future built environment, high-quality yet affordable architecture and a novel digital building culture.
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Jun 16, 2025 - EXC IntCDC Research Project 26 'AI-supported Collaborative Control and Trajectory Generation of Mobile Manipulators for Indoor Construction Tasks'
Hierholz, Alice; Gienger, Andreas; Sawodny, Oliver, 2025, "Replication Data for: Improving Data-based Trajectory Generation by Quadratic Programming for Redundant Mobile Manipulators", https://doi.org/10.18419/DARUS-5029, DaRUS, V1, UNF:6:4JKlZHhid5dpl97qNrg3EQ== [fileUNF]
Dataset containing 36000 trajectories generated by an Optimal Control Problem (OCP) for a mobile manipulator with 10 degrees of freedom. The OCP is solved for an initial joint state configuration and a unique randomly chosen desired tool-center-point (TCP) target pose which lies within a certain goal region. The desired TCP position is computed by...
Tabular Data - 7.0 MB - 24 Variables, 36000 Observations - UNF:6:AaGhFPs1QwdQQnalWUknEQ==
Data
Inputdata for the NN. Start joint position, the corresponding start TCP pose and the TCP desired target pose. In order to reduce the dimensionality of the input layer, the orientation is described via quaternions.
Tabular Data - 62.5 MB - 171 Variables, 36000 Observations - UNF:6:H6HShXWLHs0A/ZtcNAqZyw==
Data
Outputdata for the NN. The output consists of the optimal joint positions and velocities for each collocation point k ∈ [0; N], the joint accelerations for k ∈ [0; N−1] and the optimal end time.
Jun 5, 2025 - EXC IntCDC Research Project 18 'Holistic Quality Model for Extension of Existing Buildings'
Balangé, Laura; Kerekes, Gabriel; Frolow, Rudolf; Yang, Yihui; Abolhasani, Sahar; Schwieger, Volker, 2025, "Point Clouds of the livMatS Biomimetic Shell at Various Stages of the Construction Process", https://doi.org/10.18419/DARUS-5093, DaRUS, V1
The data set contains the point clouds of different construction stages of the of the building demonstrator 'livMatS Biomimetic Shell' during the manufacturing process, as well as a point cloud of the pavilion after construction of the shell. The data is named according to the numbering of the most recently built element, which does not necessarily...
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