The Master in Robotics and Advanced Construction (MRAC) seeks to train a new generation of interdisciplinary professionals who are capable of facing our growing need for a more sustainable and optimised construction ecosystem. The Master is focused on the emerging design and market opportunities arising from novel robotic and advanced manufacturing systems.
Through a mixture of seminars, workshops, and studio projects, the master programme challenges the traditional processes in the Construction Sector. It investigates how advances in robotics and digital fabrication tools change the way we build and develop processes and design tools for such new production methods.
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IAAC Workshop led by the Professorship of Digital Fabrication | Technical University of Munich Faculty: Begüm Saral, Avishek Das and Pit Siebenaler Design Goals and Process When designing with the bricks, we began looking at their imperfections. We thought about using and exposing these defects as part of the material’s architectural expression. The idea focused … Read more
Robotic Disassembly& Reassembly with Spatial AI In this blog post, we’re presenting the project developed during IAAC 2026 Workshop 2.2 in collaboration with the Augmented Fabrication Lab. Our focus was to step beyond purely digital design and engage directly with physical processes, using robotic systems and sensor-based feedback. Through hands-on experimentation with robotic fabrication and … Read more
Robotic Brickwork Disassembly & Reassembly Enabled by Spatial Artificial Intelligence In this blog post, we’re sharing the project we built during the IAAC 2026 Workshop 2.2 with the Augmented Fabrication Lab. Our main goal was to move beyond just designing on a computer and actually work with robots and smart sensors in the real world. … Read more
Process Overview Material Disassembly Material Evaluation & Design Generative Assembly Human Visual Inspection Manual Damage Categorization First Steps First approaches or manual Assembly AI-Based Evaluation Stack 2_Brick 0 We noticed inconsistencies in the evaluation results. After finalizing the prompt, we ran the test twice for each brick, averaged the two values, and visualized the results … Read more
