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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PalmPilot 2000

No mouse. No keyboard. Just you.  Github Link: https://github.com/Adronegenius/palmpilot2000.git Problem/Opportunity Current 2D CAD layout tools rely heavily on complex UI layers and precise mouse manipulation. These become barriers for: PalmPilot2000 addresses this by introducing a body-centered interaction system, where gestures drive the logic of selecting, moving, and placing elements on a plan — with visual … Read more

Hardware III _ LEGO_GUIDE

Github : https://github.com/Clarrainl/Lego_AR_Interface Introduction What if LEGO instructions could appear right on your table, adapting to the bricks you have?Lego_AR_Interface turns the simple act of LEGO building into a smart and interactive experience. Combining computer vision, real-time projection, and gesture recognition, the system guides users through constructing custom models—no screen touches required. Concept: Build from Random Bricks … Read more

Machine Learning Strategies for Toolpath Optimization in Fabrication

In the ongoing pursuit of efficient toolpath generation, we set out to build a modular, logic-driven system capable of planning subtractive manufacturing strategies. The framework integrated zonal segmentation, directional movement, and dynamic state awareness; its goal was adaptability and long-term scalability. While we achieved full system functionality, this initial iteration exposed the distance between a … Read more

Interlock Tower

Rethinking Towe Typology with AI: This project explores the redesign of contemporary tower structures using machine learning (ML), challenging the repetitive, profit-driven design seen in cities like Hong Kong. The goal is to discover new typologies through AI and stacking rules, and tren translate them to a robotic fabrication system (pick and place). AI-generated towers … Read more

Workshop 3.1_KAPLA-Nest

| INTRODUCTION | Learning Structures: From Parametric Rules to Machine-Made Forms. In this project, we explored the interplay between parametric design, machine learning, and robotic fabrication. Starting from Kapla block assemblies controlled by simple deformation rules, we trained a GAN to reinterpret and generate new structural variations. The process concluded with robotic pick-and-place construction, closing … Read more

Pioneering Design: AI Driven Kapla Stack Generation

A Closed-Loop RL-GAN-ML Pipeline for Generative Design VIDEO: Objective:  Demonstrate an intelligent system for stable Kapla stack design, showcasing its intelligent, iterative pipeline. Automated Generation of Stable Kapla Plank Stacks. 1. Introduction The Python script (`loop.py`) presents a sophisticated framework for automating the design of stable Kapla plank stacks, a wooden construction toy consisting of … Read more

Software III _ UN_LOG FACTORY

Github : https://github.com/Clarrainl/UN_LOG-Factory | INTRODUCTION | Detecting wood defects in 3D-scanned logs using Machine Learning In the timber industry, a significant portion of wood gets discarded due to irregularities or defects that make it unusable under standard practices. However, many of these logs can still be used creatively or structurally if properly understood and classified. This project … Read more

Software III: AI Optimized Earth Injection Deposits

injection printing

Github: https://github.com/Adronegenius/Software-III-AI-Optimized-Earth-Injection-Deposits The process begins with human fabrication of woven modules using flexible rods or sticks. Due to tension, compression, and human variability, the woven pattern often deforms. Our system integrates computer vision to scan these deformations and a robotic arm to inject earth between structural members at optimized locations. This bridges physical craft and … Read more

Reinforcement Learning for Robot Obstacle Avoidance

adapted from IaaC´s Artificial Intelligence Program’s study of machine learning for robotic pick and place. (https://blog.iaac.net/reinforcement-learning-for-robotic-pick-and-place/research). Github Repository. https://github.com/LaurenD66/ROS-GridWorld-RL-with-Obstacles In a recent study by IaaC´s Artificial Intelligence Program, students used reinforcement learning models to train an (robotic) agent to move through a space defined by a simple grid from an origin to a goal, while … Read more