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.
“Precision becomes poetry through reflection and sound.” Reflection is an immersive installation that explores the potential of precision and reflection between two robotic arms through synchronized movements. Equipped with mirrors, the robots become both instruments and performers. Concept: The law of reflection The law of reflection states that the angle of incidence is equal to … Read more
INTRODUCTION In today’s construction industry, a large portion of timber is discarded due to its non-standard shape, curvature, or internal defects. Un_Log Factory challenges this paradigm by proposing a digitally augmented fabrication system that embraces the natural irregularity of timber. Instead of seeing bent or cracked logs as waste, our process redefines them as raw … Read more
A Real-Time Audio-Visual Stone Symphony Rock the Rock is an interactive audio-visual installation that identifies and tracks rocks in real time, generating dynamic sound and projection overlays. By leveraging computer vision and finite state machines, it transforms geological forms into a sensory experience. Concept and Context This project served as our introduction to Finite State … Read more
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
| 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
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
Github : https://github.com/j-albo/robotic-3d-space-analysis INTRODUCTION Scanning irregular terrains with today’s scanning technology is crucial for obtaining precise environmental models, optimizing planning and execution in architectural projects. Its high-resolution capture capability allows for mapping complex surfaces and detecting floor level variations imperceptible to the human eye, improving efficiency and reducing errors in design and construction. WHY USING A MOBILE … Read more
CONTEXT Every year, there is about $10 trillion in construction-related spending globally, equivalent to 13 percent of GDP. This makes construction one of the largest sectors of the world economy. The sector employs 7% of the world’s working population and, by building the structures in which we live and work, which create our energy, materials, … Read more
Context Architecture, in general, is the least optimized industry. This results in more workload and less output. Hence the productivity rate is negative 1.4. In the furniture industry, even loose or modular furniture, typically expected to have quicker turnaround times faces significant delays due to the manual nature of customization and the complexity of matching … Read more
Abstract The project “Robots as Advertising Agents” explores the integration of robotics in the advertising industry to create dynamic, interactive, and memorable brand experiences. As advertising shifts toward experiential and engaging methods, robots equipped with advanced technologies such as artificial intelligence, sensors, and communication systems can act as captivating agents that interact with audiences in … Read more
This project explores a framework for Human-Robot Collaboration (HRC) and behavioural fabrication, focusing on constructing a Jenga-like tower using small timber blocks. Using the Agent-Based Modeling system (ABxM) from the Institute for Computational Design and Construction (ICD), a communication network was established integrating a human participant, a computer vision system, and an interactive audio interface. … Read more
Concept Most of Virtual Experiences are designed and model for humans and by humans. In this scenario believe the overall concept is that the game platform is seen from the perspective of an animal. References Aim “Our goal is to offer humans a unique experience through the eyes of a peacock. This game platform immerses … Read more
Aim: To predict the number of seating spaces based on various types of seating layout, number of corridors and dimensions of generative enclosed rectangular spaces such as an auditorium. Objectives: Dataset Design: To create Dataset for the required problem, a synthetic dataset is designed with the help of various bylaws supporting the problem. Data Analysis: … Read more
The project’s objective was to create a machine-learning model capable of classifying repurposed timber components within an assembly process as either structural or non-structural, using factors such as defect quantity, age, and exposure to weather conditions as input. Dataset Generation and Analysis The dataset was produced using Roboflow by utilizing scans of the timber elements … Read more
Our aim is to develop a machine learning model that accurately predicts the color outcome of ceramic underglazes based on their ingredient compositions and firing conditions. In the world of ceramic art, the process of underglazing involves applying colors to pottery which are then sealed under a transparent glaze before firing. However, predicting the final … Read more
