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.
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. Data Structure: Prediction Comparison between normal (linear) regression and XGB regression Prediction Comparison between Kernel Ridge regression and XGB regression Conclusion:
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
Optimizing 3D Printing with AI prediction Introduction In this seminar we applied the concepts of machine learning to estimate the deformation during drying of simplified 3D printed clay objects. To do this, we trained an artificial neural network (ANN) to predict the movement of discrete points within the printed object. This project is very relevant … Read more
Our project involves the fabrication of a curved surface using cork panels that have been discretized into unique four-sided shapes. Our previous approach involved cutting each panel individually, but we aim to streamline the process by using machine learning to classify the panels into five distinct groups. We will then design and create a mold … Read more
