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.
Machine Learning for Robotic Fabrication
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[ 1 ] FIRST QUESTIONS : The application of Machine Learning (ML) to the prediction of 3D printing parameters presents a challenge that necessitates a structured approach and raises many questions on how to approach this combination. To effectively explore this integration, it is essential to address three core questions: What are the process and the … 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/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
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
