The Master Programme in Robotics and Advanced Construction is an innovative educational format that offers interdisciplinary skills and understanding through a series of class seminars that are put into practice through hands-on workshops. IAAC gives students the opportunity to create individual studio agendas and develop Pilot Thesis Projects based on the knowledge acquired during the seminars and workshops split into 3 Modules. In this way, IAAC puts together an experimental learning environment for the training of professionals with both theoretical and practical responses to the increasing complexity of the construction sector.

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A Multi-Agent System for Robotic Metal Bending.

Course Overview The MRAC Applied Theory III course focuses on the exploration of collaborative robotics through the lens of ( MAS ) Multi-Agent Systems, in which different components of the system work autonomously and collaborate in order to execute complex tasks. The course investigates how digital and physical bots , operate within a shared environment … Read more

Applied Theory III _ Un_Log Factory

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

Rock the Rock

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

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

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

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

Timber Narratives

Building on the principles of disassembly explored last semester, this phase of the Timber Narratives project delves deeper into advanced data-driven design strategies. We now capture and utilize timber colour values through enhanced scanning technologies, integrating this data into our designs. Additionally, we’ve implemented machine learning with logistic regression for precise categorization of timber for … Read more

ReWeave_3.0

Abstract: The ReWeave project develops a robotic system to repurpose construction and demolition (C&D) waste into functional, attractive walls, enhancing human-robot collaboration. We created a database by scanning broken tiles to extract shape, size, and color information, then developed custom nesting algorithms to optimize tile arrangement. The workflow includes scanning tiles, exporting outlines via ROS, … Read more

Glazing Virtuoso

Introduction Glazing Virtuoso marks a pivotal shift in the spray glazing industry, where craftsmanship meets cutting-edge robotics to usher in a new era of creative expression and manufacturing precision. This project enhances creative workflows by seamlessly integrating intricate spray glazing techniques, that would blend in traditional artisanal craft empowering artists with unprecedented control that could … Read more