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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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

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

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

Robotics Solutions for 3D Space Analysis

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

Hey Jarvis, let’s Collaborate!

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

Peacock Immersive Experience

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

Machine Learning to predict no. of seating spaces

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

Timber outlook

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

Predicting Ceramic Underglaze Colors

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

Manifesto for a New Era in Construction: Embracing AI

“In the dawn of this new era, the construction industry stands at the threshold of transformation, poised to redefine its legacy through the power of Artificial Intelligence (AI) and comprehensive data analytics.”* This manifesto aims to put forward the benefits of AI and how it can help the The construction business be improved by collecting … Read more

Reclaim Rover

The integration of a rover or swarm of rovers into construction demolition sites represents a paradigm shift in waste management practices. Equipped with advanced sensors and AI algorithms, this rover possesses the capability to accurately identify and segregate valuable materials such as steel and metal amidst debris and rubble. These rovers operate seamlessly alongside human … Read more

Truss and Roof Health

ROBOTIC SOLUTIONS FOR 3D SPACE ANALYSIS AIM This workshop ran in collaboration with Noumena and IAAC where we were introduced to a environmental scanning and data processing workflows which combined the use of photogrammetry and point-cloud data. The site of the study was at IAAC’s new building which is yet to be constructed. From this … Read more

PatchX

Aim The project was aimed to develop a methodology to detect damages in walls with the help of Yolo’s trained models furthering to gain the quantitative and economic analysis of the development any project. Workflow Initially, we conducted a site scan using an RGB camera of Dji drone the site was mapped section by section … Read more

Stylized Point Cloud

Aim The main objective is to generate a new formation of point cloud of the new IAAC building, that is inspired from a style (Artistic /Architectural) using  AI / Machine learning and change the existing point cloud with the the new stylized point cloud. State of The Art Image-to-image translation is a class of vision … Read more