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.
Aim “Create a range of robotic mini-games showcasing dexterity and quick reflexes, ideal for casual enjoyment.“ For this one week workshop, we drew inspiration from various games such as infinite passes, penalty shootouts, and boxing, aiming to adapt them for robotic play. Initially leaning towards infinite passes (football), we ultimately found boxing more compatible with … Read more
Due to limitation regarding the file size and quality, these performances are muted, lower quality and sped up to be under the limited file capacity. Dancing Queen(s) is an endeavor featuring a pair of robots performing synchronized dance moves. These choreographed movements mirror those of a trainer, who leads, and a follower, who emulates the … Read more
At the workshop led by Madeline Gannon, we had the chance to delve into robotic movement, prioritizing creative freedom over conventional targets like accuracy and repeatability. The workshop was designed as a breeding ground for creativity, facilitated by software components that allowed exploration without the constraints of a kinematic solver. Given the project’s one-week duration … Read more
This project was part of a 1 week workshop at IAAC, utilizing the institute’s two ABB IRB6700 industrial robots. The workshop incorporated Dr. Gannon’s sophisticated simulation tools, which provide safe, real-time control of industrial robots. Under the guidance of Madeline showing us how to sketch with robots we were able to work within a flexible … 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
Revolutionizing Construction: The Oura Project’s Path to Sustainability through Digital Solutions Introduction The construction industry stands at a critical crossroads in the face of escalating global climate challenges. As a significant contributor to worldwide greenhouse gas emissions, it is imperative for this sector to undergo a transformation. The Oura Project emerges as a pioneering initiative, … Read more
