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.
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
Abstract The escalating challenge of managing construction and demolition waste necessitates innovative approaches to enhance sustainability in the construction industry. This research proposes an automated robotic workflow leveraging Multi Agent Systems (MAS) and computer vision to repurpose planar construction waste materials, such as tiles, into new construction elements like bricks or walls. The primary objective … Read more
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
In this workshop, we collaborated all together to investigate the neuro-evolution (artificial evolution defining neural networks) as a strategy to develop autonomous behaviours of mobile robots (in this workshop we used Turtlebots) to perform given tasks. We used N.E.A.T. (NeuroEvolution of Augmenting Topologies) as a method framework for artificial evolution of these robot controllers and increased … Read more
