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Innochain ESR10 ‘Simulating Robotic Feedback’: Adaptive Robotic Training for Subtractive Manufacturing
First and second supervisors
Abstract
Integrating sensing with robotic fabrication procedures, the research wants to investigate potential methods for analysing qualitative material feedback and integrate them into the design environment as the fabrication unfolds. To achieve this, the research proposes the development of an adaptive framework for subtractive fabrication strategies where the stages of design and fabrication are not arranged in a linear fashion but rather in a continuously updating loop informed by sensor data and sequential training sessions. This is articulated around two main areas: 1) An ‘active’ simulation environment able to locally described the workpiece and store continuously updating layers of ‘affordances’ 2) A trained robotic agent able to communicate through feedback loops and operate, increasingly well, within this environment.
The training of the system is structured, on one hand, through the recording of skilled human experts performing subtractive operations (e.g. carving procedures with a set of chisels and gouges), while on the other through ‘extensive’ robotic explorations directly operating with the material. In both cases, the recorded information is subsequently compiled into large datasets and used within a machine learning procedure (Artificial Neural Network) to train an adaptive robotic system for subtractive fabrication processes with a similar range of materials and tools.
This allows investigating to what extent the system is able to address changes in the materials, tools or design intentions, and, at the same time, to become a platform to research how specific sets of affordances could drive the fabrication process, uniquely shaping its physical outcome.
Biography
Giulio is a trained architect with a strong interest in computational tools and robotic fabrication for architectural production. He is currently Research Assistant (Marie Curie Trainee) at The Bartlett School of Architecture in London as part of the InnoChain Research Network. His research (ESR 10) focuses on exploring adaptive robotic fabrication processes and sensing methods that allow designers to engage with the qualitative properties of heterogeneous materials. Previously he received a B.Arch in Architectural Sciences from IUAV University of Venice and an M.Sc. in Integrative Technologies and Architectural Design Research from the University of Stuttgart.