The paper presents the developments of a series of methods to train a fabrication system for the integration of material performances in timber manufacturing processes, combining robotic fabrication together with different sensing strategies and machine learning techniques, and their further application within a prototypical design to manufacturing workflow. The training cycle, spanning from the recording of skilled human experts to autonomous robotic explorations, aims to encapsulate different layers of instrumental knowledge into a design interface, giving designers the opportunity to engage with material and tool affordances as process driver. The training methods are evaluated in a series of experiments and design iterations, proving their potential in the development of customized design to manufacturing workflows and integration of material performances, with a specific focus on timber.
Adaptive Robotic Carving: Training Methods for the Integration of Material Performances in Timber Manufacturing
2019-01-01
In: Willmann, J and Block, P and Hutter, M and Byrne, K and Schork, T, (eds.) Robotic Fabrication in Architecture, Art and Design 2018 (ROBARCH 2018). (pp. pp. 336-348). Springer: Cham, Switzerland. (2019)
Paper
Electronic Resource
English
Technique for carving honeycomb material
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