A Tool for Searching Active Bending Bamboo Strips in Construction via Deep Learning
1DesignLab published a paper about its first research on deep learning in innovative material system and digital fabrication in the 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA). This is an ongoing research, and the paper demonstrates the initial results.
Abstract
As a popular material, the structural use of bamboo in architecture is commonly associated with active bending. As natural material, the deformation of unprocessed bamboo strips is affected by many factors such as the distribution of nodes, whose impact on deformation is difficult to precisely programme for each individual case and thus often cause discrepancies between generic digital simulation and construction. This research proposes a tool for searching active bending bamboo strips via deep leaning based on a multi-task neural network. The tool is able to predict both the number and locations of nodes suggested on bamboo strips according to a target curve as tool input. By approximating the prediction, users can find a strip that is most likely to deform into the desired geometry.
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