Abstract
This paper shows a computational approach for knitting net shape preforms with bespoke 3D shapes and patterns. The approach takes partial knitting as the major shaping technique and as the fabrication constraints to generate multi-coloured pixel-based knitting maps based on given 3D meshes. The generation process include 5 steps: 1 generation of wales, 2 generation of courses, 3 generation of 2D knitting maps, 4 stitch placement optimizations, and 5 pattern variations. At final stage, users can get a knittable 3D mesh with each face representing each stitch, as well as a 2D pixel-based knitting map. The knittable 3D mesh allows designers to further design pattern variations, the 2D knitting map can be directly used for generating knitting information in knitting software or easily followed by users.
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Acknowledgements
This research is supported by Supported by Open Projects Fund of Key Laboratory of Ecology and Energy-saving Study of Dense Habitat (Tongji University), Ministry of Education 201810102. Machine knitting experiments have been done in collaboration with Stoll and Chemtax Industrial Co Ltd.
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Liu, Y., Li, L., Yuan, P.F. (2020). A Computational Approach for Knitting 3D Composites Preforms. In: Yuan, P., Xie, Y., Yao, J., Yan, C. (eds) Proceedings of the 2019 DigitalFUTURES . CDRF 2019. Springer, Singapore. https://doi.org/10.1007/978-981-13-8153-9_21
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DOI: https://doi.org/10.1007/978-981-13-8153-9_21
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