Knitting 4D garments with elasticity controlled for body motion
Z. Liu (Centre for Perceptual and Interactive Intelligence Limited, Hong Kong, TU Delft - Materials and Manufacturing)
Xingjian Han (Boston University)
Yuchen Zhang (Centre for Perceptual and Interactive Intelligence Limited, Hong Kong)
Xiangjia Chen (Centre for Perceptual and Interactive Intelligence Limited, Hong Kong)
Y. Lai (Cardiff University)
E.L. Doubrovski (TU Delft - Mechatronic Design)
Emily Whiting (Boston University)
C.C. Wang (The University of Manchester)
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Abstract
In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in different elastic levels by single-jersey jacquard (SJJ) with two yarns. We design the distribution of elasticity for a garment by physics-based computation, the optimized elasticity on the garment is then converted into instructions for a digital knitting machine by two algorithms proposed in this paper. Specifically, a graph-based algorithm is proposed to generate knittable stitch meshes that can accurately capture the 3D shape of a garment, and a tiling algorithm is employed to assign SJJ patterns on the stitch mesh to realize the designed distribution of elasticity. The effectiveness of our approach is verified on simulation results and on specimens physically fabricated by knitting machines.