Knitting 4D garments with elasticity controlled for body motion

Zishun Liu, Xingjian Han, Yuchen Zhang, Xiangjia Chen, Yu Kun Lai, Eugeni L. Doubrovski, Emily Whiting, Charlie C.L. Wang

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
124 Downloads (Pure)


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.

Original languageEnglish
Article number3459868
Pages (from-to)16
JournalACM Transactions on Graphics
Issue number4
Publication statusPublished - 2021

Bibliographical note

Accepted Author Manuscript


  • 4D garment
  • computational fabrication
  • elasticity control
  • knitting


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