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: Chapter in Book/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - SCF 2022 - 7th Annual ACM Symposium on Computational Fabrication
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450398725
DOIs
Publication statusPublished - 26 Oct 2022
Event7th Annual ACM Symposium on Computational Fabrication, SCF 2022 - Seattle, United States
Duration: 26 Oct 202228 Oct 2022

Publication series

NameProceedings - SCF 2022 - 7th Annual ACM Symposium on Computational Fabrication

Conference

Conference7th Annual ACM Symposium on Computational Fabrication, SCF 2022
Country/TerritoryUnited States
CitySeattle
Period26/10/2228/10/22

Keywords

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

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