An Augmented Knitting Machine for Operational Assistance and Guided Improvisation

要旨

Computational mediation can unlock access to existing creative fabrication tools. By outfitting an otherwise purely mechanical hand-operated knitting machine with lightweight sensing capabilities, we produced a system which provides immediate feedback about the state and affordances of the underlying knitting machine. We describe our technical implementation, show modular interface applications which center the particular patterning capabilities of this kind of machine knitting, and discuss user experiences with interactive hybrid computational/mechanical systems.

著者
Lea Albaugh
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Scott E. Hudson
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Lining Yao
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
論文URL

https://doi.org/10.1145/3544548.3581549

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Sensor Integration

Hall G1
6 件の発表
2023-04-27 18:00:00
2023-04-27 19:30:00