Hybrid Embroidery: Exploring Interactive Fabrication in Handcrafts

Abstract

This paper presents Hybrid Embroidery, a framework for interactive fabrication that leverages computational methods to broaden the possibilities of the craft of embroidery. Combining embroidery techniques, generative design methods, computer vision and a computerized embroidery machine, we show how this framework elicits a variety of innovative fabrication experiences that emphasize open-ended exploration, improvisation and play. The paper documents this framework, a series of sample results, challenges and next steps. It further outlines some of its implications for supporting creative exploration through real-time and direct manipulation of materials and close human-machine interaction.

The application of robotics and artificial intelligence in embroidery: challenges and benefits

“…The Industrial Revolution in the 20th century converted the embroidery process from manual to mechanical, making mass production possible (Sharpe and Chapman, 1996). More and more advanced tools such as robotic embroidery systems are emerging (Su and Ouyang, 2021; Ahn and Kim, 2022; Jhanji, 2018; Lee and Llach, 2020). The robotic systems significantly increase the ability of producing diverse and complex embroidery items.…”

See - Sense - Respond: An adaptive robotic fabrication framework for post-processing of glass fiber-reinforced plastic architectural panels

“…Other research efforts focus on visionbased systems to inform the digital representation and adapt tooling in accordance with the deviation between the physical realm and the digital representation (Dörfler, Rist and Rust, 2013;Schwartz et al, 2014;Brugnaro et al, 2016;Ercan Jenny et al, 2020;Nicholas et al, 2020). More recently, researchers began looking into how this established feedback loop can be utilized as a conversational method for designing within more interactive design-fabrication workflows (Zoran and Paradiso, 2013;Weichel et al, 2015;Capunaman, 2020;Lee and Llach, 2020) Within this body of work, we propose a computational framework for high fidelity reconstruction of the work object to inform subsequent fabrication operations and register the digital twin within the robot's coordinate system within tooling tolerances. Even though similar vision-based approaches to capture work environment exists in high precision fabrication scenarios such as the aerospace industry, these solutions are often black-boxed, task-specific and Figure 1 An example application of GFRP façade panels on SFMoMA Expansion Building.…”