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Machine knitting is an increasingly accessible fabrication technology for producing custom soft goods. However, recent machine knitting research has focused on knit shaping, or on adapting hand-knitting patterns. We explore a capability unique to machine knitting: producing multilayer spacer fabrics. These fabrics consist of two face layers connected by a monofilament filler yarn which gives the structure stiffness and volume. We show how to vary knit patterning and yarn parameters in spacer fabrics to produce tactile materials with embedded functionality for forming soft actuated mechanisms and sensors with tunable density, stiffness, material bias, and bristle properties. These soft mechanisms can be rapidly produced on a computationally-controlled v-bed knitting machine and integrated directly into soft objects. 

Computational handweaving combines the repeatable precision of digital fabrication with relatively high production demands of the user: a weaver must be physically engaged with the system to enact a pattern, line by line, into a fabric. Rather than approaching co-presence and repetitive labor as a negative aspect of design, we look to current practices in procedural generation (most commonly used in game design and screen-based new media art) to understand how designers can create room for suprise and emergent phenomena within systems of precision and constraint. We developed three designs for blending real-time input with predetermined pattern features. These include: using camera imagery sampled at weaving time; a 1:1 scale tool for composing patterns on the loom; and a live "Twitch'' stream where spectators determine the woven pattern. We discuss how experiential qualities of the systems led to different balances of underdetermination in procedural generation as well as how such an approach might help us think beyond an artifact/experience dichotomy in fabrication. 

The current work examines interactions that are enabled when depositing a human-safe hydrogel onto textile substrates. These hydrogel-textile composites are water-responsive, supporting reversible actuation. To enable these interactions, we describe a fabrication process using a consumer-grade 3D printer. We show how different combinations of printed hydrogel patterns and textiles create a rich actuator design space. Finally, we show an application of this approach and discuss opportunities for future work. 

The Internet-of-things (IoT) embeds computing in everyday objects, but has largely focused on new devices while ignoring the home's many existing possessions. We present a field study with 10 American families to understand how these possessions could be included in the smart home through upcycling. We describe three patterns for how families collaborate around home responsibilities; we explore families' mental models of home that may be in tension with existing IoT systems; and we identify ways that families can more easily imagine a smart home that includes their existing possessions. These insights can help us design an upcycled approach to IoT that supports users in reconfiguring objects (and social roles as mediated by objects) in a way that is sensitive to what will be displaced, discarded, or made obsolete. Our findings inform the design of future lightweight systems for the upcycled home. 

Knitting creates complex, soft fabrics with unique texture properties that can be used to create interactive objects.However, little work addresses the challenges of designing and using knitted textures computationally. We present KnitPick: a pipeline for interpreting hand-knitting texture patterns into KnitGraphs which can be output to machine and hand-knitting instructions. Using KnitPick, we contribute a measured and photographed data set of 472 knitted textures. Based on findings from this data set, we contribute two algorithms for manipulating KnitGraphs. KnitCarving shapes a graph while respecting a texture, and KnitPatching combines graphs with disparate textures while maintaining a consistent shape. KnitPick is the first system to bridge the gap between hand- and machine-knitting when creating complex knitted textures. 

Abstract: 3D printing offers significant potential in creating highly customized interactive and functional objects. However, at present ability to manufacture functional objects is limited by available materials (e.g., various polymers) and their process properties. For instance, many functional objects need stronger materials which may be satisfied with metal printers. However, to create wholly interactive devices, we need both conductors and insulators to create wiring, and electronic components to complete circuits. Unfortunately, the single material nature of metal printing, and its inherent high temperatures, preclude this. Thus, in 3D printed devices, we have had a choice of strong materials, or embedded interactivity, but not both. In this paper, we introduce a set of techniques we call FiberWire, which leverages a new commercially available capability to 3D print carbon fiber composite objects. These objects are light weight and mechanically strong, and our techniques demonstrate a means to embed circuitry for interactive devices within them. With FiberWire, we describe a fabrication pipeline takes advantage of laser etching and fiber printing between layers of carbon-fiber composite to form low resistance conductors, thereby enabling the fabrication of electronics directly embedded into mechanically strong objects. Utilizing the fabrication pipeline, we show a range of sensor designs, their performance characterization on these new materials and finally three fully printed example object that are both interactive and mechanically strong -- a bicycle handle bar with interactive controls, a swing and impact sensing golf club and an interactive game controller (Figure 1).