We present FibeRobo, a thermally-actuated liquid crystal elastomer (LCE) fiber that can be embedded or structured into textiles and enable silent and responsive interactions with shape-changing, fiber-based interfaces. Three definitive properties distinguish FibeRobo from other actuating fibers explored in HCI. First, they exhibit rapid thermal self-reversing actuation with large displacements (~40%) without twisting. Second, we present a reproducible UV fiber drawing setup that produces hundreds of meters of fiber with a sub-millimeter diameter. Third, FibeRobo is fully compatible with existing textile manufacturing machinery such as weaving looms, embroidery, and industrial knitting machines. This paper contributes to developing temperature-responsive LCE fibers, a facile and scalable fabrication pipeline with optional heating element integration for digital control, mechanical characterization, and the establishment of higher hierarchical textile structures and design space. Finally, we introduce a set of demonstrations that illustrate the design space FibeRobo enables.
https://doi.org/10.1145/3586183.3606732
As electronic textiles have become more advanced in sensing, ac- tuating, and manufacturing, incorporating smartness into fabrics has become of special interest to ubiquitous computing and interac- tion researchers and designers. However, innovating smart textile interfaces for numerous input and output modalities usually re- quires expert-level knowledge of specific materials, fabrication, and protocols. This paper presents EmTex, a construction kit based on embroidered textiles, patterned with dedicated sensing, actuating, and connecting components to facilitate the design and prototyp- ing of smart textile interfaces. With machine embroidery, EmTex is compatible with a wide range of threads and underlay fabrics, proficient in various stitches to control the electric parameters, and capable of integrating versatile and reliable interaction functionali- ties with aesthetic patterns and precise designs. EmTex consists of 28 textile-based sensors, actuators, connectors, and displays, pre- sented with standardized visual and tactile effects. Along with a visual programming tool, EmTex enables the prototyping of every- day textile interfaces for diverse life-living scenarios, that embody their touch input, and visual and haptic output properties. With EmTex, we conducted a workshop and invited 25 designers and makers to create freeform textile interfaces. Our findings revealed that EmTex helped the participants explore novel interaction oppor- tunities with various smart textile prototypes. We also identified challenges EmTex shall face for practical use in promoting the design innovation of smart textiles.
https://doi.org/10.1145/3586183.3606815
Knitting machines can fabricate complex fabric structures using robust industrial fabrication machines. However, machine knitting's full capabilities are only available through low-level programming languages that operate on individual machine operations. We present KnitScript, a domain-specific machine knitting scripting language that supports computationally driven knitting designs. KnitScript provides a comprehensive virtual model of knitting machines, giving access to machine-level capabilities as they are needed while automating a variety of tedious and error-prone details. Programmers can extend KnitScript with Python programs to create more complex programs and user interfaces. We evaluate the expressivity of KnitScript through a user study where nine machine knitters used KnitScript code to modify knitting patterns. We demonstrate the capabilities of KnitScript through three demonstrations where we create: a program for generating knitted figures of randomized trees, a parameterized hat template that can be modified with accessibility features, and a pattern for a parametric mixed-material lampshade. KnitScript advances the state of machine-knitting research by providing a platform to develop and share complex knitting algorithms, design tools, and patterns.
https://doi.org/10.1145/3586183.3606789
With recent advances in Generative AI, it is becoming easier to automatically manipulate 3D models. However, current methods tend to apply edits to models globally, which risks compromising the intended functionality of the 3D model when fabricated in the physical world. For example, modifying functional segments in 3D models, such as the base of a vase, could break the original functionality of the model, thus causing the vase to fall over. We introduce a method for automatically segmenting 3D models into functional and aesthetic elements. This method allows users to selectively modify aesthetic segments of 3D models, without affecting the functional segments. To develop this method we first create a taxonomy of functionality in 3D models by qualitatively analyzing 1000 models sourced from a popular 3D printing repository, Thingiverse. With this taxonomy, we develop a semi-automatic classification method to decompose 3D models into functional and aesthetic elements. We propose a system called Style2Fab that allows users to selectively stylize 3D models without compromising their functionality. We evaluate the effectiveness of our classification method compared to human-annotated data, and demonstrate the utility of Style2Fab with a user study to show that functionality-aware segmentation helps preserve model functionality.
https://doi.org/10.1145/3586183.3606723
New digital fabrication workflows require both software development and digital/physical material exploration. To support digital fabrication workflow development, we contribute infrastructure that prioritizes extensibility and iteration. Dynamic Toolchains are dataflow programs with event-driven feedback between interactive, stateful modules. We contribute a browser-based dataflow environment for running Dynamic Toolchains, a library of fabrication-oriented front- and back-end modules for design and machine control, and a development framework for building custom modules. Furthermore, we show how our infrastructure supports unconventional fabrication workflows with demonstrations that include interactive watercolor painting, map plotting, machine knitting, audio embroidery, textured 3d printing, and computer-controlled milling. These demonstrations show how our infrastructure supports multiple kinds of engagement including reuse, remix, and extension. Finally, we discuss how this work contributes to broader conversations in HCI on creativity across the digital/physical divide.
https://doi.org/10.1145/3586183.3606802
Surface ornamentation is a rich component of ceramic manufacture wherein craftspeople use multiple methods to create intricate patterns on vessels. Computational fabrication can extend manual ceramic ornamentation through procedural pattern generation and automated fabrication; however, to be effective in traditional ceramics, computational fabrication systems must remain compatible with existing processes and materials. We contribute an interactive design workflow, CeramWrap, in which craftspeople can procedurally design and fabricate decorative patterned stencils tailored to radially symmetrical vessels. Our approach extends manual techniques through a workflow where craftspeople design and edit repetitive motifs directly on a 3D digital model of a vessel and then interactively adjust the unrolling of the 3D design to a 2D format suitable for digitally fabricating stencils and templates. Through a series of example artifacts, we demonstrate how our workflow generalizes across multiple vessel geometries, supports manual and digital clay fabrication, and is adaptable to different surface ornamentation methods.
https://doi.org/10.1145/3586183.3606726