We present ANISMA, a software and hardware toolkit to prototype on-skin haptic devices that generate skin deformation stimuli like pressure, stretch, and motion using shape-memory alloys (SMAs). Our toolkit embeds expert knowledge that makes SMA spring actuators more accessible to human–computer interaction (HCI) researchers. Using our software tool, users can design different actuator layouts, program their spatio-temporal actuation and preview the resulting deformation behavior to verify a design at an early stage. Our toolkit allows exporting the actuator layout and 3D printing it directly on skin adhesive. To test different actuation sequences on the skin, a user can connect the SMA actuators to our customized driver board and reprogram them using our visual programming interface. We report a technical analysis, verify the perceptibility of essential ANISMA skin deformation devices with 8 participants, and evaluate ANISMA regarding its usability and supported creativity with 12 HCI researchers in a creative design task.
Designers and makers are increasingly interested in leveraging bio-based and bio-degradable 'do-it-yourself' (DIY) materials for sustainable prototyping. Their self-produced bioplastics possess compelling properties such as self-adhesion but have so far not been functionalized to create soft interactive devices, due to a lack of DIY techniques for the fabrication of functional electronic circuits and sensors. In this paper, we contribute a DIY approach for creating Interactive Bioplastics that is accessible to a wide audience, making use of easy-to-obtain bio-based raw materials and familiar tools. We present three types of conductive bioplastic materials and their formulation: sheets, pastes and foams. Our materials enable additive and subtractive fabrication of soft circuits and sensors. Furthermore, we demonstrate how these materials can substitute conventional prototyping materials, be combined with off-the-shelf electronics, and be fed into a sustainable material `life-cycle' including disassembly, re-use, and re-melting of materials. A formal characterization of our conductors highlights that they are even on-par with commercially available carbon-based conductive pastes.
Bridges are unique structures appeared in fused deposition modeling (FDM) that make rigid prints flexible but not fully explored. This paper presents X-Bridges, an end-to-end workflow that allows novice users to design tunable bridges that can enrich 3D printed objects' deformable and physical properties. Specifically, we firstly provide a series of deformation primitives (e.g. bend, twist, coil, compress and stretch) with three versions of stiffness (loose, elastic, stable) based on parametrized bridging experiments. Embedding the printing parameters, a design tool is developed to modify the imported 3D model, evaluate optimized printing parameters for bridges, preview shape-changing process, and generate the G-code file for 3D printing. Finally, we demonstrate the design space of X-Bridges through a set of applications that enable foldable, resilient, and interactive shape-changing objects.
Foundation paper piecing is a widely used quilt-making technique in which fabric pieces are sewn onto a paper guide to facilitate construction. But, designing paper pieceable quilt patterns is challenging because the sewing process imposes constraints on both the geometry and sewing order of the fabric pieces. Based on a formative study with expert quilt designers, we develop a novel sketch-based tool for designing such quilt patterns. Our tool lets designers sketch a partial design as a set of edges, which may intersect but do not have to form closed polygons, and our tool automatically completes it into a fully paper pieceable pattern. We contribute a new sketch-completion algorithm that extends the input sketched edges into a planar mesh composed of closed polygonal faces representing fabric pieces, determines a paper pieceable sewing order for the faces, and breaks complicated sketches into independently paper pieceable sections when necessary. A partial input design often admits multiple visually different completions. Thus, our tool lets designers specify completion heuristics, which are based on current quilt design practices, to control the appearance of the completed quilt. Initial user evaluations with novice and expert quilt designers suggest that our tool fits within current design workflows and greatly facilitates designing foundation paper pieceable quilts by allowing users to focus on the visual design rather than tedious constraint checks.
Recent advances in smart materials have enabled displays to move beyond planar surfaces into the fabric of everyday life. We propose reflective light-diffuser modules for non-emissive flexible display systems. Our system leverages reflective-backed polymer-dispersed liquid crystal (PDLC), an electroactive material commonly used in smart window applications. This low-power non-emissive material can be cut to any shape, and dynamically diffuses light. We present the design & fabrication of two exemplar artifacts, a canvas and a handbag, that use the reflective light-diffuser modules. We also describe our content authoring pipeline and interaction modalities. We hope this work inspires future designers of flexible displays.
Garments with the ability to provide kinesthetic force-feedback on-demand can augment human capabilities in a non-obtrusive way, enabling numerous applications in VR haptics, motion assistance, and robotic control. However, designing such garments is a complex, and often manual task, particularly when the goal is to resist multiple motions with a single design. In this work, we propose a computational pipeline for designing connecting structures between active components---one of the central challenges in this context. We focus on electrostatic (ES) clutches that are compliant in their passive state while strongly resisting elongation when activated. Our method automatically computes optimized connecting structures that efficiently resist a range of pre-defined body motions on demand. We propose a novel dual-objective optimization approach to simultaneously maximize the resistance to motion when clutches are active, while minimizing resistance when inactive. We demonstrate our method on a set of problems involving different body sites and a range of motions. We further fabricate and evaluate a subset of our automatically created designs against manually created baselines using mechanical testing and in a VR pointing study.