Hyunyoung Kim

Programmable folding of elastic sheets typically relies on predefined flexible creases or active materials‐enabled hinges, which lack intrinsic bistability and limit reprogrammability within a single structure. Here, we present a dimple‐encoded origami platform that converts bistable dimple snapping into dimple‐encoded hinge bands with prescribed folding angles in a continuous sheet. This interaction‐enabled mechanism enables the design of distributed hinge networks through the arrangement and selective inversion of dimples. We establish folding‐angle design charts that can be directly used to select local dimple arrangements for a target folding angle, forming a practical hinge‐angle library without altering the underlying unit geometry. Using this approach, a single dimpled sheet can be reprogrammed to realize multiple distinct configurations, such as triangle, square, and pentagon shapes. We further extend the method to flat‐to‐3D morphing of polyhedral origami and validate the results through experiments and finite element simulations. As demonstrations, we realize self‐supporting cubic shells with enhanced impact resistance and partially deployable cube configurations that remain stable upon opening, highlighting their potential for protective enclosures and deployable architectural structures. The proposed strategy provides a fabrication‐friendly route to reprogrammable shape‐morphing and adaptive mechanical systems.

Digital fabrication research within HCI has generated powerful new techniques, tools, and systems, enabling lay users to create novel application devices. Yet many of these contributions remain confined to academic publications or lab prototypes. This workshop asks how fabrication research can make an impact beyond the paper. We will examine motivations for dissemination, strategies employed, and lessons learned from both successes and failures. Through two invited keynotes and interactive ideation activities, we will chart pathways by which fabrication research reaches the real world. The outcome will be a set of shared notes and insights, documenting practices that help researchers extend the reach of their work.

Conception centrée sur l'utilisateur des commandes de changement de forme: Les interfaces à forme variable apportent de la flexibilité aux interfaces physiques en transformant les dispositifs de calcul en n'importe quelle forme ou matérialité. Les interfaces à forme variable seront de plus en plus accessibles aux utilisateurs finaux à l'avenir, de même que le développement technologique. Cependant, nous en savons peu sur les critères de conception des interfaces de changement de forme pour les utilisateurs finaux, en particulier pour ceux qui utilisent des interfaces de contrôle des paramètres. Les interfaces de contrôle des paramètres sont souvent conçues à partir d'exemples existants tels que les cadrans et les curseurs, et il y a eu peu d'études pour comprendre les besoins des utilisateurs derrière leur utilisation. D'autre part, il existe des taxonomies d'interface qui permettent aux concepteurs d'explorer systématiquement les idées de conception d'interfaces qui changent de forme, mais elles ne sont guère évaluées. Dans cet exposé, je discute de mon travail de doctorat sur les deux domaines de l'ICH : les interfaces de contrôle des paramètres et les interfaces de changement de forme. J'effectue d'abord une étude formative pour suggérer les exigences de conception des interfaces de contrôle des paramètres en fonction de la pratique actuelle des utilisateurs. Deuxièmement, j'affine une taxonomie d'interface qui change de forme en évaluant sa puissance descriptive en utilisant des objets reconfigurables de tous les jours. Enfin, j'examine l'intersection des interfaces de contrôle des paramètres et des interfaces de changement de forme. Je développe deux études de cas : KnobSlider, une interface de changement de forme qui peut être un bouton ou un curseur, et ExpanDial, un contrôle de rotation qui étend la modalité d'interaction par des changements de forme.

We introduce Rhapso, a 3D printing system designed to embed a diverse range of continuous fiber materials within 3D objects during the printing process. This approach enables integrating properties like tensile strength, force storage and transmission, or aesthetic and tactile characteristics, directly into low-cost thermoplastic 3D prints. These functional objects can have intricate actuation, self-assembly, and sensing capabilities with little to no manual intervention. To achieve this, we modify a low-cost Fused Filament Fabrication (FFF) 3D printer, adding a stepper motor-controlled fiber spool mechanism on a gear ring above the print bed. In addition to hardware, we provide parsing software for precise fiber placement, which generates G-code for printer operation. To illustrate the versatility of our system, we present applications that showcase its extensive design potential. Additionally, we offer comprehensive documentation and open designs, empowering others to replicate our system and explore its possibilities.

Designing robotic hands has been an active area of research and innovation in the last decade. However, little is known about how people perceive robot hands and react to being touched by them. To inform hand design for social robots, we created a database of 73 robot hands and ran two user studies. In the first study, 160 online users rated the hands in our database. Variations in user ratings mostly centered on the perceived Comfortableness , Interestingness , and Industrialness of the hands. In a second lab-based study, users evaluated seven physical hands and had similar ratings to results from the online study. Furthermore, we did not find a significant difference in user ratings before and after the users were touched by the hands. We provide regression models that can predict user ratings from the hand features (e.g., number of fingers) and an online interface for using our robot hand database and predictive models.

A wide variety of robotic hands have been designed to date. Yet, we do not know how users perceive these hands and feel about interacting with them. To inform hand design for social robots, we compiled a dataset of 73 robot hands and ran an online study, in which 160 users rated their impressions of the hands using 17 rating scales. Next, we developed 17 regression models that can predict user ratings (e.g., humanlike) from the design features of the hands (e.g., number of fingers). The models have less than a 10-point error in predicting the user ratings on a 0-100 scale. The shape of the fingertips, color scheme, and size of the hands influence the user ratings the most. We present simple guidelines to improve user impression of robot hands and outline remaining questions for future work.