Uniquely Shaped Spaces: Object-Driven Algorithmic Shelf Design and Fabrication

要旨

Most shelving relies on rectangular compartments that ignore the contours of the objects they hold. We present Uniquely Shaped Spaces, an object-driven algorithmic tool for custom shelving generation. The workflow arranges users' object silhouettes with simulated annealing, grows walls via cellular automata to carve fitted voids, and outputs fabrication files with joinery for laser cutting. We designed the system so that objects, our algorithm, and users share authorship, and studied how this configuration played out with five participants as they designed shelves in guided workshops and then lived with the fabricated pieces. Our findings show how participants navigated object geometry, algorithmic search, and fabrication limits by curating, tweaking, and appropriating algorithmic proposals, and how the resulting shelves supported reflection and storytelling. These results point toward object-driven fabrication systems that foreground objects as generative constraints and explicitly support negotiation within constraint-driven workflows.

著者
Deanna Gelosi
University of Colorado, Boulder, Boulder, Colorado, United States
Michael L.. Rivera
University of Colorado Boulder, Boulder, Colorado, United States
Laura Devendorf
University of Colorado Boulder, Boulder, Colorado, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Tangible Interfaces for Electronics, PCBs, and Physical Computing

P1 - Room 124
7 件の発表
2026-04-15 20:15:00
2026-04-15 21:45:00