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Computational Design and Single-Wire Sensing of 3D Printed Objects with Integrated Capacitive Touchpoints
CU Boulder, CO 80309 USA; Univ Arizona, AZ 85721 USA.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Univ Arizona, AZ USA.ORCID iD: 0000-0002-6382-2752
Univ North Carolina Chapel Hill, NC USA.
CU Boulder, CO 80309 USA.
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2025 (English)In: 10TH ACM SYMPOSIUM ON COMPUTATIONAL FABRICATION, SCF 2025, Association for Computing Machinery (ACM) , 2025, article id 8Conference paper, Published paper (Refereed)
Abstract [en]

Producing interactive 3D printed objects currently requires laborious 3D design and post-instrumentation with off-the-shelf electronics. Multi-material 3D printing using conductive PLA presents opportunities to mitigate these challenges. We present a computational design pipeline that embeds multiple capacitive touchpoints into any 3D model that has a closed mesh without self-intersection. With our pipeline, users define touchpoints on the 3D object's surface to indicate interactive regions. Our pipeline then automatically generates a conductive path to connect the touch regions. This path is optimized to output unique resistor-capacitor delays when each region is touched, resulting in all regions being able to be sensed through a double-wire or single-wire connection. We illustrate our approach's utility with five computational and sensing performance evaluations (achieving 93.35% mean accuracy for single-wire) and six application examples. Our sensing technique supports existing uses (e.g., prototyping) and highlights the growing promise to produce interactive devices entirely with 3D printing.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2025. article id 8
Keywords [en]
computational design; 3D printing; sensors; capacitive sensing; input devices
National Category
Vehicle and Aerospace Engineering
Identifiers
URN: urn:nbn:se:liu:diva-223107DOI: 10.1145/3745778.3766650ISI: 001723278600008Scopus ID: 2-s2.0-105023713770ISBN: 9798400720345 (print)OAI: oai:DiVA.org:liu-223107DiVA, id: diva2:2054679
Conference
10th Symposium on Computational Fabrication-SCF, Cambridge, MA, nov 20-21, 2025
Note

Funding Agencies|U.S. National Science Foundation [IIS-2040489, IIS-2320920, STEM+C 1933915]; Knut and Alice Wallenberg Foundation [KAW 2019.0024]; CU Boulder Engineering Education and AI-Augmented Learning Interdisciplinary Research Theme Seed Grant; National Renewable Energy Laboratory (NREL) under Alliance Partner University Program (APUP) [UGA-0-41026-191]; Linkoping University

Available from: 2026-04-21 Created: 2026-04-21 Last updated: 2026-06-17

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CiteExportLink to record
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Citation style
  • apa
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Output format
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