WORM
Sam Bourgault, Alejandro Aponte, Megumi Ondo, Emilie Yu, Jennifer Jacobs. 2025. WORM: Programming Collaborative Robots Through Manual Actions for Craft-Aligned Digital Fabrication, UIST 2025, Busan, Korea. doi: https://doi.org/10.1145/3746059.3747616
Collaborative robotic (cobot) arms enable digital fabrication practitioners to engage in safe and adaptable robotic interactions. Cobot machining involves similar principles to CNC operation; however, cobot fabrication workflows are more complex than CNC because they require both programming expertise and material knowledge. These requirements limit the adoption of cobots in manufacturing and craft. Prior cobot fabrication research frames the robot as a generative partner, but we seek to enable artists to precisely specify domain-specific machining operations. We contribute a novel cobot programming framework that allows artists to use manual interaction with the robot to define robotic behaviors. We identified four interaction modes to enhance human-robot collaboration in digital fabrication. We used these modes to develop the Workflow-Oriented Robotic Manufacturing (WORM 🪱) system. We informed our development through need-finding interviews with two professional ceramicists and assessed our system through a preliminary study with a professional painter, production of exemplar artifacts, and an expert evaluation with a professional ceramicist.
This work was done in collaboration with Alejandro Aponte, Megumi Ondo, Emilie Yu and Jennifer Jacobs at the Expressive Computation Lab (UCSB).
Acknowledgement: We would like to express our gratitude to the artists we interviewed and those who participated in our evaluation effort. Thank you, Camila Friedman-Gerlicz, Joey Watson, and Paul Bourgault, for your help! We also thank Elijah Frankle for his contributions to the initial prototype of the desktop interface. Lastly, we want to thank all our friends and colleagues in the Expressive Computation Lab at UCSB who read and provided feedback on our paper. This research was funded in part by the NSF CAREER Program (Award: 2441766).
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UIST2025, Busan, Republic of Korea
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