Y-AR: A Mixed Reality CAD Tool for 3D Wire Bending
October 31, 2024 Β· Declared Dead Β· π Proceedings of the ACM Symposium on Computational Fabrication
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Shuo Feng, Bo Liu, Yifan, Shan, Roy Zunder, Wei-Che Lin, Tri Dinh, Harald Haraldsson, Ofer Berman, Thijs Roumen
arXiv ID
2410.23540
Category
cs.HC: Human-Computer Interaction
Citations
3
Venue
Proceedings of the ACM Symposium on Computational Fabrication
Last Checked
4 months ago
Abstract
Wire bending is a technique used in manufacturing to mass-produce items such as clips, mounts, and braces. Recent advances in programmable wire bending have made this process increasingly accessible for custom fabrication. However, CNC wire benders are controlled using Computer Aided Manufacturing (CAM) software, without design tools, making custom designs challenging to produce. We present Y-AR, a Computer Aided Design (CAD) interface for 3D wire bending. Y-AR uses mixed reality to let designers create clips, mounts, and braces to physically connect objects to their surrounding environment. The interface incorporates springs as design primitives which (1) apply forces to hold objects, and (2) counter-act dimensional inaccuracies inherently caused by mid-air modeling and measurement errors in AR. Springs are a natural design element when working with metal wire-bending given its specific material properties. We demonstrate workflows to design and fabricate a range of mechanisms in Y-AR as well as structures made using free-hand design tools. We found that combining gesture-based interaction with fabrication-aware design principles allowed novice users to create functional wire connectors, even when using imprecise XR-based input. In our usability evaluation, all 12 participants successfully designed and fabricated a functional bottle holder using Y-AR.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted