SplatOverflow: Asynchronous Hardware Troubleshooting
Amritansh Kwatra, Tobias M. Weinberg, Ilan Mandel, Ritik Batra, Peter He, François Guimbretière, Thijs Roumen
Abstract
As tools for designing and manufacturing hardware become more accessible, smaller producers can develop and distribute novel hardware. However, processes for supporting end-user hardware troubleshooting or routine maintenance aren’t well defined. As a result, providing technical support for hardware remains ad-hoc and challenging to scale. Inspired by patterns that helped scale software troubleshooting, we propose a workflow for asynchronous hardware troubleshooting: SplatOverflow. SplatOverflow creates a novel boundary object, the SplatOverflow scene, that users reference to communicate about hardware. A scene comprises a 3D Gaussian Splat of the user’s hardware registered onto the hardware’s CAD model. The splat captures the current state of the hardware, and the registered CAD model acts as a referential anchor for troubleshooting instructions. With SplatOverflow, remote maintainers can directly address issues and author instructions in the user’s workspace. Workflows containing multiple instructions can easily be shared between users and recontextualized in new environments. In this paper, we describe the design of SplatOverflow, the workflows it enables, and its utility to different kinds of users. We also validate that non-experts can use SplatOverflow to troubleshoot common problems with a 3D printer in a usability study. Project Page: https://amritkwatra.com/research/splatoverflow.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 1798215f-2943-4301-b4f2-a88a0e2a2f4cCited by top-tier papers1
Ask how each one uses itBuilds on13
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 5,687 citations
- Instant neural graphics primitives with a multiresolution hash encodingThomas Müller, Alex Evans, Christoph Schied, Alexander KellerSIGGRAPH 2022 · 4,089 citations
- DUSt3R: Geometric 3D Vision Made EasyShuzhe Wang, Vincent Leroy, Yohann Cabon, Boris Chidlovskii et al.CVPR 2024 · 302 citations
- TransceiVR: Bridging Asymmetrical Communication Between VR Users and External CollaboratorsBalasaravanan Thoravi Kumaravel, Cuong Nguyen, Stephen DiVerdi, Bjoern HartmannUIST 2020 · 75 citations
- InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging ToolsMustafa Doga Dogan, Ahmad Taka, Michael Lu, Yunyi Zhu et al.CHI 2022 · 59 citations
Related papers
- From Copy/Paste to Copying Pastes: Supporting Replication in an Online Digital Fabrication CommunityBlair Subbaraman, Nadya PeekCHI 2026 · 1 citation
- Formalizing Linear Motion G-Code for Invariant Checking and Differential Testing of Fabrication ToolsYumeng He, Chandrakana Nandi, Sreepathi PaiOOPSLA 2025 · 2 citations
- Painting with 3D Gaussian Splat BrushesKarran Pandey, Anita Hu, Clement Fuji Tsang, Or Perel et al.SIGGRAPH 2025 · 5 citations
- OScH in the Wild: Dissemination of Open Science Hardware and Implications for HCIPiyum Fernando, Stacey KuznetsovCHI 2020 · 6 citations
- GaussianNexus: Room-Scale Real-Time AR/VR Telepresence with Gaussian SplattingXincheng Huang, Dieter Frehlich, Ziyi Xia, Peyman Gholami et al.UIST 2025 · 5 citations
