The Full-scale Assembly Simulation Testbed (FAST) Dataset
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Abstract (arXiv)
In recent years, numerous researchers have begun investigating how virtual reality (VR) tracking and interaction data can be used for a variety of machine learning purposes, including user identification, predicting cybersickness, and estimating learning gains. One constraint for this research area is the dearth of open datasets. In this paper, we present a new open dataset captured with our VR-based Full-scale Assembly Simulation Testbed (FAST). This dataset consists of data collected from 108 participants (50 females, 56 males, 2 non-binary) learning how to assemble two distinct full-scale structures in VR. In addition to explaining how the dataset was collected and describing the data included, we discuss how the dataset may be used by future researchers.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 3 of its 30 references that are in the map. First posted on arXiv 13 Mar 2024.
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Citing papers per year: 2025: 1.
1 paper.