The Full-scale Assembly Simulation Testbed (FAST) Dataset

March 13, 2024 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Alec G. Moore, Tiffany D. Do, Nayan N. Chawla, Antonia Jimenez Iriarte, Ryan P. McMahan arXiv ID 2403.08969 Category cs.HC: Human-Computer Interaction Cross-listed cs.LG Citations 2 Venue arXiv.org Last Checked 4 months ago
Abstract
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.
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