The Full-scale Assembly Simulation Testbed (FAST) Dataset
Alec G. Moore Tiffany D. Do Nayan N. Chawla Antonia Jimenez Iriarte Ryan P. McMahan
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.