VI-SLAM for Subterranean Environments

2021 
Among the most challenging of environments in which an autonomous mobile robot might be required to serve is the subterranean environment. The complete lack of ambient light, unavailability of GPS, and geometric ambiguity make subterranean simultaneous localization and mapping (SLAM) exceptionally difficult. While there are many possible solutions to this problem, a visual-inertial framework has the potential to be fielded on a variety of robotic platforms which can operate in the spatially constrained and hazardous environments presented by the subterranean domain. In this work, we present an evaluation of visual-inertial SLAM in the subterranean environment with onboard lighting and show that it can consistently perform quite well, with less than 4% translational drift. However, this performance is dependent on including some modifications that depart from the typical formulation of VI-SLAM, as well as careful tuning of the system’s visual tracking parameters. We discuss the sometimes counter-intuitive effects of these parameters and provide insight into how they affect the system’s overall performance.
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