A bathymetric mapping and SLAM dataset with high-precision ground truth for marine robotics
Abstract
In recent years, sonar systems for surface and underwater vehicles have increased in resolution and become significantly less expensive. As such, these systems are viable at a wide range of price points and are appropriate for a broad set of applications on surface and underwater vehicles. However, to take full advantage of these high-resolution sensors for seafloor mapping tasks an adequate navigation solution is also required. In GPS-denied environments this usually necessitates a simultaneous localization and mapping (SLAM) technique to maintain good accuracy with minimal error accumulation. Acoustic positioning systems such as ultra short baseline (USBL) and long baseline (LBL) are sometimes deployed to provide additional bounds on the navigation solution, but the positional uncertainty of these systems is often much greater than the resolution of modern multibeam or interferometric side scan sonars. As such, subsurface vehicles often lack the means to adequately ground-truth navigation solutions and the resulting bathymetic maps. In this article, we present a dataset with four separate surveys designed to test bathymetric SLAM algorithms using two modern sonars, typical underwater vehicle navigation sensors, and high-precision (2 cm horizontal, 10 cm vertical) real-time kinematic (RTK) GPS ground truth. In addition, these data can be used to refine and improve other aspects of multibeam sonar mapping such as ray-tracing, gridding techniques, and time-varying attitude corrections.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 11, 2021
- Source ID
- 10.1177/02783649211044749
Entities
People
- Christopher Roman
- David Casagrande
- Kristopher Krasnosky
Organizations
- Office of Naval Research
- University of Rhode Island