InsSo3D: Inertial Navigation System and 3D Sonar SLAM for turbid environment inspection

TL;DR

InsSo3D introduces a novel SLAM method combining 3D Sonar and INS for accurate underwater environment mapping in turbid conditions, effectively correcting odometry drift and producing detailed 3D maps.

Contribution

The paper presents a new SLAM framework that leverages 3D Sonar data and INS, with robust loop closure and pose graph optimization, for large-scale underwater mapping.

Findings

Average trajectory error below 21cm over 50 minutes

Produced 3D maps with 9cm average reconstruction error

Effective in murky water conditions

Abstract

This paper presents InsSo3D, an accurate and efficient method for large-scale 3D Simultaneous Localisation and Mapping (SLAM) using a 3D Sonar and an Inertial Navigation System (INS). Unlike traditional sonar, which produces 2D images containing range and azimuth information but lacks elevation information, 3D Sonar produces a 3D point cloud, which therefore does not suffer from elevation ambiguity. We introduce a robust and modern SLAM framework adapted to the 3D Sonar data using INS as prior, detecting loop closure and performing pose graph optimisation. We evaluated InsSo3D performance inside a test tank with access to ground truth data and in an outdoor flooded quarry. Comparisons to reference trajectories and maps obtained from an underwater motion tracking system and visual Structure From Motion (SFM) demonstrate that InsSo3D efficiently corrects odometry drift. The average trajectory error is below 21cm during a 50-minute-long mission, producing a map of 10m by 20m with a 9cm average reconstruction error, enabling safe inspection of natural or artificial underwater structures even in murky water conditions.