Feature Geometry for Stereo Sidescan and Forward-looking Sonar

TL;DR

This paper introduces a geometry-based method for projecting features between forward-looking and sidescan sonar images, inspired by stereo camera epipolar geometry, to improve feature correspondence in marine robotics.

Contribution

It proposes a novel acoustic geometry model for cross-modal stereo sonar data fusion, leveraging relative pose to enhance feature projection accuracy.

Findings

Simulated results identify effective stereo configurations.

The method improves feature correspondence between sonar types.

Analysis of feature location and pose impacts projection accuracy.

Abstract

In this paper, we address stereo acoustic data fusion for marine robotics and propose a geometry-based method for projecting observed features from one sonar to another for a cross-modal stereo sonar setup that consists of both a forward-looking and a sidescan sonar. Our acoustic geometry for sidescan and forward-looking sonar is inspired by the epipolar geometry for stereo cameras, and we leverage relative pose information to project where an observed feature in one sonar image will be found in the image of another sonar. Additionally, we analyze how both the feature location relative to the sonar and the relative pose between the two sonars impact the projection. From simulated results, we identify desirable stereo configurations for applications in field robotics like feature correspondence and recovery of the 3D information of the feature.