Opti-Acoustic Scene Reconstruction in Highly Turbid Underwater Environments

TL;DR

This paper introduces a real-time opti-acoustic scene reconstruction method for underwater robots that combines sonar and camera data to improve accuracy in turbid waters, validated through experiments and field tests.

Contribution

It presents a novel approach that fuses sonar and monocular vision data for robust underwater scene reconstruction in turbid environments.

Findings

Effective in highly turbid water conditions

Outperforms existing vision and sonar-based methods

Validated through marina environment tests

Abstract

Scene reconstruction is an essential capability for underwater robots navigating in close proximity to structures. Monocular vision-based reconstruction methods are unreliable in turbid waters and lack depth scale information. Sonars are robust to turbid water and non-uniform lighting conditions, however, they have low resolution and elevation ambiguity. This work proposes a real-time opti-acoustic scene reconstruction method that is specially optimized to work in turbid water. Our strategy avoids having to identify point features in visual data and instead identifies regions of interest in the data. We then match relevant regions in the image to corresponding sonar data. A reconstruction is obtained by leveraging range data from the sonar and elevation data from the camera image. Experimental comparisons against other vision-based and sonar-based approaches at varying turbidity levels, and field tests conducted in marina environments, validate the effectiveness of the proposed approach. We have made our code open-source to facilitate reproducibility and encourage community engagement.