A Sonar-based AUV Positioning System for Underwater Environments with Low Infrastructure Density

TL;DR

This paper introduces a real-time sonar-based positioning system for autonomous underwater vehicles operating in environments with sparse infrastructure, enhancing localization accuracy in challenging underwater conditions.

Contribution

It presents a novel fusion algorithm combining two data interpretation methods within a particle filter for improved AUV localization using multibeam sonar data.

Findings

Promising results in simulated environments

Effective fusion of data interpretation methods

Potential for real-world application

Abstract

The increasing demand for underwater vehicles highlights the necessity for robust localization solutions in inspection missions. In this work, we present a novel real-time sonar-based underwater global positioning algorithm for AUVs (Autonomous Underwater Vehicles) designed for environments with a sparse distribution of human-made assets. Our approach exploits two synergistic data interpretation frontends applied to the same stream of sonar data acquired by a multibeam Forward-Looking Sonar (FSD). These observations are fused within a Particle Filter (PF) either to weigh more particles that belong to high-likelihood regions or to solve symmetric ambiguities. Preliminary experiments carried out on a simulated environment resembling a real underwater plant provided promising results. This work represents a starting point towards future developments of the method and consequent exhaustive evaluations also in real-world scenarios.