3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization

TL;DR

This paper introduces a novel 3D water quality mapping system using an underwater robot with invariant extended Kalman filtering, enhancing accuracy and depth coverage in aquaculture environments.

Contribution

It presents an innovative underwater robot-based approach combining GPS and water sensors with invariant extended Kalman filtering for precise 3D water quality mapping.

Findings

Enhanced accuracy in water quality measurements

Effective depth variability coverage

Successful deployment in Chesapeake Bay oyster farm

Abstract

Water quality mapping for critical parameters such as temperature, salinity, and turbidity is crucial for assessing an aquaculture farm's health and yield capacity. Traditional approaches involve using boats or human divers, which are time-constrained and lack depth variability. This work presents an innovative approach to 3D water quality mapping in shallow water environments using a BlueROV2 equipped with GPS and a water quality sensor. This system allows for accurate location correction by resurfacing when errors occur. This study is being conducted at an oyster farm in the Chesapeake Bay, USA, providing a more comprehensive and precise water quality analysis in aquaculture settings.