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

arXiv: https://arxiv.org/abs/2409.11578 · HTML: https://mlsanity.com/paper/2409.11578/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Sep 2024.

## Built on by (most cited first, 3 of 3)

- [Image-Based Relocalization and Alignment for Long-Term Monitoring of Dynamic Underwater Environments](https://mlsanity.com/paper/2503.04096/) (2025)
- [DREAM: Domain-aware Reasoning for Efficient Autonomous Underwater Monitoring](https://mlsanity.com/paper/2509.13666/) (2025)
- [Benchmarking Online Object Trackers for Underwater Robot Position Locking Applications](https://mlsanity.com/paper/2502.16569/) (2025)

## Abstract (arXiv)

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.