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

2024-09-17

arXiv.org

AI Summary

To address insufficient spatiotemporal coverage and limited depth penetration of manual/boat-based sampling in three-dimensional (3D) water quality monitoring of shallow aquaculture zones, this paper proposes a high-precision autonomous mapping method leveraging the BlueROV2 underwater robot. We innovatively introduce the Invariant Extended Kalman Filter (IEKF) for underwater water-quality mapping, tightly fusing multi-sensor data from GPS, CTD (conductivity–temperature–depth), and IMU. A periodic autonomous surfacing and relocalization mechanism is further designed to enhance pose estimation robustness. Field validation at an oyster farm in Chesapeake Bay demonstrates sub-0.5 m underwater positioning accuracy and achieves a 3D water-quality field resolution of 0.5 m × 0.5 m × 0.2 m for temperature, salinity, and turbidity. Sampling efficiency improves by over fivefold compared to conventional manual methods. This framework establishes a scalable, real-time 3D water-quality sensing paradigm for nearshore aquaculture health assessment and yield prediction.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: 3D Computer Vision

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

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.

Problem

• 3D water quality mapping
• Underwater robot localization
• Aquaculture farm health assessment

Innovation

• 3D water quality mapping
• Invariant Extended Kalman Filtering
• Underwater robot localization