An Underwater, Fault-Tolerant, Laser-Aided Robotic Multi-Modal Dense SLAM System for Continuous Underwater In-Situ Observation

TL;DR

Water-DSLAM addresses the persistent challenge of achieving uninterrupted, dense underwater SLAM in texture-sparse and degraded environments. It fuses data from DP-INS, Water-UBSL, and Water-Stereo via a fault-tolerant triple-subsystem front-end and a dynamic multi-modal factor-graph back-end, enabling continuous in-situ observation even under partial sensor dropouts. The Water-Scanner hardware platform with UBSL enables high-precision 3D perception, while extensive experiments across pools, dark underwater scenes, sinkholes, and rivers demonstrate superior robustness (trajectory RMSE of 0.039 m and 100% continuity) and mapping density (up to 6922.4 points/m^3 in 750 m^3). The approach advances underwater autonomous observation by delivering reliable, dense maps in challenging real-world environments and paves the way for practical underwater exploration and inspection tasks.

Abstract

Existing underwater SLAM systems are difficult to work effectively in texture-sparse and geometrically degraded underwater environments, resulting in intermittent tracking and sparse mapping. Therefore, we present Water-DSLAM, a novel laser-aided multi-sensor fusion system that can achieve uninterrupted, fault-tolerant dense SLAM capable of continuous in-situ observation in diverse complex underwater scenarios through three key innovations: Firstly, we develop Water-Scanner, a multi-sensor fusion robotic platform featuring a self-designed Underwater Binocular Structured Light (UBSL) module that enables high-precision 3D perception. Secondly, we propose a fault-tolerant triple-subsystem architecture combining: 1) DP-INS (DVL- and Pressure-aided Inertial Navigation System): fusing inertial measurement unit, doppler velocity log, and pressure sensor based Error-State Kalman Filter (ESKF) to provide high-frequency absolute odometry 2) Water-UBSL: a novel Iterated ESKF (IESKF)-based tight coupling between UBSL and DP-INS to mitigate UBSL's degeneration issues 3) Water-Stereo: a fusion of DP-INS and stereo camera for accurate initialization and tracking. Thirdly, we introduce a multi-modal factor graph back-end that dynamically fuses heterogeneous sensor data. The proposed multi-sensor factor graph maintenance strategy efficiently addresses issues caused by asynchronous sensor frequencies and partial data loss. Experimental results demonstrate Water-DSLAM achieves superior robustness (0.039 m trajectory RMSE and 100\% continuity ratio during partial sensor dropout) and dense mapping (6922.4 points/m^3 in 750 m^3 water volume, approximately 10 times denser than existing methods) in various challenging environments, including pools, dark underwater scenes, 16-meter-deep sinkholes, and field rivers. Our project is available at https://water-scanner.github.io/.

Figures (18)

• Figure 1: Mechatronic design, prototype, sensors and test scenarios of underwater multi-sensor robotic system, named Water-Scanner. Note: The picture in the background shows Water-Scanner's test site at Changhewan, a field river in Beijing, China.
• Figure 2: The proposed underwater, fault-tolerant, laser-aided robotic multi-modal dense SLAM framework for continuous underwater in-situ observation, named Water-DSLAM. It mainly consists of three parallel subsystems and a multi-modal factor graph back-end to achieve fault tolerance and continuous operation.
• Figure 3: The frequency of sensors in DP-INS Subsystem.
• Figure 4: The designed schematic of Water-UBSL Subsystem.
• Figure 5: The designed schematic of Water-Stereo Subsystem.