ROCVMar 14, 2025

AQUA-SLAM: Tightly-Coupled Underwater Acoustic-Visual-Inertial SLAM with Sensor Calibration

arXiv:2503.11420v130 citationsh-index: 6Has CodeIEEE Trans robot
Originality Incremental advance
AI Analysis

This addresses localization and mapping problems for underwater robotics in challenging environments, representing a domain-specific incremental improvement.

The paper tackles the challenges of underwater visual SLAM by introducing AQUA-SLAM, a tightly-coupled acoustic-visual-inertial SLAM system with sensor calibration, which outperforms state-of-the-art methods in localization accuracy and robustness in tank and offshore tests.

Underwater environments pose significant challenges for visual Simultaneous Localization and Mapping (SLAM) systems due to limited visibility, inadequate illumination, and sporadic loss of structural features in images. Addressing these challenges, this paper introduces a novel, tightly-coupled Acoustic-Visual-Inertial SLAM approach, termed AQUA-SLAM, to fuse a Doppler Velocity Log (DVL), a stereo camera, and an Inertial Measurement Unit (IMU) within a graph optimization framework. Moreover, we propose an efficient sensor calibration technique, encompassing multi-sensor extrinsic calibration (among the DVL, camera and IMU) and DVL transducer misalignment calibration, with a fast linear approximation procedure for real-time online execution. The proposed methods are extensively evaluated in a tank environment with ground truth, and validated for offshore applications in the North Sea. The results demonstrate that our method surpasses current state-of-the-art underwater and visual-inertial SLAM systems in terms of localization accuracy and robustness. The proposed system will be made open-source for the community.

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