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

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 article 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 the multisensor extrinsic calibration (among the DVL, camera, and IMU) and the 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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Publication Details

Journal
IEEE Transactions on Robotics
Published
2025-01-01
DOI
https://doi.org/10.1109/tro.2025.3554396
Citations
15
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
17.18
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article

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

Shida Xu, Kaicheng Zhang, Sen Wang
15 citations
IEEE Transactions on Robotics
Underwater Vehicles and Communication Systems
17.18
article

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

Shida Xu, Kaicheng Zhang, Sen Wang
article en
15 citations

Abstract

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 article 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 the multisensor extrinsic calibration (among the DVL, camera, and IMU) and the 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.

IEEE Transactions on RoboticsVol. 41
Imperial College London (GB)
Affordable and clean energy
Openalex Percentile: Top 1%
Underwater Vehicles and Communication Systems
17.18
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