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

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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.

Shida Xu, Kaicheng Zhang, Sen Wang• 2025

Related benchmarks

TaskDatasetResultRank
Absolute Translation Error EstimationTank Structure Medium
RMSE0.18
10
Absolute Translation Error EstimationTank Structure Easy
RMSE0.07
6
Absolute Translation Error EstimationTank HalfTank Easy
RMSE0.28
6
Absolute Translation Error EstimationTank WholeTank Medium
RMSE0.52
6
Absolute Translation Error EstimationTank WholeTank Hard
RMSE0.22
5
Absolute Translation Error EstimationTank Structure Hard
RMSE0.5
5
Absolute Translation Error EstimationTank HalfTank Hard
RMSE0.36
5
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