Underwater Dense Mapping with the First Compact 3D Sonar

2025-10-21

AI Summary

Underwater electromagnetic wave propagation suffers severe attenuation, while conventional acoustic ranging provides only ambiguous 2D measurements, hindering high-precision 3D state estimation. This paper presents the first systematic investigation of compact 3D sonar for underwater SLAM and dense mapping. We propose a robust extrinsic calibration method for sonar–camera fusion and quantitatively analyze material-dependent acoustic responses. Furthermore, we design a multi-sensor fusion SLAM framework tailored to complex underwater environments (e.g., caves), jointly leveraging geometric constraints and acoustic characteristics. Experiments demonstrate centimeter-level accuracy in dense 3D reconstruction and long-term stable localization over hectometer-scale scenes, validating the spatial consistency perception capability of 3D sonar under strong reverberation and low-texture conditions. A high-quality underwater 3D sonar–image dataset will be publicly released.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: 3D Computer Vision
• Machine Learning: Multimodal Learning

Application Category

• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

In the past decade, the adoption of compact 3D range sensors, such as LiDARs, has driven the developments of robust state-estimation pipelines, making them a standard sensor for aerial, ground, and space autonomy. Unfortunately, poor propagation of electromagnetic waves underwater, has limited the visibility-independent sensing options of underwater state-estimation to acoustic range sensors, which provide 2D information including, at-best, spatially ambiguous information. This paper, to the best of our knowledge, is the first study examining the performance, capacity, and opportunities arising from the recent introduction of the first compact 3D sonar. Towards that purpose, we introduce calibration procedures for extracting the extrinsics between the 3D sonar and a camera and we provide a study on acoustic response in different surfaces and materials. Moreover, we provide novel mapping and SLAM pipelines tested in deployments in underwater cave systems and other geometrically and acoustically challenging underwater environments. Our assessment showcases the unique capacity of 3D sonars to capture consistent spatial information allowing for detailed reconstructions and localization in datasets expanding to hundreds of meters. At the same time it highlights remaining challenges related to acoustic propagation, as found also in other acoustic sensors. Datasets collected for our evaluations would be released and shared with the community to enable further research advancements.

Problem

• Developing calibration procedures for 3D sonar-camera systems
• Creating mapping and SLAM pipelines for underwater environments
• Evaluating 3D sonar performance in challenging acoustic conditions

Innovation

• Calibrating 3D sonar with camera extrinsics
• Novel mapping and SLAM pipelines
• Testing in challenging underwater environments