Underwater Dense Mapping with the First Compact 3D Sonar
Chinmay Burgul, Yewei Huang, Michalis Chatzispyrou, Ioannis Rekleitis, Alberto Quattrini Li, Marios Xanthidis
AI summary
Problem
Underwater autonomy is limited by poor electromagnetic wave propagation, forcing reliance on low-dimensional acoustic sensors or vision systems that fail in turbid, dark waters.
Approach
The study characterizes the new Sonar 3D-15 sensor, introduces a novel camera-to-sonar calibration method using concrete blocks, and integrates the sonar with visual-inertial odometry into a drift-reduced SLAM pipeline.
Key results
- Characterized Sonar 3D-15 acoustic response across diverse underwater materials
- Developed a target-based camera-to-sonar extrinsic calibration method
- Demonstrated reduced trajectory drift in sonar-only and fused sonar-VIO SLAM pipelines
- Publicly released multi-modal underwater datasets for community research
Why it matters
Provides a robust sensing foundation for autonomous underwater exploration, infrastructure inspection, and scientific mapping in previously inaccessible low-visibility environments.
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 exam- ining 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. The datasets used in our evaluation will be publicly released to support reproducibility and foster further research by the community: Dataset Repository.