robotics
The Sonar Taught One Camera to See the Underwater Floor
AquaBEV uses paired 3D imaging sonar during training, then predicts local bird's-eye occupancy from a single RGB image.
Summary
AquaBEV uses paired 3D imaging sonar during training, then predicts local bird's-eye occupancy from a single RGB image.
Underwater appearance offers weak geometry, so AquaBEV maps visual features into a calibration-free polar representation and decodes outward along range before reconstructing a Cartesian occupancy map. On a controlled benchmark, it reached 31.4 visible IoU and 38.6 observed IoU, relative improvements of 4.0 and 4.3 percent over the strongest transferred baseline. The paper evaluates a controlled dataset; it does not certify monocular navigation in open water.
Why it matters
AquaBEV uses paired 3D imaging sonar during training, then predicts local bird's-eye occupancy from a single RGB image.
Limits and context
- The paper evaluates a controlled dataset; it does not certify monocular navigation in open water.
Key claims
AquaBEV uses paired 3D imaging sonar during training, then predicts local bird's-eye occupancy from a single RGB image.
Qualification: The paper evaluates a controlled dataset; it does not certify monocular navigation in open water.
Evidence: source-2026-09-07-009
Sources
- arXiv preprint 2609.04411arXiv · primary research
Corrections
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