3D Underwater Path Planning via Generative Flow Field Surrogates
Autonomous underwater vehicle (AUV) launch and recovery (LAR) into the hull of an advancing host platform requires traversal of a complex, three-dimensional propeller wake whose hydrodynamic structure cannot be characterised by a uniform current model. High-fidelity Reynolds-Averaged Navier-Stokes (RANS) Computational Fluid Dynamics (CFD) simulations resolve this structure with sufficient accuracy for path planning, but their computational cost renders them impractical for onboard use. We address this gap by integrating two conditional generative adversarial network (cGAN) architectures -- a regularised PatchGAN and a 2D3DGAN with self-attention -- as drop-in replacements for RANS CFD dat...
| Authors | Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth et al. |
|---|---|
| Primary category | cs.RO |
| Published | 4 June 2026 |
| Last updated at source | 4 June 2026 |
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