A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac Sim
Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so reported performance does not always describe behavior outside training. This paper presents a pipeline-tracking architecture for a six-degree-of-freedom remotely operated vehicle (ROV) in which one Universal Scene Description (USD) scene supplies the real BlueROV2-Heavy mass, added-mass, damping, buoyancy, and thruster parameters to both halves of the system: a vectorized NumPy implementation of Fossen's marine-craft equations, and an interactive NVIDIA Isaac Sim deployment applying the identical equations as PhysX forces at every step. The Co...
| Authors | Cheng Siong Chin, M. Venkateshkumar, Jianhua Zhang |
|---|---|
| Primary category | cs.RO |
| Published | 4 October 2026 |
| Last updated at source | 4 October 2026 |
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