# Bio-inspired Neural Network-based Optimal Path Planning for UUVs under the Effect of Ocean Currents

arXiv: https://arxiv.org/abs/2206.10087 · HTML: https://mlsanity.com/paper/2206.10087/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2022.

## Built on by (most cited first, 3 of 3)

- [A Hybrid Tracking Control Strategy for an Unmanned Underwater Vehicle Aided with Bioinspired Neural Dynamics](https://mlsanity.com/paper/2209.01484/) (2022)
- [Current Effect-eliminated Optimal Target Assignment and Motion Planning for a Multi-UUV System](https://mlsanity.com/paper/2401.05521/) (2024)
- [RadDQN: a Deep Q Learning-based Architecture for Finding Time-efficient Minimum Radiation Exposure Pathway](https://mlsanity.com/paper/2402.00468/) (2024)

## Abstract (arXiv)

To eliminate the effect of ocean currents when addressing the optimal path in the underwater environment, an intelligent algorithm designed for the unmanned underwater vehicle (UUV) is proposed in this paper. The algorithm consists of two parts: a neural network-based algorithm that deducts the shortest path and avoids all possible collisions; and an adjusting component that balances off the deviation brought by the effect of ocean currents. The optimization results of the proposed algorithm are presented in detail, and compared with the path planning algorithm that does not consider the effect of currents. Results of the comparison prove the effectiveness of the path planning method when encountering currents of different directions and velocities.