Bio-Inspired Neural Network-Based Optimal Path Planning for UUVs Under the Effect of Ocean Currents

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 details, 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.

Automated summary

An intelligent algorithm for unmanned underwater vehicles (UUVs) is proposed in this paper to address the optimal path in the underwater environment without being affected by ocean currents. The algorithm consists of a neural network-based algorithm for deducing the shortest path and avoiding collisions, and an adjusting component for balancing the deviation caused by ocean currents. The optimization results of the proposed algorithm are presented and compared with a path planning algorithm that does not consider the effect of currents. The results demonstrate the effectiveness of the proposed method when encountering currents of different directions and velocities.