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

TL;DR

This paper presents a bio-inspired neural network algorithm for optimal UUV path planning that effectively compensates for ocean currents, improving navigation accuracy in underwater environments.

Contribution

It introduces a novel neural network-based method combined with an adjustment component to optimize UUV paths considering ocean currents, which is a new approach in underwater navigation.

Findings

The proposed algorithm outperforms traditional methods without current consideration.

It effectively adjusts paths in various current conditions.

Results demonstrate improved collision avoidance and path optimality.

Abstract

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.