Litcius/Paper detail

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

Danjie Zhu, Simon X. Yang

2021IEEE Transactions on Intelligent Vehicles67 citationsDOIOpen Access PDF

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 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.

Topics & Concepts

UnderwaterPath (computing)Artificial neural networkMotion planningShortest path problemComputer scienceAlgorithmOcean currentArtificial intelligenceGeologyRobotGraphTheoretical computer scienceClimatologyProgramming languageOceanographyUnderwater Vehicles and Communication SystemsRobotic Path Planning AlgorithmsMaritime Navigation and Safety