Path Planning Algorithm Comparison Analysis for Wireless AUVs Energy Sharing System

TL;DR

This paper compares RRT* and PSO algorithms for efficient obstacle-avoiding path planning in wireless energy-sharing systems for AUVs, enhancing autonomous underwater navigation in complex environments.

Contribution

It introduces a combined RRT* and PSO approach for obstacle avoidance in AUV path planning, with comparative simulation analysis demonstrating improved efficiency.

Findings

RRT* and PSO algorithms are effective for underwater obstacle avoidance.

The combined approach improves path planning efficiency in complex environments.

Simulation results validate the proposed method's effectiveness.

Abstract

Autonomous underwater vehicles (AUVs) are increasingly used in marine research, military applications, and undersea exploration. However, their operational range is significantly affected by battery performance. In this paper, a framework for a wireless energy sharing system among AUVs is proposed, enabling rapid energy replenishment. Path planning plays a crucial role in the energy-sharing process and autonomous navigation, as it must generate feasible trajectories toward designated goals. This article focuses on efficient obstacle avoidance in complex underwater environments, including irregularly shaped obstacles and narrow passages. The proposed method combines Rapidly-exploring Random Trees Star (RRT*) with Particle Swarm Optimization (PSO) to improve path planning efficiency. Comparative analysis of the two algorithms is presented through simulation results in both random and irregular obstacle environments. Index Terms: Wireless charging, autonomous underwater vehicles (AUVs), path planning, irregular obstacles, narrow passages, RRT*, particle swarm optimization (PSO).