Design and Implementation of Global Path Planning System for Unmanned Surface Vehicle among Multiple Task Points

TL;DR

This paper presents a novel global path planning system for unmanned surface vehicles that uses hexagonal grids, an improved A* algorithm, and ant colony optimization to efficiently and safely plan routes among multiple task points.

Contribution

It introduces a new global environment model with hexagonal grids, simplifies algorithms with Cube coordinates, and enhances path planning with improved A* and ant colony optimization techniques.

Findings

The system plans optimal, safe, and rapid paths among multiple points.

Hexagonal grids outperform square grids in safety and speed.

The planned paths are directly applicable to real USV operations.

Abstract

Global path planning is the key technology in the design of unmanned surface vehicles. This paper establishes global environment modelling based on electronic charts and hexagonal grids which are proved to be better than square grids in validity, safety and rapidity. Besides, we introduce Cube coordinate system to simplify hexagonal algorithms. Furthermore, we propose an improved A* algorithm to realize the path planning between two points. Based on that, we build the global path planning modelling for multiple task points and present an improved ant colony optimization to realize it accurately. The simulation results show that the global path planning system can plan an optimal path to tour multiple task points safely and quickly, which is superior to traditional methods in safety, rapidity and path length. Besides, the planned path can directly apply to actual applications of USVs.