Design and Implementation of Global Path Planning System for Unmanned Surface Vehicle among Multiple Task Points
This addresses path planning for USVs, an incremental improvement combining existing techniques for better performance.
This paper tackles global path planning for unmanned surface vehicles (USVs) among multiple task points by establishing environment modeling with hexagonal grids and Cube coordinates, and proposing improved A* and ant colony optimization algorithms. Simulation results show the system plans optimal paths that are superior to traditional methods in safety, rapidity, and path length.
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.