  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.
