Mission-driven path planning and design of submersible unmanned ship with multiple navigation states

The path planning of unmanned ships at the lowest energy consumption is of great significance for energy savings. At present, the path planning of unmanned ships based on the idea of energy savings is usually oriented toward a single navigation state, and there are few research projects on the path planning of ships that sail across multiple navigation states. The navigation states of submersible unmanned ships of path planning in this paper involves underwater navigation states with various diving depths and water's surface navigation state. The improved genetic algorithm is applied to carry out the path planning for a single navigation state and task-driven multi-navigation states of the submersible unmanned ship at energy-saving velocity and non-energy-saving velocity, respectively. The energy-saving velocities are obtained by establishing optimization models. The results show that, at energy-saving velocity, the energy consumption of the same type of navigation paths increase with the diving depth. There is an obvious velocity demarcation point at non-energy-saving velocity range, which makes the sequence of energy consumption of the three types of paths classed by navigation tasks reversed before and after that point. The research can provide technical support for path planning of cross-domain unmanned ships.