| 内容提要: |
This report investigates the path planning problem for unmanned surface vehicle (USV), wherein the goal is to find the shortest, smoothest, most economical and safest path in the presence of obstacles and currents, which is subject to the collision avoidance, motion boundaries and velocity constraints. It is formulated that this problem is treated as a multi-objective nonlinear optimization problem with generous constraints. Then, a new method namely the dynamic augmented multi-objective particle swarm optimization algorithm is proposed to achieve the solution. With this approach, USV can select the ideal path from the Pareto optimal paths set. Numerical simulations verify the effectiveness of our formulated model and proposed algorithm. |