Unmanned surface vehicle path planning method based on neighborhood intelligent water drop algorithm

Abstract

The invention relates to the technical field of unmanned surface vehicle path planning, in particular to an unmanned surface vehicle path planning method based on a neighborhood intelligent water drop algorithm. The method comprises the steps of 1, performing environment modeling on unmanned surface vehicle path planning; 2, performing off-line global path planning in an operation area grid matrix by utilizing the intelligent water drop (IWD) algorithm according to a known unmanned surface vehicle operation area static obstacle, an advancing goal and path evaluating function so as to obtain a global off-line optimum path. The problem that the method is stagnated and low in convergence rate caused by the fact that a basic IWD method is easily caught in local optical solution is improved, and an optical solution adjacency expansion mechanism and a global optimum stressing mechanism are introduced on the basis of the basic IWD method to obtain an NIWD method, so that prematurity caused by the fact that the method is caught in local optimum is avoided, and the optimizing convergence rate of the method is improved.

Description

technical field [0001] The invention relates to the technical field of path planning for an unmanned water surface boat, in particular to a path planning method for an unmanned water surface boat based on a neighborhood intelligent water droplet algorithm. Background technique [0002] With the transformation of combat methods, unmanned combat systems are one of the development trends of modern weapons and equipment. Unmanned surface vehicles (USV) can undertake intelligence collection, maritime reconnaissance and surveillance, precision strikes, search and capture, hydrographic surveys, anti-terrorism, and ocean blockade Support and other functions, so the development is rapid. Autonomous route planning is an important part of realizing USV autonomous navigation. [0003] The representative methods of USV path planning mainly include artificial potential field method, genetic algorithm, artificial neural network, and rapid random search tree algorithm (RRT). The artificia...

AI Technical Summary

Problems solved by technology

Although the IWD algorithm has been widely used in various fields, the IWD algorithm still has the problem that it is easy to fall into a local optimal solution, resulting in premature algorithm and slow convergence speed.

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