Intelligent ship path planning method based on fast search genetic algorithm

Abstract

The invention relates to an intelligent ship path planning method based on a fast search genetic algorithm. The method comprises the steps of (S1) performing rasterization on a test site electronic chart, obtaining obstacle points for the rasterized chart, obtaining starting point coordinates and target port coordinates, presetting a maximum number G of iterations, an initial temperature T0, an ending temperature Tf and an attenuation value a, and obtaining an initial path set pop0 and an inflection point of an unmanned ship, (S2) obtaining the inflection point spacing sum D of each path in the initial path set pop0, and (S3) obtaining an updated path set popm through G times of iterations by using crossover, variation, proportional selection and annealing optimization operations accordingto the inflection point spacing sum D, a target temperature T and a preset attenuation value a, performing temperature updating according to an attenuation coefficient a, and selecting a shortest path in the updated path set popm as an optimal path when T is smaller than Tf. The planned path of the invention has a small steering angle, the trajectory is smooth, an obstacle is actively avoided, the method is close to actual navigation application, the convergence speed is fast, and the problem that a traditional genetic algorithm is easy to fall into a local extremum is overcome.

Description

technical field [0001] The invention relates to the field of unmanned ship navigation control, in particular to an intelligent ship path planning method based on a fast search genetic algorithm. Background technique [0002] Intelligent unmanned ship is a kind of unmanned ship, which has autonomous navigation, intelligent engine room, energy efficiency management, cargo transportation and intelligent integration platform; compared with traditional human-controlled driving mode, autonomous ship navigation has a high safety factor, economical and environmental protection , green energy saving and high degree of automation, and the core of the ship's autonomous navigation is autonomous obstacle avoidance path planning; in the ship's autonomous navigation decision-making system, its main task is to determine the ship's needs in an environment with obstacles or when the navigation environment changes. Temporarily adjust the local route according to the navigation environment, and...

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Problems solved by technology

[0003] At present, the commonly used methods in the local planning of ship navigation routes mainly include A* algorithm grid method, genetic algorithm, simulated annealing algorithm, particle swarm algorithm, and ant colony algorithm; However, such methods also have the following problems in the actual application process; (1) If the A* algorithm is used for ship autonomous navigation planning, although it can achieve rapid route planning, it does not consider the craft of the ship itself. Therefore, there will be more inflection points for large-angle steering; (2) the short distance between the inflection point and the obstacle is not conducive to the operation of the ship's navigation, and cannot guarantee the safety and stability of the ship to avoid obstacles, so it lacks practical applicability; (3) the genetic The algorithm is prone to premature convergence when solving practical application problems, which makes the efficiency of path search in the later stage lower; therefore, there is an urgent need for a method that can accurately identify obstacles while obtaining the optimal path to avoid obstacles in combination with the characteristics of the ship itself. An intelligent obstacle avoidance path planning method with better operability

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