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Unmanned ship path planning method and system based on improved genetic algorithm

A technology for improving genetic algorithms and path planning, applied in the field of unmanned boat path planning methods and systems, can solve the problems of large amount of calculation of ant colony algorithm, self-intersection phenomenon of unmanned boats, combined explosion, etc., to reduce the cost of calculation time, Realize the effect of control and track correction, and improve the robustness

Active Publication Date: 2019-11-12
NANJING SEAWOLF OCEAN TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The inventors found in the research and development process that these algorithms have some defects when they are applied to the path planning of unmanned ships, and the free space method is difficult to apply to multi-dimensional path planning problems such as the path planning of unmanned ships; the artificial potential field method and the particle The swarm algorithm is prone to problems such as unreachable targets, falling into local optimum, and low efficiency, which cause self-intersection of unmanned vehicles; Both algorithms are time-consuming and cannot meet the timeliness requirements of unmanned vehicle path planning.
Although the traditional genetic algorithm cannot find the global optimal value due to the premature phenomenon, its good parallelism and efficient search ability meet the needs of unmanned vehicles in path planning

Method used

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  • Unmanned ship path planning method and system based on improved genetic algorithm
  • Unmanned ship path planning method and system based on improved genetic algorithm
  • Unmanned ship path planning method and system based on improved genetic algorithm

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Embodiment 1

[0067] This embodiment provides a method of path planning for unmanned boats based on an improved genetic algorithm, please refer to the attached figure 1 , the method includes the following steps:

[0068] S101. Obtain heading data and position data of the unmanned boat, and perform preprocessing on them.

[0069] Specifically, the longitude and latitude coordinates of the navigation point required by the unmanned boat are obtained through GPS and the electronic compass, and the longitude and latitude coordinates of the navigation point are transformed into the horizontal and vertical coordinate values ​​in the Cartesian coordinate system.

[0070] S102. Obtain weather and wave information of the environment where the unmanned boat is located, and convert them into constraint factors.

[0071] Specifically, the ultrasonic weather sensor collects the weather and wave information of the environment where the unmanned boat is located, including the height of the wave, the veloc...

Embodiment 2

[0135] An unmanned ship path planning system based on an improved genetic algorithm, the system includes:

[0136] The navigation data acquisition module is used to acquire the course data and position data of the unmanned boat, and preprocess it;

[0137] The constraint factor determination module is used to collect the weather and wind wave information of the environment where the unmanned boat is located, and convert it into a constraint factor;

[0138] The optimal path planning module is used to use the improved genetic algorithm to perform path planning according to the course data and position data of the unmanned boat, and obtain the optimal path sorting;

[0139] The track correction module is used to correct the course and speed of the unmanned vehicle according to the constraint factors based on the optimal path sorting, and complete the path planning.

Embodiment 3

[0141] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are realized;

[0142] Obtain the course data and position data of the unmanned boat, and preprocess it;

[0143] Collect the weather and wind and wave information of the environment where the UAV is located, and convert it into a constraint factor;

[0144] The improved genetic algorithm is used to plan the path according to the course data and position data of the unmanned vehicle, and the optimal path sorting is obtained;

[0145] Based on the optimal path sorting, the course and speed of the UAV are corrected according to the constraint factors to complete the path planning.

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Abstract

The invention discloses an unmanned ship path planning method and system based on an improved genetic algorithm, and the improved genetic algorithm is adopted to plan the path of an unmanned ship. Themethod comprises the following steps: acquiring course data and position data of the unmanned ship, and preprocessing the course data and the position data; collecting wave information of the environment where the unmanned ship is located, and converting the wave information into a constraint factor; performing path planning according to the course data and the position data of the unmanned shipby adopting an improved genetic algorithm to obtain an optimal path sequence; and based on the optimal path sequence, correcting the course and the speed of the unmanned ship according to the constraint factor, and completing path planning.

Description

technical field [0001] The present disclosure relates to the technical field of unmanned boat control, in particular to an unmanned boat path planning method and system based on an improved genetic algorithm. Background technique [0002] The Traveling Salesman Problem (TSP) is a typical NP-hard problem. Its purpose is to plan a shortest path for a traveling salesman to return to the starting city after visiting each city once. In production and life, the TSP model is widely used in many fields, such as vehicle path planning, machine learning, time map, word meaning disambiguation, green logistics, fuel efficiency management, wireless charging, etc. Therefore, solving the TSP problem is of great significance for home, civilian and military applications. [0003] In recent years, the research on the method of solving TSP problem mainly tends to the heuristic algorithm with adaptive control idea, such as genetic algorithm (GA), simulated annealing algorithm, ant colony algori...

Claims

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Application Information

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IPC IPC(8): G05D1/02G05B13/04
CPCG05D1/0206G05B13/042Y02T70/00
Inventor 辛峻峰张永波李世鑫杨奉儒李鹏昊
Owner NANJING SEAWOLF OCEAN TECH CO LTD
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