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Unmanned ship global path multi-objective planning method based on improved ant colony algorithm

A technology of multi-objective programming and ant colony algorithm, which is applied in the field of global path multi-objective planning of unmanned ships based on the improved ant colony algorithm, can solve the problems of slow convergence speed and high smoothing coefficient of the global path at local extremum, and achieve faster convergence speed , increase the global solution space, and enhance the guiding effect

Pending Publication Date: 2020-04-17
HARBIN ENG UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the problems of slow convergence speed of basic ant colony algorithm, easy to fall into local extremum and high global path smoothing coefficient, and propose a global path multi-objective planning scheme for unmanned boats based on improved ant colony algorithm

Method used

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  • Unmanned ship global path multi-objective planning method based on improved ant colony algorithm
  • Unmanned ship global path multi-objective planning method based on improved ant colony algorithm
  • Unmanned ship global path multi-objective planning method based on improved ant colony algorithm

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Experimental program
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Effect test

Embodiment 1

[0172] Embodiment 1 is realized by the following steps:

[0173] For a certain type of unmanned surface vehicle, the initialization of the improved ant colony algorithm is as follows:

[0174] The next node probability of ant colony tracing is modified as follows:

[0175]

[0176] The next node of the ant trace:

[0177]

[0178] J is the adjusted heading angle when the USV shipboard laser radar scans and detects that the obstacle is within a safe distance The next node reached.

[0179] Pheromone selection threshold: pheThres = 0.8,

[0180] Pheromone calculation parameters: pheCacuPara=2,

[0181] Pheromone update parameters: pheUpPara=[0.1,0.0003],

[0182] Heuristic information parameters: qfzPara1=ones(10,1)*0.5, qfzPara2=1.1

[0183] Number of ants: m=10,

[0184] Iterative algebra: nc=500,

[0185] Link line point ratio parameter: hi=pathk(l+1,k) / 10,

[0186] USV real-time direction angle: ψt=acos(angleend-anglestart),

[0187] USV Expected Direction A...

Embodiment 2

[0223] Embodiment 2 realizes according to the following steps:

[0224] This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0225] In the step 6, consider multi-objective tasks such as the shortest global path, the shortest number of algorithm optimization iterations, and the lowest path smoothing coefficient to carry out the simulation experiment of the global path planning of the unmanned vehicle. The global path smoothing coefficient of the UAV is designed as follows:

[0226] The optimal global path smoothness reflects the requirement of the minimum accumulative deflection angle of the heading angle of the unmanned vehicle when navigating at sea, and can improve the safety factor of the global path tracking control of the unmanned vehicle, which is one of the goals of algorithm optimization. When the USV controls the heading change, it needs additional heading angle auxiliary thrusters to work, but the auxiliary heading angle ...

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Abstract

The invention belongs to the field of unmanned ship global path planning and particularly relates to an unmanned ship global path multi-target planning method based on the improved ant colony algorithm. The method comprises steps of establishing a marine environment map model by utilizing a Maklink graph theory; improving a path heuristic information strategy to obtain a path average value; designing an ant pheromone volatilization adaptive adjustment strategy; designing a strategy combining local pheromone updating and global pheromone updating; improving the state transition probability of anext node searched by an ant colony through a heading angle deviation factor of an unmanned ship; and designing an evaluation function by integrating the requirements of the shortest global path length, the least optimization iteration times of the improved ant colony algorithm, the lowest path smoothing coefficient and the like. The method is advantaged in that multiple targets such as a globalpath distance of marine navigation of an unmanned surface vehicle, the iteration frequency of optimizing the global path by improving the ant colony algorithm and the smoothness coefficient of the planned global path are comprehensively considered, the optimal global path of marine navigation of the unmanned surface vehicle is finally planned, and the method has relatively high safety.

Description

technical field [0001] The invention belongs to the field of global path planning of unmanned boats, and in particular relates to a multi-objective planning method for global paths of unmanned boats based on an improved ant colony algorithm. Background technique [0002] With the development of modern society, technical means such as sensor miniaturization and high precision, intelligent control theory, and unmanned equipment system engineering are constantly being introduced. The wide application in the military and civilians such as exploration has made unmanned systems a cutting-edge cutting-edge technology that the world's technological powers are vying to capture first. Among them, the unmanned surface vehicle (USV), as a representative of unmanned systems in the ocean, can perform marine scientific research and engineering tasks for a long time, at low cost and on a large scale, and is extremely popular in the military and civil fields. Potential use of space, such as...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0206
Inventor 王元慧陈伟张晓云徐玉杰谢可超王晓乐徐明刘扬
Owner HARBIN ENG UNIV
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