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Path Planning Method for Mobile Robot Based on Improved Genetic Algorithm

A mobile robot and path planning technology, applied in genetic rules, instruments, genetic models, etc., can solve the problems of slow running speed and genetic algorithm falling into local optimum, and achieve the effect of improving performance and speeding up search efficiency

Active Publication Date: 2019-02-05
JIANGSU UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a mobile robot path planning method and system to solve the technical problems that the existing genetic algorithm is easy to fall into local optimum and slow running speed

Method used

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  • Path Planning Method for Mobile Robot Based on Improved Genetic Algorithm
  • Path Planning Method for Mobile Robot Based on Improved Genetic Algorithm
  • Path Planning Method for Mobile Robot Based on Improved Genetic Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0071] Such as figure 1 As shown, this implementation 1 provides a mobile robot path planning method, including the following steps:

[0072] Step S1, environment modeling; and

[0073] Step S2, execute the genetic algorithm to output the optimal path.

[0074] The step S1 environment modeling is to model the working environment of the mobile robot to establish a coordinate system. The method includes: using the mobile robot's own sensor group (such as but not limited to a camera, sonar ring, infrared sensor) to collect the working environment Information, and map modeling; where the mobile robot is used as a particle, the mobile robot and obstacles are modeled according to the two-dimensional coordinate system, and the two-dimensional workspace is divided by grids of the same size, so that the mobile robot can freely move in this space sports;

[0075] If there is an obstacle in a grid, define this grid as an obstacle grid, otherwise it is a free grid; and

[0076] Number...

Embodiment 2

[0109] On the basis of embodiment 1, this embodiment 2 provides a mobile robot path planning system,

[0110] The mobile robot path planning system includes:

[0111] a modeling unit to model the working environment of the mobile robot to establish a coordinate system;

[0112] A path calculation unit executes a genetic algorithm to output an optimal path.

[0113] Specifically, the mobile robot has its own sensor group to collect the working environment information and perform map modeling; where the mobile robot is used as a particle, the mobile robot and obstacles are modeled according to the two-dimensional coordinate system, and the grid with the same size Divide the two-dimensional workspace so that the mobile robot can move freely in the space;

[0114] If there is an obstacle in a grid, define this grid as an obstacle grid, otherwise it is a free grid; and

[0115] Number each grid with a serial number, and each number N corresponds to its rectangular coordinates on...

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Abstract

The invention relates to a mobile robot path planning method and system based on an improved genetic algorithm. The mobile robot path planning method comprises the following steps: step S1, modeling an environment; and step S2, executing the genetic algorithm to output an optimal path. The mobile robot path planning method and system accelerate the search efficiency of a robot, avoid local optimum, improve the performance of the algorithm, effectively avoid a local optimal solution and solve the problem of low convergence rate of the traditional genetic algorithm.

Description

technical field [0001] The invention relates to the technical field of mobile robot intelligent algorithms, in particular to a path planning method based on an improved genetic algorithm. Background technique [0002] Mobile robot path planning is an important research field of robotics. In addition to being used in space exploration, ocean development, and atomic energy, it also has broad application prospects in factory automation, construction, mining, risk elimination, military, service, and agriculture. There are many methods of path planning, such as A* algorithm, artificial potential field method, fuzzy reasoning method, ant colony algorithm, etc. Although the A* algorithm is used for relatively simple maps, its search speed is very fast, and it can also find the optimal path , but the overall performance is poor, and improper heuristic function selection is easy to fall into an infinite loop; using the artificial potential field method is convenient for real-time con...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02G06N3/12
CPCG05D1/0221G06N3/126
Inventor 俞烨贺乃宝孙阳阳
Owner JIANGSU UNIV OF TECH
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