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Mobile robot path planning method based on improved ant colony algorithm

A mobile robot and ant colony algorithm technology, applied in the field of robotics, can solve problems such as easy to fall into local optimal solution, slow convergence speed of ant colony algorithm, etc., to enhance the optimization ability, avoid local optimal solution, and speed up the convergence speed Effect

Inactive Publication Date: 2022-04-12
CHINA JILIANG UNIV
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Problems solved by technology

However, the ant colony algorithm also has problems such as slow convergence speed and easy to fall into local optimal solution.

Method used

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  • Mobile robot path planning method based on improved ant colony algorithm
  • Mobile robot path planning method based on improved ant colony algorithm
  • Mobile robot path planning method based on improved ant colony algorithm

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Embodiment 1

[0057] A kind of mobile robot path planning method based on improved ant colony algorithm of the present invention, flow chart is as follows figure 1 As shown, it specifically includes the following steps:

[0058] S1: Establish a grid map, determine the starting node, target node and obstacle information.

[0059] S2: Initialize the parameters of the ant colony algorithm, generate the initial path according to the artificial potential field method, update the initial pheromone matrix of the path, and initialize the taboo table.

[0060] Specifically, the artificial potential field method is affected by the gravitational force of the target node and the repulsive force of obstacles during the path planning process, thereby quickly generating a path. The gravitational field function and repulsive field function are shown in the following formula:

[0061] u att (X) = 0.5αρ 2 (X,X g )

[0062]

[0063] In the formula, X=(x, y) is the position vector of the robot, α and β...

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Abstract

The invention provides a mobile robot path planning method based on an improved ant colony algorithm. The method comprises the following steps: establishing a grid map; all parameters of the ant colony algorithm are initialized, an initial path is generated according to an artificial potential field method, an initial pheromone matrix of the path is updated, and a tabu table is initialized; a selectable node is constructed according to the tabu table and the obstacle information, a candidate solution is constructed according to an improved state transition rule, and a next node is selected according to a roulette principle; updating the taboo table and recording path nodes and path lengths of the ants; judging whether the ants arrive at a target node or not, if the ants arrive at the target node, performing node optimization on the complete path according to a node optimization strategy to obtain an optimal path of current iteration, and performing pheromone global updating; and performing iteration according to a preset maximum number of iterations to obtain an optimal path. According to the invention, the traditional ant colony algorithm is optimized and improved to achieve the effects of accelerating the convergence speed of the algorithm and avoiding the local optimal solution.

Description

technical field [0001] The invention relates to the technical field of robotics, in particular to a path planning method for a mobile robot based on an improved ant colony algorithm. Background technique [0002] The path planning of a mobile robot refers to planning an optimal solution path for the robot from the starting point to the target point within a specified area, and it must ensure that there is no collision with obstacles. Path planning algorithms have been developed so far, which can be generally divided into two categories: traditional path planning algorithms and intelligent bionic path planning algorithms. Among them, traditional algorithms mainly include A* algorithm, artificial potential field algorithm, and tabu search algorithm; while intelligent bionic algorithms mainly include ant colony algorithm, particle swarm algorithm, and genetic algorithm. Ant colony algorithm has been widely used in the field of path planning because of its unique advantages. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
Inventor 王丽娜王鹤静杨鑫高雁凤崔小红王斌锐
Owner CHINA JILIANG UNIV
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