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Mobile robot path planning method based on ant colony improvement and peak smoothing

A mobile robot and peak smoothing technology, applied in navigation computing tools and other directions, can solve problems such as slow solution speed, energy loss, easy to fall into local optimal solution, etc., achieve the effect of smooth path corners and reduce energy loss

Active Publication Date: 2018-06-19
KUNMING UNIV OF SCI & TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

The basic ant colony algorithm has the disadvantages of slow solution speed and easy to fall into the local optimal solution; most of the above-mentioned algorithms ignore the requirement of path smoothness in path planning, which will make the robot poorly balanced, and will cause abnormal necessary energy loss

Method used

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  • Mobile robot path planning method based on ant colony improvement and peak smoothing
  • Mobile robot path planning method based on ant colony improvement and peak smoothing
  • Mobile robot path planning method based on ant colony improvement and peak smoothing

Examples

Experimental program
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Effect test

Embodiment 1

[0028] Embodiment 1: as Figure 1-8 As shown, a mobile robot path planning method based on ant colony improvement and peak smoothing, the method steps are as follows:

[0029] S1. Using the grid method to model the environment of the mobile robot's operating space;

[0030] S2. Set parameters, initialize the number of ants M, the number of iterations N, the starting point and the ending point of ants, the heuristic factor α, the expected heuristic factor β, the pheromone volatilization coefficient ρ, the pheromone increase intensity coefficient Q, and the expected deflection angle θ 1 , taboo list B k initialization;

[0031] S3, M ants start from the initial point;

[0032] S4. Ant individual k according to the state transition probability The formula transfers from grid i to adjacent grid j with the maximum transition probability;

[0033] S5. Every time ant individual k is transferred, grid j is added to taboo table B k ;

[0034] S6. Update the formula τ according ...

Embodiment 2

[0041] Embodiment 2: as Figure 1-8 As shown, a mobile robot path planning method based on ant colony improvement and peak smoothing, the method steps are as follows:

[0042] Step 1. Use the grid method to model the environment of the mobile robot's operating space, such as figure 2 As shown, 1 in the matrix means black grids represent obstacles, 0 means white grids represent freely passable grids, and the working environment of the robot is divided into 20×20 and 17×17 grids;

[0043] Step 2: Initialize parameters, the number of ants M is 50, the number of iterations N is 200, the heuristic factor α is 1, the expected heuristic factor β is 7, the pheromone evaporation coefficient ρ is 0.7, the pheromone increase intensity coefficient Q is 1, the robot The starting point coordinates are (0.5,16.5), the ending point coordinates are (16.5,0.5), and the expected deflection angle θ 1 155°, taboo table B k initialization;

[0044] Step 3, M ants start from the initial point; ...

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Abstract

Belonging to robot path planning, artificial intelligence and other fields, the invention relates to a mobile robot path planning method based on ant colony improvement and peak smoothing. The invention integrates elite ant strategy and a center point based smoothing method, and introduces elitist strategy to solve the local optimum disadvantage. The center point based smoothing method has a correction effect on the path peak, makes the path corner more smooth, enables a robot entity to move forward steadily in the turning process, and simultaneously reduces unnecessary energy loss at the pathpeak. Through application of the improved ant colony algorithm to mobile robot path planning, a short and relatively smooth curve path can be obtained.

Description

technical field [0001] The invention relates to a path planning method for a mobile robot based on ant colony improvement and peak smoothing, and belongs to the fields of robot path planning, artificial intelligence, and the like. Background technique [0002] In recent years, the application of robots in daily life has become more and more extensive. As an important branch of robot applications, mobile robots have gradually shown their importance in production and life. Path planning for mobile robots is an important issue in robot autonomous navigation. The prerequisite for a robot to complete a certain task is to reach the task area. Therefore, path planning for mobile robots is an important research content in the field of robotics. [0003] Ant Colony Algorithn (ACA), also known as Ant Algorithm, was proposed by Marco Dorigo in his doctoral dissertation in 1992. It was inspired by the intelligent behavior that ant colonies can communicate through pheromones. The select...

Claims

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Application Information

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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 王娇娇毛剑琳
Owner KUNMING UNIV OF SCI & TECH
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