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An Effective Initialization Method for Genetic Algorithm-based Robot Path Planning using a Directed Acyclic Graph

Abstract

The goal of robot path planning is to find a feasible path that proceeds from a starting point to a destination point without intersecting any obstacles in the given environment. Recently, genetic algorithm-based robot path planning methods have been widely considered in the intelligent robotics community. Because the initialization process significantly influences the performance of the genetic algorithm, an effective initialization method is required. However, investigation on this subject is still lacking. In this paper, we propose an effective initialization method for genetic algorithm-based robot path planning. Experimental results comparing genetic algorithms with conventional initialization methods and the proposed initialization method showed that the proposed method leads to high quality paths in a significantly shorter execution time.

This program is designed to generate initial path set for genetic algorithm-based robot path planning.

[Paper]

Jaesung Lee and Dae-Won Kim, "An Effective Initialization Method for Genetic Algorithm-based Robot Path Planning using a Directed Acyclic Graph," Information Sciences, 332(1):1-18, 2016 Entropy, 2020

License

This program is available for download for non-commercial use, licensed under the GNU General Public License, which is allows its use for research purposes or other free software projects but does not allow its incorporation into any type of commerical software.

Sample Input and Output

SGMP function will return the path set according to given map. This code can be executed from MATLAB command window. Detailed information is given below.

[Usage]:

>> [pathSet, execTime, dag] = sgmp( map, sp, dp, setSize, numPt );

[Description]

pathSet – A set of path that contains “setSize” paths
execTime – A history of execution time for creating each path
dag – A Directed Acyclic Graph created by SGMP

map – A map specified in the binary square matrix
sp – The index of starting node
dp – The index of destination node
setSize – The number of paths to be created from DAG
numPt – The maximum number of allowable parents node

For more detailed information, please type “help sgmp” from MATLAB command window.

Other miscellaneous functions are also included in the ZIP package.

[Usage]:

>> draw_path( map, path ); – it will draw the obtained path.
>> draw_dag( map, dag ); – it will draw the obtaind DAG.

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sgmp's Issues

Will algorithms like KDtree improve the speed?

Thank you for your splendid work. I have read your code and have some questions about your implementation.

Your algorithm searches for the nearest nodes using brute force (line 163~169 in sgmp.m).
I wonder whether algorithms like KDtree improve the speed? Do you use brute force because it is fast or simple to implement?

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