Mobile Robot Path Planning based on Parameter Optimization Ant Colony Algorithm

The basic ant colony algorithm for mobile robot path planning exists many problems, such as lack of stability, algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes improvement measures. Apply genetic algorithm to optimization an...

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Published in:Procedia engineering Vol. 15; pp. 2738 - 2741
Main Authors: Zhangqi, Wang, Xiaoguang, Zhu, Qingyao, Han
Format: Journal Article
Language:English
Published: Elsevier Ltd 2011
Subjects:
Ant colony algorithm
Genetic algorithm
Mobile Robot
Path planning
Mobile Robot
Path planning
Genetic algorithm
Ant colony algorithm
ISSN:1877-7058, 1877-7058
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Abstract The basic ant colony algorithm for mobile robot path planning exists many problems, such as lack of stability, algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes improvement measures. Apply genetic algorithm to optimization and configuration parameters of the basic ant colony algorithm. Simulation results show that the improved optimal path length significantly less than the basic ant colony algorithm and volatility is smaller, stability significantly improves. The stability of improved ant colony algorithm is superior to the basic ant colony algorithm, verify the effectiveness of the improvement measures.
AbstractList The basic ant colony algorithm for mobile robot path planning exists many problems, such as lack of stability, algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes improvement measures. Apply genetic algorithm to optimization and configuration parameters of the basic ant colony algorithm. Simulation results show that the improved optimal path length significantly less than the basic ant colony algorithm and volatility is smaller, stability significantly improves. The stability of improved ant colony algorithm is superior to the basic ant colony algorithm, verify the effectiveness of the improvement measures.
Author Qingyao, Han
Zhangqi, Wang
Xiaoguang, Zhu
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Cites_doi 10.1109/ICEC.1997.592327
10.1109/3477.484436
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Keywords Mobile Robot
Path planning
Genetic algorithm
Ant colony algorithm
Language English
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SubjectTerms Ant colony algorithm
Genetic algorithm
Mobile Robot
Path planning
Title Mobile Robot Path Planning based on Parameter Optimization Ant Colony Algorithm
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