A Hybrid Algorithm to Solute the Problem of the Robot Path Planning

Quan Bo Yuan; Hui Juan Wang; Peng Hua Zhu; Hui Zhao

doi:10.4028/www.scientific.net/AMR.383-390.385

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 383-390A Hybrid Algorithm to Solute the Problem of the...

A Hybrid Algorithm to Solute the Problem of the Robot Path Planning

Abstract:

This paper analyzes the problems of artificial potential fields in robot path planning. A hybrid algorithm for robot path planning is proposed. Robot searching for path in artificial potential fields method, it is possible that the robot can’t reach the goal because of local minimum, when it is best to use a genetic algorithm for robot. Simulation results show the effectiveness of the models, and it can effectively solve the problem caused by defects of artificial potential fields in the path planning.

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Periodical:

Advanced Materials Research (Volumes 383-390)

Pages:

385-389

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.383-390.385

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Online since:

November 2011

Authors:

Quan Bo Yuan, Hui Juan Wang, Peng Hua Zhu, Hui Zhao

Keywords:

Artificial Potential Field (APF), Genetic Algorithm (GA), Path Planning

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References

[1] PARK MG, LEE MC. Artificial Potential Field Based Path Planning for Mobile Robots Using a Virtual Obstacle Concept[J]. IEEE/ASME International conference on Advanced Intelligent Mechatronics(AIM), 2003: 735-740.

DOI: 10.1109/aim.2003.1225434

Google Scholar

[2] WANGC, SOHYC, WANGH , et al . A hierarchical enetic algorithm for path planning ina static environme nt with obstacles[ A]. I EEE Canadian Conference on Electrical and Computer Engineering [C ]. Canada : IE EE, 20 02. (3 ): 1652—1657.

Google Scholar

[3] GOLDBERG D E . Genetic Algorithm in Search, OptimAssion and Machine Learning[M]. New York: Assion— Wesley Publishing Company, (1989).

Google Scholar

[4] Liu Jinkun, How to design Robot Control System and matlab simulation, 2008, 680—685.

Google Scholar

[5] NOBORU N, HIDEO T. Path planning of agricultural mobile robot by neural network and genetic algorithm [J]. Computers and Electronics in Agriculture, 1997, (18): 187—204.

DOI: 10.1016/s0168-1699(97)00029-x

Google Scholar

[6] WOONGGIE H, SEUNGMIN B, TAEYONG K. Genetic algorithm based path planning and dynamic obstacle avoidance of mobile robots[A]. IEEE International Conference on Computational Cybernetics and Simulation[C]. Orlando: IEEE, 1997. (3): 2747—2751.

DOI: 10.1109/icsmc.1997.635354

Google Scholar