The Mixing Algorithm of ACO and GA Based Global Path Planning Method for Mobile Robot

Abstract:

An ant colony algorithm is a stochastic searching optimization algorithm that is based on the heuristic behavior of the biologic colony. Its positive feedback and coordination make it possible to be applied to a distributed system. It has favorable adaptability in solving combinatorial optimization and has great development potential for its connotative parallel property. This study focused on global path planning with an ant colony algorithm in an environment based on grids, which explores a new path planning algorithm. How to present and update the pheromone of an ant system was investigated. The crossover operation of a genetic algorithm was used in the ant system for path optimization. Experimental results show that the algorithm has better path planning optimization ability than other algorithms.

• Periodical: Applied Mechanics and Materials (Volumes 494-495)
• Pages: 1290-1293
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.494-495.1290
• Online since: February 2014
• Authors: Shi Gang Cui, Jiang Lei Dong*, Fan Liang
• Keywords: Ant Colony Algorithm (ACO), Genetic Algorithm (GA), Global Path Planning, Robot

References

[1] ZHANG Ying, WU Chengdong, YUAN Baolong. Progress on path planning research for robot[J]. Control Engineering of China, 2003, 10(supplement): 152-155.

[2] WANG Xingce, ZHANG Rubo, GU Guochang. Potential grid based global path planning for robots[J]. Journal ofHarbin Engineering University, 2003, 4: 170-174.

[3] LIU Yuming. Research on global path planning for AUV based on genetic algorithm[D]. Harbin: Harbin Engineering University, (2002).

[4] MARTIN M, FRANK R, HARTMUT S. Multi colonyant algorithms [J]. Journal of Heuristics, 2002, 8: 305-320.

[5] DANIEL M, MARTIN M. Ant colony optimization withglobal pheromone evaluation for scheduling a single machine[J]. AppliedIntelligence, 2003, 18: 105-111.