期刊
CURRENT DEVELOPMENT OF MECHANICAL ENGINEERING AND ENERGY, PTS 1 AND 2
卷 494-495, 期 -, 页码 1290-+出版社
TRANS TECH PUBLICATIONS LTD
DOI: 10.4028/www.scientific.net/AMM.494-495.1290
关键词
Ant colony algorithm(ACO); Genetic algorithm(GA); Global path planning; Robot
资金
- National Natural Science Foundation of China [61178048]
- National Social Science Fund [BFA110049]
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.
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