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Using Cellular Ant Colony Algorithm for Path-Planning of Robots

Yong Fen Wu, Xin Xing Zhang, Jun Wu

发表年份
2012
引用次数
4

摘要

To overcome some shortcoming existed in the conventional ant colony algorithms, e.g. slow converging and trend for falling into local convergences, a novel method for robot path planning is introduced based on cellular ant colony. Firstly, two ant colonies were set to run with different strategies. Secondly, the existing ant colony paths were evolved by following the cellular rules, so that the ants could jump from the current region into the region with a solution. Experiment results showed that the proposed algorithm proved to be stable, and that the global optimal path was found in a short time in a number of iterations.

关键词

Ant colony optimization algorithmsJumpPath (computing)Ant colonyMotion planningSet (abstract data type)Mathematical optimizationAlgorithmComputer scienceANT

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