[1]张兴国,周东健,李成浩.基于粒子群-蚁群融合算法的移动机器人路径优化规划[J].江西师范大学学报(自然科学版),2014,(03):274-277.
 ZHANG Xing-guo,ZHOU Dong-jian,LI Cheng-hao.The Optimal Path Planning for Mobile Robot Based on Ant Colony Algorithm Combined with Particle Swarm Optimization[J].,2014,(03):274-277.
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基于粒子群-蚁群融合算法的移动机器人路径优化规划()
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《江西师范大学学报》(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2014年03期
页码:
274-277
栏目:
出版日期:
2014-06-30

文章信息/Info

Title:
The Optimal Path Planning for Mobile Robot Based on Ant Colony Algorithm Combined with Particle Swarm Optimization
作者:
张兴国;周东健;李成浩
南通大学机械工程学院,江苏 南通,226019
Author(s):
ZHANG Xing-guo;ZHOU Dong-jian;LI Cheng-hao
关键词:
蚁群算法粒子群算法TSP问题路径规划移动机器人
Keywords:
ant colony algorithmparticle swarm optimizationTSP problempath planningmobile robot
分类号:
TP242
文献标志码:
A
摘要:
基于TSP问题,提出了一种基于粒子群-蚁群算法相互融合的综合优化算法对移动机器人路径规划问题进行研究。通过粒子群算法对全局路径实施粗略搜索,获得部分次优解,在获得次优解的路径上进行信息素分布,再采用蚁群算法进行精确搜索,得到路径规划的最优解。实验结果表明:粒子群-蚁群融合优化算法在路径寻优上优于蚁群算法及粒子群算法。
Abstract:
Aiming at the TSP problem,in order to research the optimal path planning for mobile robot,a new algo-rithm based on ant colony algorithm combined with particle swarm algorithm( PAAAA)has been proposed. Firstly, using the particle swarm optimization to search the global path,the second best solution is obtained. Then,after dis-tributing the pheromones on the second best solution paths,using ant colony algorithm to finish accurate searching. Last,the optimal solution of path planning is achieved. The simulation result shows that PAAA is better than single ant colony algorithm or single particle swarm optimization.

参考文献/References:

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备注/Memo

备注/Memo:
江苏省自然科学基金(BK20131205)
更新日期/Last Update: 1900-01-01