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基于多策略混合人工鱼群算法的移动机器人路径规划

发布时间:2018-07-21 16:18
【摘要】:针对移动机器人的路径规划问题,提出了一种基于多策略混合人工鱼群算法的路径规划方法(MH-AFSA).为了提高传统人工鱼群算法(AFSA)的收敛速度和全局搜索能力,引入多策略混合机制,利用加权平均距离策略,扩大了人工鱼的视野范围.采用对数函数作为步长的移动因子,克服了传统固定步长的缺陷.进一步利用高斯变异策略扩大了种群的多样性.通过经典函数优化和旅行商问题(TSP)测试了算法的性能.最后,建立移动机器人的环境模型,给出了基于多策略混合人工鱼群算法的移动机器人路径规划步骤.通过数值仿真说明了所提算法的优越性和有效性.
[Abstract]:A path planning method (MH-AFSA) based on multi-strategy hybrid artificial fish swarm algorithm (MH-AFSA) is proposed for path planning of mobile robots. In order to improve the convergence speed and global search ability of the traditional artificial fish swarm algorithm (AFSA), a multi-strategy hybrid mechanism was introduced, and the weighted average distance strategy was used to enlarge the field of vision of artificial fish. The logarithmic function is used as the moving factor of step size, which overcomes the defect of traditional fixed step size. Further use of Gao Si mutation strategy to expand the diversity of the population. The performance of the algorithm is tested by classical function optimization and traveling salesman problem (tsp). Finally, the environment model of mobile robot is established, and the path planning steps of mobile robot based on multi-strategy hybrid artificial fish swarm algorithm are presented. Numerical simulation shows the superiority and effectiveness of the proposed algorithm.
【作者单位】: 安徽工程大学电气工程学院;安徽省检测技术与节能装置省级重点实验室;
【基金】:国家自然科学基金资助项目(61304127) 安徽省自然科学基金资助项目(1408085QF132) 安徽工程大学中青年拔尖人才资助项目(2016BJRC004)
【分类号】:TP18;TP242

【参考文献】

相关期刊论文 前10条

1 殷霞红;倪建军;吴榴迎;;一种基于改进人工蜂群算法的机器人实时路径规划方法[J];计算机与现代化;2015年03期

2 杨淑云;徐云霞;李盼池;;基于Bloch球面搜索的量子鱼群算法[J];信息与控制;2014年06期

3 翁理国;纪壮壮;夏e,

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