[1]王红君,徐军,赵辉,等.基于平滑蚁群算法的机器人路径规划[J].燕山大学学报,2017,41(3):278-282.[doi:10.3969/j.issn.1007-791X.2017.03.012]
 WANG Hongjun,XU Jun,ZHAO Hui,et al.Mobile robot path planning based on smoothing ant colony algorithm[J].Journal of YanShan University,2017,41(3):278-282.[doi:10.3969/j.issn.1007-791X.2017.03.012]
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基于平滑蚁群算法的机器人路径规划
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《燕山大学学报》[ISSN:1007-791X/CN:13-1219/N]

卷:
41
期数:
2017年第3期
页码:
278-282
栏目:
信息与计算机技术
出版日期:
2017-05-31

文章信息/Info

Title:
Mobile robot path planning based on smoothing ant colony algorithm
文章编号:
1007-791X(2017)03-0278-05
作者:
王红君1*徐军1赵辉12岳有军1
1.天津理工大学 天津市复杂系统控制理论与应用重点实验室,天津 300384;2.天津农学院 工程技术学院,天津 300384
Author(s):
WANG Hongjun1XU Jun1ZHAO Hui12YUE Youjun1
1.Tianjin Key Laboratory for Control Theory and Applications in Complicated System,Tianjin University of Technology,Tianjin 300384,China;2.College of Engineering and Technology,Tianjin Agricultural University,Tianjin 300384,China
关键词:
移动机器人路径规划平滑蚁群算法障碍物栅格地图
Keywords:
mobile robotpath planningsmoothing ant algorithmobstaclesgrid map
分类号:
TP242
DOI:
10.3969/j.issn.1007-791X.2017.03.012
文献标志码:
A
摘要:
在栅格环境下利用蚁群算法规划出来的移动机器人路径存在转弯次数多,累计转折角大等问题。针对这些问题,提出了平滑蚁群算法。平滑蚁群算法是在蚁群算法规划出来的最优路径的基础上,将当前节点与其它不在同一条直线上的节点依次连线,如果新的连接线不穿越障碍物,则将当前连接线作为新路径代替原来路径,并删除中间节点,否则对当前路径不作任何修改。仿真结果表明,平滑蚁群算法能够在不同栅格规模和障碍物覆盖率不同的情况下,有效降低路径长度,减少转折次数和累计转折角度,并且路经规划结果优于免疫遗传算法和势场蚁群算法的路径规划结果。
Abstract:
Path planning for mobile robot by ant colony algorithm is flaw with frequently turning points,large cumulative turning angle under grid environment.Smoothing ant colony algorithm is proposed to solve these problems.Smoothing ant colony algorithm is based on the optimal path planned by ant colony algorithm,connecting the current node and the nodes after the turning point,deleting original node and replacing the initial path by the new line as no obstacles existing on the line.Otherwise,the current path is not modified.The simulation results show that smoothing ant colony algorithm exceeds immune genetic algorithm and ant colony optimization and artificial potential.Length,total turning points and cumulative turning angle of path are almost reduced when smoothing ant colony algorithm is adopted.Path planning problem under different complex environment with different obstacles distribution can be achieved by smoothing ant colony algorithm.

相似文献/References:

[1]赵逢达,孔令富.一种基于图像匹配的闭环检测方法[J].燕山大学学报,2008,(2):115.
 ZHAO Feng-da,KONG Ling-fu.An approach to loop-closing based on images matching[J].Journal of YanShan University,2008,(3):115.

备注/Memo

备注/Memo:
收稿日期:2016-09-09        责任编辑:孙峰
基金项目:天津市科技计划项目(15ZXZNGX00290);天津市农业科技成果转化与推广项目(201203060,201303080)
作者简介:*王红君(1963-),女,天津人,硕士,教授,主要研究方向工业先进控制技术、微机控制、智能控制,Email:hongewang@126.com。
更新日期/Last Update: 2017-07-07