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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:

2015年01期

Page:

81-

Research Field:

计算机科学

Publishing date:

Info

Title:

Research on Global Path Planning for Mobile Robot Based onImproved Ant Colony Optimization Algorithm

Author(s):

Qu Zhenggeng¹; Yang Chuan²

(1.School of Mathematics and Computer Application,Shangluo University,Shangluo 726000,China)(2.School of Electronic Information and Automation,Chongqing University of Technology,Chongqing 400054,China)

Keywords:

mobile robot; path planning; modeling; Ant-cycle model; automatic adaptation

PACS:

TP242

DOI:

-

Abstract:

Analysis of the principle of ant colony algorithm trajectory planning,robot,the grid environment model for trajectory planning of robot trajectory planning,and environment model is discussed and analyzed. An adaptive ant colony algorithm based on improved ant colony algorithm was proposed; and the adaptive ant colony algorithm parameters were corrected by simulation results to prove the superiority,feasibility of the improved ant colony algorithm.

References:

[1] 赵金龙,曹雷,郭锐. 基于ADAMS的输电线路移动机器人越障仿真[J]. 计算机应用与软件,2012,29(4):59-63
[2]陈祥章. 基于单目视觉的机器人人工势场法路径规划研究[J]. 南京师大学报:自然科学版,2014,37(1):61-66.
[3]王梅,王叶婷,屠大维. 基于混合势场法的移动机器人路径规划[J]. 计算机应用研究,2012,29(7):2 447-2 450.
[4]Dorigo M,Maniezzo V,Colorni V. The ant system:optimization by a colony of cooperating agents[J]. IEEE Transactions on Systems,Man,and Cybernetics Part B,2006,26,ZX:29-41.
[5]朱东伟,毛晓波,陈铁军. 基于改进粒子群三次Bezier曲线优化的路径规划[J]. 计算机应用研究,2012,29(5):1 710-1 713.
[6]张彪,曹其新,王雯珊. 使用三维栅格地图的移动机器人路径规划[J]. 西安交通大学学报:自然科学版,2013,47(10):57-62.
[7]李方洁,刘希玉,陈洁. 基于改进蚁群算法的DNA双序列比对[J]. 南京师大学报:自然科学版,2010,33(4):148-152.
[8]张琦,马家辰,谢玮. 基于改进蚁群算法的移动机器人路径规划[J]. 东北大学学报:自然科学版,2013,34(11):109-114.
[9]李琳,任俊霖,邹焱飚. 基于免疫遗传算法的移动机器人轨迹跟踪[J]. 华南理工大学学报:自然科学版,2013,41(7):13-19.
[10]陈卫东,朱奇光. 基于模糊算法的移动机器人路径规划[J]. 电子学报,2011,39(4):971-975.

Memo

Memo:

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Common functions

Last Update: 2015-03-30