[1]王 雷,李 明.改进自适应遗传算法在移动机器人路径规划中的应用[J].南京理工大学学报(自然科学版),2017,41(05):627.[doi:10.14177/j.cnki.32-1397n.2017.41.05.015]
 Wang Lei,Li Ming.Application of improved adaptive genetic algorithmin mobile robot path planning[J].Journal of Nanjing University of Science and Technology,2017,41(05):627.[doi:10.14177/j.cnki.32-1397n.2017.41.05.015]
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改进自适应遗传算法在移动机器人路径规划中的应用()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年05期
页码:
627
栏目:
出版日期:
2017-10-31

文章信息/Info

Title:
Application of improved adaptive genetic algorithmin mobile robot path planning
文章编号:
1005-9830(2017)05-0627-07
作者:
王 雷李 明
安徽工程大学 机械与汽车工程学院,安徽 芜湖 241000
Author(s):
Wang LeiLi Ming
School of Mechanical and Automotive Engineering,Anhui Polytechnic University,Wuhu 241000,China
关键词:
自适应遗传算法 路径规划 移动机器人 人工势场
Keywords:
adaptive genetic algorithm path planning mobile robots artificial potential field
分类号:
TP242
DOI:
10.14177/j.cnki.32-1397n.2017.41.05.015
摘要:
为了克服基本遗传算法在求解移动机器人路径规划问题中存在的收敛速度慢、易陷入局部最优等不足,该文提出了一种改进的自适应遗传算法。采用人工势场法对种群进行初始化,设计了自适应交叉和变异概率。同时,采用混合选择方式改善了基本遗传算法收敛速度慢和早熟的现象,提高了算法的进化效率。栅格环境下的仿真实验证明了该文算法在移动机器人路径规划中的可行性和有效性。
Abstract:
In order to deal with the problem of the slow convergence speed and local optima of the basic genetic algorithm(GA)in solving the robot path planning,an improved adaptive genetic algorithm(IGA)is proposed here.An artificial potential field method is employed to create the initial population,and the adaptive crossover probability and the mutation probability are designed.Meanwhile,a hybrid selection method is adopted to improve the convergence speed and the evolutionary efficiency and overcome the premature phenomenon of the basic genetic algorithm obviously.Some experiments under the grid environment verify the feasibility and effectiveness of the improved adaptive genetic algorithm in mobile robot path planning.

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 SHEN Xiao-ning,GUO Yu,CHEN Qing-wei,et al.Application of Multi-objective Optimization Genetic Algorithm to Robot Path Planning[J].Journal of Nanjing University of Science and Technology,2006,(05):659.

备注/Memo

备注/Memo:
收稿日期:2016-07-18 修回日期:2016-09-04

基金项目:国家自然科学基金(51305001); 安徽省自然科学基金(1708085ME129); 安徽省科技攻关项目(1604A0902183); 安徽省高校优秀青年人才支持计划重点项目(gxyqZD2016125)
作者简介:王雷(1982-),男,博士,副教授,主要研究方向:作业车间调度、机器人路径规划及智能优化算法,E-mail:wangdalei2000@126.com。
引文格式:王雷,李明.改进自适应遗传算法在移动机器人路径规划中的应用[J].南京理工大学学报,2017,41(5):627-633.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-09-30