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改进遗传算法在移动机器人路径规划中的应用研究

王雷 李明 蔡劲草 刘志虎

王雷, 李明, 蔡劲草, 刘志虎. 改进遗传算法在移动机器人路径规划中的应用研究[J]. 机械科学与技术, 2017, 36(5): 711-716. doi: 10.13433/j.cnki.1003-8728.2017.0509
引用本文: 王雷, 李明, 蔡劲草, 刘志虎. 改进遗传算法在移动机器人路径规划中的应用研究[J]. 机械科学与技术, 2017, 36(5): 711-716. doi: 10.13433/j.cnki.1003-8728.2017.0509
Wang Lei, Li Ming, Cai Jingcao, Liu Zhihu. Research on Mobile Robot Path Planning by using Improved Genetic Algorithm[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(5): 711-716. doi: 10.13433/j.cnki.1003-8728.2017.0509
Citation: Wang Lei, Li Ming, Cai Jingcao, Liu Zhihu. Research on Mobile Robot Path Planning by using Improved Genetic Algorithm[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(5): 711-716. doi: 10.13433/j.cnki.1003-8728.2017.0509

改进遗传算法在移动机器人路径规划中的应用研究

doi: 10.13433/j.cnki.1003-8728.2017.0509
基金项目: 

国家自然科学基金项目(51305001)、安徽省自然科学基金项目(1708085ME129)及安徽省高校优秀青年人才支持计划重点项目(gxyqZD2016125)资助

详细信息
    作者简介:

    王雷(1982-),副教授,博士,研究方向为作业车间调度、智能优化算法和机器人路径规划,wangdalei2000@126.com

Research on Mobile Robot Path Planning by using Improved Genetic Algorithm

  • 摘要: 针对基本遗传算法解决移动机器人路径规划问题存在收敛速度慢等不足,对遗传算法进行了改进,提出了一种改进自适应遗传算法。根据进化过程中个体适应度值的大小自动调节交叉概率和变异概率,从而使算法能够跳出局部最优解,克服早熟的缺点。同时采用栅格法对机器人工作空间进行建模。对移动机器人路径规划进行仿真实验,对比结果表明:该改进的遗传算法是有效可行的,能够有效的提高机器人路径规划的质量。
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出版历程
  • 收稿日期:  2015-09-23
  • 刊出日期:  2017-05-05

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