基于16方向24邻域改进蚁群算法的移动机器人路径规划
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(1. 西南交通大学交通运输与物流学院,成都611756;2. 西南交通大学综合交通运输智能化国家地方联合工程实验室,成都611756;3. 重庆交通大学机电与车辆工程学院,重庆400074)

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E-mail: xl_xnjd@163.com.

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TP242.6

基金项目:

四川省软科学研究项目(2019JDR0186).


Mobile robots path planning based on 16-directions 24-neighborhoods improved ant colony algorithm
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(1. School of Transportation and Logistics,Southwest Jiaotong University,Chengdu611756,China;2. National and Combined Engineering Lab of Intelligentizing Integrated Transportation,Southwest Jiaotong University,Chengdu 611756,China;3. School of Mechatronics and Vehicle Engineering,Chongqing Jiaotong University,Chongqing400074,China)

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    摘要:

    为了提高蚁群算法的路径寻优效果和搜索效率,提出一种改进的蚁群算法,用于移动机器人在栅格环境下的路径规划.在标准蚁群算法中,蚂蚁的搜索方式一般是4方向4邻域或者8方向8邻域,在此基础上提出一种16方向24邻域的蚂蚁搜索方式,给出蚂蚁的移动规则;针对启发信息,结合向量夹角的思想设计2种启发信息的计算方法,通过实验分析两种计算方法的使用特点;在转移概率部分引入转移概率控制参数,通过调整转移概率控制参数可以调控算法的搜索范围.最后,在不同规模的栅格地图环境下,通过实验仿真验证所提算法的有效性.

    Abstract:

    To improve the path optimization effect and search efficiency of ant colony algorithms, an improved ant colony algorithm for the path planning of mobile robots under the grid map environment is proposed. In traditional ant colony algorithms, ants generally search 4 directions, 4 neighborhoods or 8 directions, 8 neighborhoods. Based on that, this paper proposes am improved search method for ants to search 16 directions and 24 neighborhoods, and also shows the mobile rules of ants. For heuristic information, we combine the idea of vector angle to design two methods to calculate heuristic information, and also analyze the application characteristics of those two methods through experiments. In the transfer probability part, we introduce the transfer probability control parameters. The search range of the algorithm can be adjusted by adjusting the transfer probability control parameters. Finally, the simulation experiments under grid map environments with different scales verify the effectiveness of the improved ant colony algorithm.

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徐菱,付文浩,江文辉,等.基于16方向24邻域改进蚁群算法的移动机器人路径规划[J].控制与决策,2021,36(5):1137-1146

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  • 在线发布日期: 2021-04-08
  • 出版日期: 2021-05-20
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