留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于改进概率路线图算法的煤矿机器人路径规划方法

薛光辉 刘爽 王梓杰 李亚男

薛光辉,刘爽,王梓杰,等. 基于改进概率路线图算法的煤矿机器人路径规划方法[J]. 工矿自动化,2023,49(6):175-181.  doi: 10.13272/j.issn.1671-251x.18116
引用本文: 薛光辉,刘爽,王梓杰,等. 基于改进概率路线图算法的煤矿机器人路径规划方法[J]. 工矿自动化,2023,49(6):175-181.  doi: 10.13272/j.issn.1671-251x.18116
XUE Guanghui, LIU Shuang, WANG Zijie, et al. A path-planning method for coal mine robot based on improved probability road map algorithm[J]. Journal of Mine Automation,2023,49(6):175-181.  doi: 10.13272/j.issn.1671-251x.18116
Citation: XUE Guanghui, LIU Shuang, WANG Zijie, et al. A path-planning method for coal mine robot based on improved probability road map algorithm[J]. Journal of Mine Automation,2023,49(6):175-181.  doi: 10.13272/j.issn.1671-251x.18116

基于改进概率路线图算法的煤矿机器人路径规划方法

doi: 10.13272/j.issn.1671-251x.18116
基金项目: 国家自然科学基金面上项目(51874308);国家重点基础研究发展计划(973计划)项目(2014CB046306)。
详细信息
    作者简介:

    薛光辉(1977—),男,河南汝州人,副教授,博士,主要研究方向为煤矿机器人、煤矿设备自动化与智能化、设备状态检测与健康诊断、无线传感器网络等,E-mail:xgh@cumtb.edu.cn

  • 中图分类号: TD67

A path-planning method for coal mine robot based on improved probability road map algorithm

  • 摘要: 路径规划是煤矿机器人在煤矿井下非结构化狭长受限空间中应用亟待解决的关键技术之一。针对传统概率路线图(PRM)算法在空间狭长封闭巷道环境中难以保障采样的节点均匀分布于自由空间中导致路径规划失效,以及节点可能距离障碍物较近导致规划的路径可通行性差等问题,提出了一种基于改进PRM算法的煤矿机器人路径规划方法。在构造阶段引入人工势场法,将落在障碍物中的节点沿与其距离最近自由空间中的节点连线方向推至自由空间,并在障碍物边缘建立斥力场,实现节点的均匀分布且使其距离障碍物有一定距离;在查询阶段融合D* Lite算法,当遇到动态障碍物或前方无法通行时可实现路径的重规划。仿真结果表明:改进PRM算法的节点均匀分布在自由空间中,且均距离障碍物一定距离,提高了路径规划的安全性;当节点数为100个时,改进PRM算法成功率较传统PRM算法提高了25%;随着节点数增加,传统PRM算法和改进PRM算法路径规划成功次数均呈增长趋势,但改进PRM算法在效率方面优势更明显;当节点数为400个时,改进PRM算法运行效率较传统PRM算法提高了35.13%,且规划的路径更平滑,路径长度更短;当障碍物突然出现时,改进PRM算法能够实现路径的重规划。

     

  • 图  1  实验场景

    Figure  1.  Experiment scenes

    图  2  节点分布

    Figure  2.  Nodes distribution

    图  3  采样100个节点时路径规划结果

    Figure  3.  Path planning results when sampling 100 nodes

    图  4  采样200个节点时路径规划结果

    Figure  4.  Path planning results when sampling 200 nodes

    图  5  采样200个节点时路径重规划结果

    Figure  5.  Path re-planning result when sampling 200 nodes

    表  1  不同节点数量时改进前后PRM算法路径规划结果统计

    Table  1.   Path planning results statistics of probabilistic road map algorithm before and after improvement with different number of sampling nodes

    算法节点
    数/个
    成功
    次数
    运行
    时间/s
    路径
    长度/m
    转折点
    数/个
    路径数
    量/条
    传统PRM算法100103.14420.35104
    200309.78390.3983
    3006114.09381.0972
    40010029.92372.7861
    改进PRM算法100352.63400.9363
    200665.13382.6452
    300979.87372.4641
    40010019.41369.5741
    下载: 导出CSV
  • [1] 周李兵. 煤矿井下无轨胶轮车无人驾驶系统研究[J]. 工矿自动化,2022,48(6):36-48.

    ZHOU Libing. Research on unmanned driving system of underground trackless rubber-tyred vehicle in coal mine[J]. Journal of Mine Automation,2022,48(6):36-48.
    [2] 薛光辉,候称心,张云飞,等. 煤矿巷道修复重载作业机器人现状与发展趋势[J]. 工矿自动化,2020,46(9):8-14.

    XUE Guanghui,HOU Chenxin,ZHANG Yunfei,et al. Current situation and development trend of heavy-duty operation robot for coal mine roadway repair[J]. Industry and Mine Automation,2020,46(9):8-14.
    [3] 袁晓明,郝明锐. 煤矿辅助运输机器人关键技术研究[J]. 工矿自动化,2020,46(8):8-14.

    YUAN Xiaoming,HAO Mingrui. Research on key technologies of coal mine auxiliary transportation robot[J]. Industry and Mine Automation,2020,46(8):8-14.
    [4] 金祖进,程刚,郭锋,等. 煤矿搜救机器人最优路径规划算法[J]. 工矿自动化,2018,44(10):24-28.

    JIN Zujin,CHENG Gang,GUO Feng,et,al. Optimal path planning algorithm for coal mine search and rescue robot[J]. Industry and Mine Automation,2018,44(10):24-28.
    [5] 王国法,赵国瑞,任怀伟. 智慧煤矿与智能化开采关键核心技术分析[J]. 煤炭学报,2019,44(1):34-41.

    WANG Guofa,ZHAO Guorui,REN Huaiwei. Analysis on key technologies of intelligent coal mine and intelligent mining[J]. Journal of China Coal Society,2019,44(1):34-41.
    [6] 葛世荣,胡而已,李允旺. 煤矿机器人技术新进展及新方向[J]. 煤炭学报,2023,48(1):54-73. doi: 10.13225/j.cnki.jccs.2022.1661

    GE Shirong,HU Eryi,LI Yunwang. New progress and direction of robot technology in coal mine[J]. Journal of China Coal Society,2023,48(1):54-73. doi: 10.13225/j.cnki.jccs.2022.1661
    [7] 田子建,高学浩,张梦霞. 基于改进人工势场的矿井导航装置路径规划[J]. 煤炭学报,2016,41(增刊2):589-597.

    TIAN Zijian,GAO Xuehao,ZHANG Mengxia. Path planning based on the improved artificial potential field of coal mine dynamic target navigation[J]. Journal of China Coal Society,2016,41(S2):589-597.
    [8] GAO Yongxin,DAI Zhonglin,YUAN Jing. A multiobjective hybrid optimization algorithm for path planning of coal mine patrol robot[J]. Computational Intelligence and Neuroscience,2022,2022:9094572. DOI: 10.1155/2022/9094572.
    [9] SONG Baoye,MIAO Huimin,XU Lin. Path planning for coal mine robot via improved ant colony optimization algorithm[J]. Systems Science & Control Engineering,2021,9(1):283-289.
    [10] 陶德俊,姜媛媛,刘延彬,等. 煤矿救援机器人路径平滑算法研究[J]. 工矿自动化,2019,45(10):49-54.

    TAO Dejun,JIANG Yuanyuan,LIU Yanbin,et al. Research on path smoothing algorithm of coal mine rescue robot[J]. Industry and Mine Automation,2019,45(10):49-54.
    [11] MAO Ruiqing,MA Xiliang. Research on path planning method of coal mine robot to avoid obstacle in gas distribution area[J]. Journal of Robotics,2016,2016:120-125.
    [12] 鲍久圣,张牧野,葛世荣,等. 基于改进A*和人工势场算法的无轨胶轮车井下无人驾驶路径规划[J]. 煤炭学报,2022,47(3):1347-1360.

    BAO Jiusheng,ZHANG Muye,GE Shirong,et al. Underground driverless path planning of trackless rubber tyred vehicle based on improved A* and artificial potential field algorithm[J]. Journal of China Coal Society,2022,47(3):1347-1360.
    [13] 代嘉惠. 大功率本安驱动煤矿救援机器人定位与建图算法研究[D]. 重庆: 重庆大学, 2019.

    DAI Jiahui. Study on localization and mapping algorithm of high-power intrinsically safe coal mine rescue robot[D]. Chongqing: Chongqing University, 2019.
    [14] 金书奎,寇子明,吴娟. 煤矿水泵房巡检机器人路径规划与跟踪算法的研究[J]. 煤炭科学技术,2022,50(5):253-262.

    JIN Shukui,KOU Ziming,WU Juan. Research on path planning and tracking algorithm of inspection robot in coal mine water[J]. Coal Science and Technology,2022,50(5):253-262.
    [15] 田洪清,王建强,黄荷叶,等. 越野环境下基于势能场模型的智能车概率图路径规划方法[J]. 兵工学报,2021,42(7):1496-1505. doi: 10.3969/j.issn.1000-1093.2021.07.017

    TIAN Hongqing,WANG Jianqiang,HUANG Heye,et al. Probabilistic roadmap method for path planning of intelligent vehicle based on artificial potential field model in off-road environment[J]. Acta Armamentarii,2021,42(7):1496-1505. doi: 10.3969/j.issn.1000-1093.2021.07.017
    [16] SULAIMAN S,SUDHEER A P. Modeling of a wheeled humanoid robot and hybrid algorithm-based path planning of wheel base for the dynamic obstacles avoidance[J]. Industrial Robot,2022,49(6):1058-1076. doi: 10.1108/IR-12-2021-0298
    [17] KAVRAKI L E,SVESTKA P,LATOMBE J C,et al. Probabilistic roadmaps for path planning in high-dimensional configuration spaces[J]. IEEE Transactions on Robotics and Automation,1996,12(4):566-580. doi: 10.1109/70.508439
    [18] KHATIB O. Real-time obstacle avoidance for manipulators and mobile robots[J]. The International Journal of Robotics Research,1986,5(1):90-98. doi: 10.1177/027836498600500106
    [19] 杨奇峰,曲道奎,徐方. 基于障碍物运动预测的移动机器人路径规划[J]. 计算机工程与设计,2021,42(1):182-188. doi: 10.16208/j.issn1000-7024.2021.01.027

    YANG Qifeng,QU Daokui,XU Fang. Path planning of mobile robot based on obstacle motion prediction[J]. Computer Engineering and Design,2021,42(1):182-188. doi: 10.16208/j.issn1000-7024.2021.01.027
    [20] 杜轩,欧资臻. 改进D* Lite和人工势场法的移动机器人路径规划研究[J]. 制造业自动化,2022,44(2):153-158.

    DU Xuan,OU Zizhen. Research on the path planning of mobile robots to improve the method of D* Lite and artificial potential field[J]. Manufacturing Automation,2022,44(2):153-158.
    [21] KOENIG S, LIKHACHEV M. D* lite[C]. AAAI Conference on Artificial Intelligence, Palo Alto, 2002: 476-483.
    [22] 周非同. 室内移动机器人导航系统研究与设计[D]. 合肥: 中国科学技术大学, 2019.

    ZHOU Feitong. Research and design of indoor mobile robot's navigation system[D]. Hefei: University of Science and Technology of China, 2019.
    [23] 黄鲁,周非同. 基于路径优化D* Lite算法的移动机器人路径规划[J]. 控制与决策,2020,35(4):877-884.

    HUANG Lu,ZHOU Feitong. Path planning of moving robot based on path optimization of D* Lite algorithm[J]. Control and Decision,2020,35(4):877-884.
  • 加载中
图(5) / 表(1)
计量
  • 文章访问数:  950
  • HTML全文浏览量:  24
  • PDF下载量:  25
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-05-08
  • 修回日期:  2023-06-25
  • 网络出版日期:  2023-07-04

目录

    /

    返回文章
    返回