煤矿救援机器人路径平滑算法研究

陶德俊, 姜媛媛, 刘延彬, 辛元芳, 罗俊

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.. DOI: 10.13272/j.issn.1671-251x.2019050069
引用本文: 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.. DOI: 10.13272/j.issn.1671-251x.2019050069
TAO Dejun, JIANG Yuanyuan, LIU Yanbin, XIN Yuanfang, LUO Jun. Research on path smoothing algorithm of coal mine rescue robot[J]. Journal of Mine Automation, 2019, 45(10): 49-54. DOI: 10.13272/j.issn.1671-251x.2019050069
Citation: TAO Dejun, JIANG Yuanyuan, LIU Yanbin, XIN Yuanfang, LUO Jun. Research on path smoothing algorithm of coal mine rescue robot[J]. Journal of Mine Automation, 2019, 45(10): 49-54. DOI: 10.13272/j.issn.1671-251x.2019050069

煤矿救援机器人路径平滑算法研究

基金项目: 

国家自然科学基金项目(51604011)

安徽省自然科学基金项目(1708085QF135)

安徽省高校省级自然科学研究项目(KJ2017A077)

安徽省高校优秀青年骨干人才国内外访学研修项目(gxfx2017025)

安徽省高校自然科学研究项目(KJ2018A0759,KJ2019ZD12)。

详细信息
  • 中图分类号: TD77

Research on path smoothing algorithm of coal mine rescue robot

  • 摘要: 针对煤矿救援机器人利用A*算法规划出来的路径存在转折次数多和路径不够平滑等问题,提出了一种基于改进A*算法的煤矿救援机器人路径平滑算法。首先利用Douglas-Peucker(D-P)算法对A*算法产生的全段路径进行处理,剔除路径中的冗余节点,提取出若干路径节点作为关键节点,解决了A*算法路径冗余节点多、路径转折次数多的问题;然后利用三次样条函数对基于关键节点的整段路径进行拟合处理,得到一条平滑的路径,有效缩短了路径长度。仿真实验结果表明,该算法通用性很强,虽然规划时间与A*算法相比略有增加,但规划出来的路径转折次数少,路径长度短,且路径质量高于遗传平滑算法。
    Abstract: In view of problems that path planning of the coal mine rescue robot planned by A* algorithm has many path turning points and the path is not smooth enough, a path smoothing algorithm of coal mine rescue robot based on improved A* algorithm was proposed. Firstly, the Douglas-Peucker (D-P) algorithm is used to process the whole path generated by A* algorithm, and eliminate redundant nodes in the path, and extracts several path nodes as key nodes, which solves the problem that there are many redundant nodes and a large number of path turning points of the A* algorithm. Then, the whole path based on the key nodes is fitted by cubic path function, and a smooth path is obtained, which can effectively shorten the path length. The simulation results show that the algorithm has strong universality, although the planning time is slightly increased compared with the A* algorithm, but the planned path turns are few, the path length is short, and the path quality is relatively better than that of the genetic smoothing algorithm.
  • 期刊类型引用(8)

    1. 刘明淳,许勇,池永锋,杨权,陈智斌. 基于Chaos-LSTM深度学习网络的边坡变形预测算法. 有色金属(矿山部分). 2025(01): 89-97+123 . 百度学术
    2. 田光,李硕. 露天矿复杂边坡支护关键技术研究与发展. 采矿技术. 2025(02): 171-175 . 百度学术
    3. 杜昌华,宋景辉,李蕊,田涯. 露天煤矿含断层顺倾边坡渗流与稳定性分析. 露天采矿技术. 2024(02): 51-55 . 百度学术
    4. 牛犇,张新伟,周玉,李婧,徐兴全,张一鸣. 基于连续-非连续元降雨工况三维边坡稳定性分析. 山东大学学报(工学版). 2023(01): 92-99 . 百度学术
    5. 刘光伟,郭直清,刘威. 基于GJO-MLP的露天矿边坡变形预测模型. 工矿自动化. 2023(09): 155-166 . 本站查看
    6. 于雷,闫岩,邓巧巧. 基于大数据的矿山边坡稳定性评价模型. 自动化技术与应用. 2022(05): 138-140+174 . 百度学术
    7. 耿佳弟,陈五一,彭志松. 基于离散元的岩土基坑边坡渗流耦合计算仿真. 计算机仿真. 2021(04): 240-243+482 . 百度学术
    8. 苏伟. 露天地下协同开采对矿山地下水渗流场的影响. 采矿技术. 2021(06): 64-68 . 百度学术

    其他类型引用(5)

计量
  • 文章访问数:  91
  • HTML全文浏览量:  14
  • PDF下载量:  19
  • 被引次数: 13
出版历程
  • 刊出日期:  2019-10-19

目录

    /

    返回文章
    返回