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昆明冶金高等专科学校学报 ›› 2023, Vol. 39 ›› Issue (6): 55-.DOI: 10.3969/j.issn.1009-0479.2023.06.009

• 电子信息技术 • 上一篇    下一篇

基于改进的 Diikstra 无人驾驶铲运机导航路径规划算法的研究#br#

尹业华,李云财,李平   

  1. (云南昆钢电子信息科技有限公司,云南昆明650300)
  • 收稿日期:2023-09-14 出版日期:2023-12-02 发布日期:2024-03-12
  • 作者简介:尹业华 (1976-),男,湖北仙桃人,高级工程师,工学学士,主要从事嵌入式系统研究、自动化智能化技术研发与技术团队管理。

Research on Navigation Path Planning Algorithm for Unmanned Shovel Loaders Based on Improved Dijkstra

YIN Yehua, Ll Yuncai, Ll Ping   

  1. ( Yunnan Kunming lron and Steel Electronie Information Technology Co. , Ltd. , Kunming 650300, China)
  • Received:2023-09-14 Online:2023-12-02 Published:2024-03-12

摘要: 为开发一种改进的 Diksta 算法,以优化井下矿山环境中无人铲运机的导航路径规划,在传统的 Dijkstura算法中,通过不断选择距离起点最近的未访问节点来生成最短路径树。然而,在井下矿山环境中,还需要考虑地形、矿物质分布、安全等因素。推导新的运动学模型并应用到算法中,能够提供更安全、高效的路径规划。案例研究展示了改进的 Diikstra 算法在井下矿山导航中的有效性和应用潜力。

关键词: 无人驾驶, 路径规划, 运动学模型

Abstract: This study aims to develop an enhanced Dijkstra algorithm to optimize navigation path planningfor unmanned shovel loaders in underground mining environments. In the traditional Dijkstra algorithmthe shortest path tree is generated by continuously selecting the nearest unvisited node from the startingpoint. However, in underground mining environments, additional factors need to be considered, such asterrain, mineral distribution, and safety factors. By deriving a new kinematic model and incorporating itinto the algorithm , the improved algorithm can provide safer and more eficient path planning. Throughpractical case studies, this paper demonstrates the efectiveness and potential applications of the enhancedDijkstra algorithm in underground mining navigation.

Key words: unmanned driving, path planning, kinematic model

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