基于改进的Dijkstra无人驾驶铲运机导航路径规划算法的研究  

Research on Navigation Path Planning Algorithm forUnmanned Shovel Loaders Based on Improved Dijkstra

作　　者：尹业华 李云财 李平 YIN Yehua;LI Yuncai;LI Ping(Yunnan Kunming Iron and Steel Electronic Information Technology Co.,Ltd.,Kunming 650300,China)

机构地区：[1]云南昆钢电子信息科技有限公司,云南昆明650300

出　　处：《昆明冶金高等专科学校学报》2023年第6期55-61,106,共8页Journal of Kunming Metallurgy College

摘　　要：为开发一种改进的Dijkstra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Dijkstra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Dijkstra算法在井下矿山导航中的有效性和应用潜力。This study aims to develop an enhanced Dijkstra algorithm to optimize navigation path planning for unmanned shovel loaders in underground mining environments.In the traditional Dijkstra algorithm,the shortest path tree is generated by continuously selecting the nearest unvisited node from the starting point.However,in underground mining environments,additional factors need to be considered,such as terrain,mineral distribution,and safety factors.By deriving a new kinematic model and incorporating it into the algorithm,the improved algorithm can provide safer and more efficient path planning.Through practical case studies,this paper demonstrates the effectiveness and potential applications of the enhanced Dijkstra algorithm in underground mining navigation.

关 键 词：无人驾驶 路径规划 运动学模型 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]