基于激光点云的矿用无人运输车路径规划研究

Research on path planning for unmanned mining transportation vehicle based on laser point cloud

随着无人驾驶技术应用于矿山运输车,其作业的安全问题得到不断改善。由于地下矿道道路复杂,需进行巷道感知和路径规划,在使用激光雷达扫描区域地形的基础上,设计了地下矿车的路径规划算法,来确保无人运输车的安全运行。仿真试验中,在确定激光点云形成的巷道边界线后,通过算法得出规划路径,随后通过计算预瞄点与原点之间的横向位移误差与航向角误差来控制车辆。数据结论表明,该算法可将最大横向位移误差控制在0.30m内,最大航向角误差控制在0.03rad,满足平滑行驶的要求。

With the application of unmanned driving technology in mining transportation vehicles,the safety of its operations has been continuously improved.Due to the complexity of underground mine roads,roadway perception and path planning were needed.Based on the terrain area scanning by the laser radar,the path planning algorithm of the underground mining vehicle was designed,which could realize the safe operation of the unmanned mining vehicle.In the simulation test,after the boundary line of the roadway formed by the laser point cloud was determined,the planning path was obtained by the algorithm,and the lateral position error and heading angle error between the preview point and the origin point were calculated to control the vehicle.The data conclusion showed that the maximum lateral displacement error could be controlled within 0.30 m,and the maximum heading angle error could be controlled within 0.03 rad,which met the requirements of smooth driving.