Efficient and accurate mapping method of underground metal mines using mobile mining equipment and solid-state lidar

Aiming at the problems of difficult sampling of environmental data, low efficiency, and accuracy of mapping in underground metal mines, this research uses remote control mobile mining equipment, solid-state lidar, and IMU as the hardware system to build an efficient mapping system for underground metal mines. A voxel grid-based point cloud processing method for solid-state lidar is proposed, which can extract planar features and segment ground point clouds more efficiently. An improved point-to-plane matching method is proposed, which can improve the matching efficiency and obtain more accurate matching results. The ground point cloud is added to the sliding window optimization as a constraint, which overcomes the problem of large vertical error in the process of drawing. Through multiple sets of experiments and comparisons with multiple methods, the results show that the errors, vertical drifts, and mapping efficiency of the proposed method are the best among the above methods.