工矿自动化2025，Vol.51Issue(3)：78-85,95,9.DOI:10.13272/j.issn.1671-251x.2025010021
基于激光雷达与惯导融合的掘进机定位方法
Positioning method for roadheaders based on fusion of LiDAR and inertial navigation
摘要
Abstract
Accurate positioning of roadheaders in coal mines is fundamental to intelligent tunneling.However,harsh working conditions,such as low illumination and high dust levels in underground mines,often degrade the accuracy and stability of single-source positioning methods.To improve the positioning accuracy of the roadheaders in these harsh conditions,a new positioning method based on the fusion of LiDAR and inertial navigation using error state kalman filter(ESKF)was developed.First,the center of the spherical target suspended from the tunnel roof was defined as the origin of the tunnel coordinate system.A density-based spatial clustering of applications with noise(DBSCAN)and a shape-feature-based spherical target point cloud extraction algorithm were designed to address the problem that conventional methods relying on reflection intensity for distinguishing spherical targets fail in environments with dust accumulation.The coordinate transformation method is then used to build a radar position measurement system to obtain a reference for the fusion positioning.Next,position and attitude information of the roadheader were obtained through inertial navigation integration.Subsequently,an error-state model was formulated based on a first-order Gaussian-Markov process,and the ESKF algorithm was applied to fuse the outputs of LiDAR and the inertial navigation,providing the fusion positioning results of the roadheader within the tunnel.The fusion positioning results were then fed back into the inertial navigation to correct accumulated errors,achieving precise positioning.Experimental results demonstrated that,under static conditions,the position error of the LiDAR-based positioning system remained below 10 cm across different positions and attitude angles,and the inertial navigation system exhibited a position error of less than 70 cm.In dynamic conditions,the fusion positioning system achieved a position error of 5.8 cm,reducing the LiDAR system's error by 12.1％.The proposed LiDAR and inertial navigation fusion-based roadheader positioning method meets the positioning requirements for automated cutting operations of roadheaders in complex tunneling conditions.关键词
掘进机定位/激光雷达/惯导/误差状态卡尔曼滤波/基于密度的噪声鲁棒空间聚类算法/球靶Key words
roadheader positioning/LiDAR/inertial navigation/Error State Kalman Filter/Density-Based Spatial Clustering of Applications with Noise(DBSCAN)/spherical targe分类
矿业与冶金引用本文复制引用
刘京,魏志强,蔡春蒙,刘洋..基于激光雷达与惯导融合的掘进机定位方法[J].工矿自动化,2025,51(3):78-85,95,9.基金项目
陕西省秦创原引用高层次创新创业人才项目(QCYRCXM-2023-094) （QCYRCXM-2023-094）
三一集团2023年重大技术开发项目(8037023). （8037023）
