地下矿山中多传感器融合里程计的研究  

Research on multi-sensor fusion odometry in underground mines

作　　者：张昊晟 聂闻 王运敏[3] 徐修平[3] ZHANG Haosheng;NIE Wen;WANG Yunmin;XU Xiuping(School of Advanced Manufacturing,Fuzhou University,Quanzhou,Fujian 362200,China;Quanzhou Institute of Equipment Manufacturing Haixi Institutes,CAS,Quanzhou,Fujian 362200,China;State Key Laboratory for Safety and Health of Metal Mines,Maanshan,Anhui 243000,China)

机构地区：[1]福州大学先进制造学院,福建泉州362200 [2]中国科学院海西研究院泉州装备制造研究中心,福建泉州362200 [3]金属矿山安全与健康国家重点实验室,安徽马鞍山243000

出　　处：《测绘科学》2023年第9期171-179,共9页Science of Surveying and Mapping

基　　金：国家重点研发计划项目(2021YFC3001300);福建省科学院科学技术合作计划项目(STS,2022T3051)。

摘　　要：针对矿山地下环境中无法使用全球导航卫星系统等设备进行高精度定位,而仅依靠激光雷达进行定位和建图存在困难的问题,该文提出了一种基于IMU、轮式编码器和固态激光雷达紧耦合的里程计算法,该方法将在进行打滑检测后自适应地判断选择使用IMU或编码器的数据预测线性速度,补偿了常规LIO算法中IMU数据会出现累积误差的缺陷。固态激光雷达所适配的先进的LIO算法被用作本文的对比算法,在室内长走廊和尾矿库排洪涵洞中进行了实际测试。结果表明:该文提出的算法在精确度和鲁棒性上均更优,可有效适用于地下矿山的长走廊式环境中。In response to the problem that high-precision positioning cannot be achieved using equipment such as global navigation satellite systems in the underground environment of mines,and relying solely on LiDAR for positioning and mapping is difficult,this paper proposes an odometer algorithm based on tight coupling of IMU,wheel encoder,and solid-state LiDAR.This method will adaptively determine whether to use IMU or encoder data to predict linear speed after slip detection,Compensated for the defect of accumulated errors in IMU data in conventional LIO algorithms.The advanced LIO algorithm adapted to solid-state LiDAR was used as the comparative algorithm in this article,and practical tests were conducted on indoor long corridors and tailings pond flood discharge culverts.The results show that the algorithm proposed in this article is more accurate and robust,and can be effectively applied to the long corridor environment of underground mines.

关 键 词：激光里程计 轮式编码器 打滑检测 地下长走廊 误差状态卡尔曼滤波器 

分 类 号：P237[天文地球—摄影测量与遥感]