基于采煤机工作面端头量测的改进因子图高精度自主定位方法
作者:
作者单位:

1. 南京航空航天大学 自动化学院,南京 210096;2. 湖北航天技术研究院 总体设计所,武汉 430040

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通讯作者:

E-mail: laijz@nuaa.edu.cn.

中图分类号:

TP273

基金项目:

国家自然科学基金项目(61973160);航空科学基金项目(2018ZC52037);工信部民机专项项目(2018-S-36).


High-precision autonomous positioning method based on improved factor graph of measurements at both ends of shearer working face
Author:
Affiliation:

1. Collage of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210096,China;2. Overall Design,Hubei Academy of Spaceflight Technology,Wuhan 430040,China

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    摘要:

    采煤机的高精度定位是煤炭开采自动化和智能化的重要研究方向,其中惯性导航系统和里程计是长壁综合机械化采煤机定位主要传感器之一.通过两者的信息融合,能够有效抑制惯性导航系统的发散并且具有较好的自主导航能力,但是仍然无法满足井下长时间的高精度导航要求.鉴于此,分析目前常用辅助传感器在采煤机开采过程中存在的问题,提出基于UWB采煤机工作面端头量测的改进因子图优化方法.利用UWB在工作面端头的位置量测信息,推导并构建惯导/里程计/UWB的约束方程和图优化模型.同时通过惯性信息的预积分,减少待优化的节点数量,降低算法的计算量.在此基础上,加入里程计标度因数误差和安装误差的因子节点进行联合估计和优化.最后通过仿真和实际跑车测试表明,相较于传统卡尔曼滤波的采煤机定位方式,所提出方法能够有效提高采煤机的定位精度.

    Abstract:

    High-precision positioning of a shearer is an important research direction of automation and intelligence in coal mining. The inertial navigation system and odometer are the main sensors for positioning of the longwall comprehensive mechanized shearer, which can effectively suppress the divergence of the inertial navigation system and has better autonomous navigation ability through information fusion. However, it still cannot meet the requirements of long-term and high-precision navigation. This paper analyzes the existing problems of auxiliary sensors in the mining process of shearer and puts forward an improved factor graph optimization method based on UWB measurement at both ends of the shearer working face. The constraint equation and graph optimization model of the inertial navigation system/ odometer/UWB are derived and constructed by position measurement information of UWB. At the same time, through the pre-integration of inertial information, the number of nodes to be optimized is reduced, thereby reducing the calculation amount of the proposed algorithm. On this basis, the factor nodes of the odometer scale factor error and installation error are added for joint estimation and optimization. Finally, simulation and actual experiments are carried out. The results show that compared with the traditional Kalman filter, the proposed algorithm effectively improves the positioning accuracy of the shearer.

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引用本文

许晓伟,赖际舟,吕品,等.基于采煤机工作面端头量测的改进因子图高精度自主定位方法[J].控制与决策,2022,37(8):2170-2176

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  • 在线发布日期: 2022-06-29
  • 出版日期: 2022-08-20