摘要
为满足煤矿对掘进机位姿精确感知的要求,提出了一种捷联惯导与双目里程计融合的掘进机组合定位方法,该方法是在捷联惯导的基础上,引入双目里程计作为辅助定位系统,以减小捷联惯导累计误差对掘进机定位精度的影响。设计了具有15维状态量的卡尔曼滤波器,用于融合捷联惯导与双目里程计的数据,并以输出校正的方式对捷联惯导进行误差校正。为验证组合定位算法的精度与可靠性,搭建了试验平台,并进行了组合定位试验,组合定位在北向、东向与天向的位移最大误差分别为3.39 cm、31.15 cm与1.65 cm,横滚角、航向角与俯仰角的最大误差分别为0.1356°、0.8290°与1.2200°。试验结果表明,组合定位方法能够有效减小捷联惯导累计误差的影响,实现掘进机高精度定位。
In order to mcct thc rcquiremcnt of position and attitude awarcncss of roadheader in mines,an intcgratcd positioning method of roadheader based on fusion of SINS and binocular odometer was proposed."The idea of this method is to introduce binocular odometer as an auxiliary positioning system based on SINS to reduce the influence of cumulative SINS errors on the positioning accuracy of roadhcader.A Kalman filter with 15-dimcnsional state volumec was designcd to fusc SINS with binocular odometer data and correct for SINS error with an output correction.To verily the accuracy and reliability of the integrated positioning method,an experimental platform was built and integrated positioning experiments were conducted.The maximum errors of integrated positioning in northward,castward and skyward displacements arc 0.0339 m,0.3115 m and 0.0165 m,respectively,and the maximum errors of roll angle,heading angle and pitch angle are 0.1356°,0.8290°and 1.2200°,rcspcctivcly.Thc cxpcrimcntal rcsults show that thc proposcd intcgrated positioning mcthod can cffcctivcly wcakcn thc cumulative SINS errors and achieve a high accuracy positioning ofl the roadheader.
作者
金铃子
王浩然
李正龙
JIN Lingzi;WANG Haoran;LI Zhengong(Lu'an Chemical Group Co.,Ltd.,Changzhi,Shanxi 046204,China;Beijing Tianma Intelligent Control Technology Co.,Ltd.,Beijing 101399,China;Ccntcr of Shanxi Enginccring Rescarch for Coal Minc Intelligcnt Equipment,Taiyuan University of Technology,Taiyuan,Shanxi 030024,China)
出处
《矿业研究与开发》
CAS
北大核心
2023年第12期171-177,共7页
Mining Research and Development
基金
山西省科技计划揭榜招标项目(20201101005,20201101008)。
关键词
掘进机
位姿感知
捷联惯导
双目里程计
卡尔曼滤波
组合定位
Roadheader
Position and attitude awarcncss
Strapdown Incrtial Navigation System(SINS)
Binocular odomcter
Kalman filtcr
Intcgrated positioning