期刊文献+

基于IMU与单目视觉融合的姿态测量方法 被引量:7

Hybrid Pose Measurement Based on Fusion of IMU and Monocular Vision
下载PDF
导出
摘要 快速准确测量运动目标的姿态,在航天航空、机器人等领域应用广泛.针对惯性姿态测量速度快但精度不足而视觉姿态测量精度高但速度慢的特点,提出了一种基于IMU与单目视觉融合的姿态测量方法.IMU姿态测量时,使用欧拉角迭代公式解算运动目标的姿态;单目视觉姿态测量时,使用POSIT算法求解被测目标的姿态;再使用H?滤波器融合两者的测量结果;用融合结果与惯性测量结果的差值修正并更新漂移误差曲线.根据被测目标的两组匀速转动信息,提出了双矢量正交化标定法标定IMU坐标系到目标坐标系的旋转矩阵;根据单目视觉采集的3幅图像信息,提出了三图快速标定法标定靶标坐标系到目标坐标系的旋转矩阵.实验表明,提出的姿态测量方法能实现快速姿态测量,测量精度高. Quick and accurate object-pose measurement is widely used in aerospace and robot fields.Inertial pose measurement,using Euler angle iteration formula,has an advantage in measuring velocity but suffers from slow drift.In contrast,visual pose measurement based on POSIT algorithm is slow but accurate.This paper proposes a method for measuring attitude by integrating the data from the two types of measurements. H∞ filter is used for fusion.In this paper,Euler drift error curve,caused by the drift of gyroscopic sensor,is corrected and updated according to the difference between the hybrid measurement result and the output of inertial measurement.In order to calibrate the coordinate relationships in pose measurement system,this paper promotes a double-vector orthogonal calibration method and a three-picture fast calibration method.Those methods use the output of IMU and the information from three captured pictures when the object takes a determined rotation.Experimental results show that hybrid pose measurement with fusion resolution is quicker than visual orientation measurement,with higher accuracy.
作者 孙长库 徐怀远 张宝尚 王鹏 郭肖亭 Sun Changku;Xu Huaiyuan;Zhang Baoshang;Wang Peng;Guo Xiaoting(State Key Laboratory of Precision Measuring Technology and Instruments,Tianjin University,Tianjin 300072,China;Science and Technology on Electro-Optic Control Laboratory,Luoyang Institute of Electro-Optic Equipment,AVIC,Luoyang 471009,China)
出处 《天津大学学报(自然科学与工程技术版)》 EI CSCD 北大核心 2017年第3期313-320,共8页 Journal of Tianjin University:Science and Technology
基金 中航工业洛阳电光设备研究所光电控制技术重点实验室和航空科学基金联合资助项目(20145148009)~~
关键词 惯性测量单元 视觉测量 融合 姿态测量 坐标系标定 IMU visual measurement fusion pose measurement coordinate calibration
  • 相关文献

参考文献2

二级参考文献33

  • 1周建军,王秀,张睿,刘刚,马伟,冯青春.农机车载GPS和DR组合导航系统定位方法![J].农业机械学报,2012,43(S1):262-265. 被引量:13
  • 2高为广,封欣,朱大为.基于神经网络构造的GPS/INS自适应组合导航算法[J].大地测量与地球动力学,2007,27(2):64-67. 被引量:14
  • 3王松桂.矩阵不等式[M].北京:科学出版社.2006:33-36.
  • 4FAKHARIAN A,GUSTAFSSON T,MEHRFAM M.Adaptive Kalman filtering based navigation:An IMU/ GPS integration approach[C].International Conference on Networking,Sensing and Control,Delft,the Netherlands,2011.
  • 5BISTROVS V,KIUGA A.MEMS INS/GPS data fusion using particle filter[J].Elektronika Ir Elektrotechnika,2011(6):77-80.
  • 6GEORGY J,NOURELDIN A.Tightly coupled low lost 3D RISS/GPS integration using a mixture particle filter for vehicular navigation[J].Sensors,2011,11(4):4244-4276.
  • 7WANG J H,GAO Y.Land vehicle dynamics-aided inertial navigation[J].Transactions on Aerospace and Electronic Systems,2010,46(4):1638-1653.
  • 8DAI H,LI J X,JIN H M.Application of robust kalman filtering to integrated navigation based on inertial navigation system and dead reckoning[C].International Conference on Artificial Intelligence and Computational Intelligence,Sanya,2010.
  • 9辜道威,程鹏飞,蔡艳辉,等.基于鲁棒滤波的GPS/INS组合导航算法研究[C].大地测量学术年会暨第六届全国大地测量研究生学术论坛,淄博,2011.
  • 10Perry K A, Enestvedt C K, Diggs B S, et al. Perioperative outcomes of laparoscopic transhiatal inversion esophageetomy compare favorably with those of combined thoracoscopic laparoseopic esophageetomy [C]. Surg Endose, 2009, 23 (9) : 2147-2154.

共引文献30

同被引文献54

引证文献7

二级引证文献21

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部