一种单目视觉位姿测量系统的误差分析方法
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摘要
针对单目视觉位姿测量传统误差分析方法中只考虑单一误差因素,分析结果与工程实际有较大差异的问题,提出一种考虑多误差因素共同作用的误差分析方法。根据单目视觉系统的测量范围和相机参数建立其位姿测量模型;综合考虑相机内参、镜头畸变、图像点、靶标三维点等误差因素,将其同时引入位姿测量模型进行分析;分析抑制不同参数误差及提高相机分辨率等在多误差因素共同作用下对位姿测量结果的影响,找到最有效的精度优化方法。采用小型机械臂手眼定位中的单目视觉位姿测量系统进行实验,结果表明通过抑制相机径向畸变误差和提高相机分辨率,能够有效地提升该系统的位姿测量精度,位姿精度分别提升6.57%、4.21%和5.88%、5.54%。
The traditional error analysis of monocular vision pose measurement only considers a single error factor,which causing the problem that there is a large difference from the actual project.An error analysis method considering multiple error factors was proposed.Firstly,a pose estimation model for monocular vision was established based on the measurement range and camera parameter.Secondly,the camera internal error,lens distortion error,image points detection error and target error were introduced into the measurement model simultaneously based on actual error levels.Finally,the influence of suppressing parameter errors,improving camera resolution on the pose measurement results were obtained,and the most effective precision optimization method was found.In addition,a monocular vision pose measurement system for small manipulator hand-eye location was adopted for experiment.The analysis results indicate that reducing the radial distortion error and improving the camera resolution can effectively improve both the position and attitude measurement accuracy of this system.The pose accuracy is increased by 6.57%,4.21%and 5.88%,5.54%,respectively.
The traditional error analysis of monocular vision pose measurement only considers a single error factor,which causing the problem that there is a large difference from the actual project.An error analysis method considering multiple error factors was proposed.Firstly,a pose estimation model for monocular vision was established based on the measurement range and camera parameter.Secondly,the camera internal error,lens distortion error,image points detection error and target error were introduced into the measurement model simultaneously based on actual error levels.Finally,the influence of suppressing parameter errors,improving camera resolution on the pose measurement results were obtained,and the most effective precision optimization method was found.In addition,a monocular vision pose measurement system for small manipulator hand-eye location was adopted for experiment.The analysis results indicate that reducing the radial distortion error and improving the camera resolution can effectively improve both the position and attitude measurement accuracy of this system.The pose accuracy is increased by 6.57%,4.21%and 5.88%,5.54%,respectively.
引文
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[4]HU Z Y,WU F C.A note on the number of solu-tions of the noncoplanar P4P problem[J].IEEETransactions on Pattern Analysis and Machine Intel-ligence,2002,24(4):550-555.
[5]NISTER D.An efficient solution to the five-pointrelative pose problem[J].IEEE Transactions on Pat-tern Analysis and Machine Intelligence,2004,26(6):756-770.
[6]ZHANG S J,CAO X B,ZHANG F,et al.Monocu-lar vision-based iterative pose estimation algorithmfrom corresponding feature points[J].Science China-Information Sciences,2010,53(8):1682-1696.
[7]KAMGER-PARSI B.Evaluation of quantization er-ror in computer vision[J].Pattern Analysis &Ma-chine Intelligence IEEE Transactions on,1989,11(9):929-940.
[8]HUO Ju,CUI Jiashan,WANG Weixing.Error a-nalysis of monocular visual position measurementbased on coplanar feature points[J].Acta PhotonicaSinica,2014,43(5):144-150.霍炬,崔家山,王伟兴.基于共面特征点的单目视觉位姿测量误差分析[J].光子学报,2014,43(5):144-150.
[9]ZHOU Jing,HAO Yingming,ZHU Feng,et al.In-fluence of the error of camera parameters on the accu-racy of pose measurement[J].Chinese Journal of Sci-entific Instrument,2007,28(8):568-572.周静,郝颖明,朱枫,等.摄像机标定参数误差对位姿测量精度的影响[J].仪器仪表学报,2007,28(8):568-572.
[10]HAO Yingming,ZHU Feng,OU Jinjun,et al.Er-ror analysis of P3Ppose estimation[J].ComputerEngineering and Application, 2008.44(18):239-242.郝颖明,朱枫,欧锦军,等.P3P位姿测量方法的误差分析[J].计算机工程与应用,2008,44(18):239-242.
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[12]ZHANG Guangjun.Machine vision[M].Beijing:Science Press,2008.张广军.机器视觉[M].北京:科学出版社,2008.
[13]LI Tong,ZHANG Qizhi.Research of SLAM loop-closure based on ORB bag of words[J].Information&Communications,2017(10):20-25.李同,张奇志.基于ORB词袋模型的SLAM回环检测研究[J].信息通信,2017(10);20-25.
[14]ZHANG Jing,ZHU Dayong,JIA Xiaodong.Cameralens distortion calibration with co-line points[J].La-ser Technology,2006 30(2):221-224.张靖,朱大勇,贾晓东.用共线点列标定摄像机镜头畸变[J].激光技术,2006,30(2):221-224.
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