基于改进ArUco标签的位姿估计方法

段志瑜; 罗哉; 江文松; 杨力; 李亚茹; 卞点

doi:10.3969/j.issn.1000-1158.2024.03.09

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计量学报 ›› 2024, Vol. 45 ›› Issue (3) : 364-371. DOI: 10.3969/j.issn.1000-1158.2024.03.09

几何量计量

基于改进ArUco标签的位姿估计方法

段志瑜¹,罗哉¹,江文松¹,杨力²,李亚茹¹,卞点¹

作者信息 +

Pose Estimation Method Based on Improved ArUco Tags

DUAN Zhiyu¹,LUO Zai¹,JANG Wensong¹,YANG Li²,LI Yaru¹,BIAN Dian¹

Author information +

文章历史 +

摘要

针对使用ArUco标签在远距离测量时精度不高的问题,提出改进ArUco标签的位姿估计方法。该方法在ArUco标签的基础上设计了阵列特征圆环,提取圆环的中心点并对其进行排序,根据交比不变特性判断出圆心检测的准确性;利用加权最小二乘法建立ArUco标签角点与阵列圆环圆心之间的直线拟合关系,实现角点修正;采用EPnP算法解算出改进ArUco标签的位姿参数,并利用LM算法对位姿进行优化,提高位姿测量精度。设计了机械臂视觉定位系统验证所提出方法的可行性和有效性。实验结果表明,此改进方法在2.5～4m范围内测量的最大平移误差为8.72mm,最大旋转误差为1.78°。所提出的方法在4m处纵向距离测量的相对误差降低0.69%,提高了测量精度。

Abstract

Aiming at the problem of low accuracy when using ArUco tags for long-distance measurement, an improved pose estimation method is proposed. The method designs array feature rings based on ArUco tags, the center points of the rings are extractd and sortd, and the accuracy of circle center detection are judged based on the cross-ratio invariant characteristics. The weighted least squares method is used to establish a straight line fitting relationship between the corner points of the ArUco tag and the center of the array rings to achieve corner point correction. The EPnP algorithm is used to calculate the pose parameters of the improved ArUco tag, and the LM algorithm is used to optimize the pose and improve the pose measurement accuracy. A robotic arm visual positioning system is designed to verify the feasibility and effectiveness of the proposed method. Experimental results show that the maximum translation error measured by this method in the range of 2.5～4m is 8.72mm, and the maximum rotation error is 1.78°, and the maximum rotation error is 4.65°. The proposed method reduces the relative error of longitudinal distance measurement by 0.69% at 4m, improving the measurement accuracy.

导出引用

段志瑜,罗哉,江文松,杨力,李亚茹,卞点. 基于改进ArUco标签的位姿估计方法[J]. 计量学报. 2024, 45(3): 364-371 https://doi.org/10.3969/j.issn.1000-1158.2024.03.09

DUAN Zhiyu,LUO Zai,JANG Wensong,YANG Li,LI Yaru,BIAN Dian. Pose Estimation Method Based on Improved ArUco Tags[J]. Acta Metrologica Sinica. 2024, 45(3): 364-371 https://doi.org/10.3969/j.issn.1000-1158.2024.03.09

中图分类号： TB92

参考文献

［1］于鲲, 丛明煜, 段佳佳, 等. 星箭对接环抓捕点单目视觉导航方法［J］. 仪器仪表学报, 2018, 39(12): 228-236.
YU K, CONG M Y, DUAN J J, et al. Monocular visual navigation method for capturing point of docking ring ［J］. Chinese Journal of Scientific Instrument, 2018, 39(12): 228-236.
［2］卢晓昀. 动态环境下的单目视觉同时定位与建图［D］. 西安: 中国科学院大学(中国科学院西安光学精密机械研究所), 2021.
［3］张立国, 章玉鹏, 金梅, 等. 基于归一化注意力机制的特征自适应融合目标跟踪算法［J］. 计量学报, 2023, 44(9): 1383-1389.
ZHANG L G, ZHANG Y P, JIN M, et al. Target tracking algorithm based on normalized attention mechanism with feature adaptive fusion ［J］. Acta Metrologica Sinica, 2023, 44(9): 1383-1389.
［4］喻靖, 江文松, 罗哉, 等. 协作机械臂末端执行器的快速定位算法［J］. 计量学报, 2021, 42(7): 833-839.
YU J, JIANG W S, LUO Z, et al. Fast positioning algorithm for end-effector of cooperative manipulator ［J］. Acta Metrologica Sinica, 2021, 42(7): 833-839.
［5］马宁, 曹云峰, 王指辉, 等. 基于YOLOv5网络架构的着陆跑道检测算法研究［J］. 激光与光电子学进展, 2022, 59(14): 199-205.
MA N, CAO Y F, WANG Z H, et al. Landing runway detection algorithm based on YOLOv5 network architecture ［J］. Laser & Optoelectronics Progress, 2022, 59(14): 199-205.
［6］李娜, 王学影, 胡晓峰, 等. 基于改进PP-YOLOv2的IC引脚焊接缺陷检测算法研究［J］. 计量学报, 2023, 44(10): 1574-1581.
LI N, WANG X Y, HU X F, et al. Research on IC pin soldering defect detection algorithm based on improved PP-YOLOv2 ［J］. Acta Metrologica Sinica, 2023, 44(10): 1574-1581.
［7］GARRIDO-JURADO S, MUNOZ-SALINAS R, MADRID-CUEVAS F J, et al. Automatic generation and detection of highly reliable fiducial markers under occlusion ［J］. Pattern Recognition, 2014, 47(6): 2280-2292.
［8］MARUT A, WOJTOWICZ K, FALKOWSKI K, et al. ArUco markers pose estimation in UAV landing aid system ［C］//IEEE 6th International Workshop on Metrology for AeroSpace (MetroAeroSpace). 2019.
［9］da SILVA S L A, TOMMASELLI A M G, ARTERO A O. Using ARUCO coded targets for camera calibration automation ［J］. Boletim de Ciencias Geodesicas, 2014, 20(3): 626-646.
［10］HU X, LUO Z, JIANG W. AGV Localization System Based on Ultra-Wideband and Vision Guidance ［J］. Electronics, 2020, 9(3), 448.
［11］邢伯阳, 潘峰, 冯肖雪. ArUco-SLAM: 基于ArUco二维码阵列的单目实时建图定位系统［J］. 北京理工大学学报, 2020, 40(4): 427-433.
XING B Y, PAN F, FENG X X. ArUco-SLAM: a monocular SLAM system based on ArUco landmark array ［J］. Transactions of Beijing Institute of Technology, 2020, 40(4): 427-433.
［12］KAM H C, YU Y K, WONG K H, et al. An Improvement on ArUco Marker for Pose Tracking Using Kalman Filter ［C］//19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). 2018.
［13］OSCADAL P, HECZKO D, VYSOCKY A, et al. Improved Pose Estimation of Aruco Tags Using a Novel 3D Placement Strategy ［J］. Sensors, 2020, 20(17), 4825.
［14］FERRAO J, DIAS P, NEVES A J R. Detection of Aruco Markers Using the Quadrilateral Sum Conjuncture ［C］//15th International Conference on Image Analysis and Recognition (ICIAR). 2018.
［15］丁浩峰, 雷清雲, 段欣葵, 等. 基于多层级合作标识无人机自主着舰视觉引导方法［J］. 测控技术, 2023, 42(8): 7-14.
DING H F, LEI Q Y, DUAN X K, et al. Visual guidance method for autonomous landing of UAV based on multi-level cooperative identification ［J］. Measurement & Control Technology, 2023, 42(8): 7-14.
［16］陈曼桐, 侯培国. 基于相对定位技术实现对Apriltags测量范围拓展的研究［J］. 电子测量与仪器学报, 2023, 37(3): 74-85.
CHEN M T, HOU P G. Method to expand the measuring range of Apriltags based on relative positioning ［J］. Journal of Electronic Measurement and Instrumentation, 2023, 37(3): 74-85.
［17］何宇. 基于机器视觉的列车定位系统设计与实现［D］. 北京: 北京邮电大学, 2021.
［18］张文, 杨耀鑫, 黄天帜, 等. ArUco辅助的爬壁机器人自主定位方法［J/OL］. 机器人: 1-10. DOI: 10.13973/j.cnki.robot.230046.
ZHANG W, YANG Y X, HUANG T Z, et al. ArUco-assisted autonomous localization method for wall climbing robots ［J/OL］. Robot: 1-10. DOI: 10.13973/j.cnki.robot.230046.
［19］YANG S, LIU M, YIN S, et al. An improved method for location of concentric circles in vision measurement ［J］. Measurement, 2017, 100: 243-251.
［20］LU C S, XIA S Y, SHAO M, et al. Arc-Support Line Segments Revisited: An Efficient High-Quality Ellipse Detection ［J］. IEEE Transactions on Image Processing, 2020, 29: 768-781.
［21］许航, 熊芝, 张刘港, 等. 基于加权最小二乘的激光跟踪姿态角测量方法［J］. 红外与激光工程, 2022, 51(6): 353-358.
XU H, XIONG Z, ZHANG L G, et al. Laser tracking attitude angle measurement method based on weighted least squares ［J］. Infrared and Laser Engineering, 2022, 51(6): 353-358.
［22］LEPETIT V, MORENONOGUER F, FUA P, et al. EPnP: An Accurate O(n) Solution to the PnP Problem ［J］. International Journal of Computer Vision, 2009, 81(2): 155-166.