基于改进ArUco标签的位姿估计方法OACSTPCD

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 2.5～4 m is 8.72 mm,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 4 m,improving the measurement accuracy.