基于改进ArUco标签的位姿估计方法

doi:10.3969/j.issn.1000-1158.2024.03.09

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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.

Key words： geometric metrology pose estimation ArUco tag visual positioning object detection;monocular vision

Received: 12 October 2023 Published: 25 March 2024

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TB92

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	Articles by authors
	DUAN Zhiyu
	LUO Zai
	JANG Wensong
	YANG Li
	LI Yaru
	BIAN Dian

Cite this article:

DUAN Zhiyu,LUO Zai,JANG Wensong, et al. Pose Estimation Method Based on Improved ArUco Tags[J]. Acta Metrologica Sinica, 2024, 45(3): 364-371.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2024.03.09 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2024/V45/I3/364

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