TY - GEN

T1 - Analytical Method of Recognition and Positioning the Circular Identification Marks

AU - Obyzalov, Maxim A.

AU - Sosnovsky, Andrey V.

N1 - The research was supported by the Grant of the Ministry of Science and Higher education of the Russian Federation (project \u2116 0836-2020-0020).

PY - 2024

Y1 - 2024

N2 - Identification marks (or the fiducial markers) recognition is an important problem in image processing. This technique is used in robotics and industry to perform loading and unloading operations. Usually, algorithms using the neural networks to solve this problem show their low efficiency in devices with low computing resources. The proposed method is based on comparing the mark contour with an ellipse and converting the camera coordinates and contour parameters into the physical ones. So, it becomes possible to recognize the circular identification marks in space and to to perform the robot positioning without using large computing resources. The algorithm based on the proposed method was implemented on the Raspberry PI 3B quad core ARM Cortex-A53 in the 1.2 GHz single-board computer and an OV5647 camera. The algorithm showed acceptable positioning accuracy for solving tasks related to loading and unloading packaging units by autonomous robots without human intervention.

AB - Identification marks (or the fiducial markers) recognition is an important problem in image processing. This technique is used in robotics and industry to perform loading and unloading operations. Usually, algorithms using the neural networks to solve this problem show their low efficiency in devices with low computing resources. The proposed method is based on comparing the mark contour with an ellipse and converting the camera coordinates and contour parameters into the physical ones. So, it becomes possible to recognize the circular identification marks in space and to to perform the robot positioning without using large computing resources. The algorithm based on the proposed method was implemented on the Raspberry PI 3B quad core ARM Cortex-A53 in the 1.2 GHz single-board computer and an OV5647 camera. The algorithm showed acceptable positioning accuracy for solving tasks related to loading and unloading packaging units by autonomous robots without human intervention.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85196551317

U2 - 10.1063/5.0210696

DO - 10.1063/5.0210696

M3 - Conference contribution

SN - 978-073544954-1

VL - 3094

T3 - AIP Conference Proceedings

BT - AIP Conference Proceedings

PB - American Institute of Physics Inc.

T2 - International Conference of Numerical Analysis and Applied Mathematics 2022, ICNAAM 2022

Y2 - 19 September 2022 through 25 September 2022

ER -