Rotating U-shaped snap gripping point positioning method based on YOLOv5

Jingyang Zhou; Jinbo Lu; Jinling Chen

doi:10.1117/12.2673007

28 February 2023 Rotating U-shaped snap gripping point positioning method based on YOLOv5

Jingyang Zhou, Jinbo Lu, Jinling Chen

Proceedings Volume 12596, International Conference on Mechatronics Engineering and Artificial Intelligence (MEAI 2022); 125961Q (2023) https://doi.org/10.1117/12.2673007
Event: International Conference on Mechatronics Engineering and Artificial Intelligence (MEAI 2022), 2022, Changsha, China

Abstract

When the robot grasps the U-shaped snap on the automatic production line, the pose detection and the positioning of the gripping point of the snap should be solved. To solve this problem, we propose the improved algorithm of YOLOv5, which can obtain the rotation angle and gripping point coordinates of the U-shaped snap. Firstly, the training sample angle information is obtained by roLabellmg. Secondly, in order to obtain the predicted angle, the algorithm adds a new angle prediction dimension and replaces the original positive box IOU with the minimum external rectangle IOU of the rotating box containing the angle information when calculating the IOU. Finally, the gripping point coordinates are determined on different poses of the U-shaped snap according to the robotic gripping rules, respectively. On the homemade U-shaped snap data set, the mAP value reaches 91.2%, which proves the effectiveness of the proposed method.

Citation Download Citation

Jingyang Zhou, Jinbo Lu, and Jinling Chen "Rotating U-shaped snap gripping point positioning method based on YOLOv5", Proc. SPIE 12596, International Conference on Mechatronics Engineering and Artificial Intelligence (MEAI 2022), 125961Q (28 February 2023); https://doi.org/10.1117/12.2673007

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