High precision spatial positioning of sealed batteries based on a hybrid two stage model

DOI:	10.11809/bqzbgcxb2023.11.037
Keywords:	deep learning; image segmentation; high precision edge positioning
Abstract:	This paper proposes a high precision sealed battery contour positioning method based on a two stage hybrid model and designs related experiments in order to efficiently carry out high precision spatial positioning and contour welding of sealed batteries. The method combines the image segmentation network with traditional image processing methods to form a two stage hybrid model, allowing for end to end spatial positioning of the sealed battery and welding of the robotic arm with high positioning accuracy. This paper performs model training on the self created battery data set and welding experiments on the six axis robotic arm. The results demonstrate that: when compared to the UNet network, the CA UNet proposed in this paper has faster training and inference speeds, as well as comparable segmentation accuracy, indicating that the two stage hybrid model can accurately realize the contour location of sealed batteries.
Issue:	Vol. 44 No. 11 (2023)
Published:	2023-11-28
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