A Real-Time Sorting Robot System for Panax Notoginseng Taproots Equipped with an Improved Deeplabv3+ Model

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Abstract
The classification of the taproots of Panax notoginseng is conducive to improving the economic added value of its products. In this study, a real-time sorting robot system for Panax notoginseng taproots was developed based on the improved DeepLabv3+ model. The system is equipped with the improved DeepLabv3+ classification model for different grades of Panax notoginseng taproots. The model uses Xception as the taproot feature extraction network of Panax notoginseng. In the residual structure of the Xception network, a group normalization layer with deep separable convolution is adopted. Meanwhile, the global maximum pooling method is added in the Atrous Spatial Pyramid Pooling (ASPP) part to retain more texture information, and multiple shallow effective feature layers are designed to overlap in the decoding part to minimize the loss of features and improve the segmentation accuracy of Panax notoginseng taproots of all grades. The model test results show that the Xception-DeepLabv3+ model performs better than VGG16-U-Net and ResNet50-PSPNet models, with a Mean Pixel Accuracy (MPA) and a Mean Intersection over Union (MIoU) of 78.98% and 88.98% on the test set, respectively. The improved I-Xce-DeepLabv3+ model achieves an average detection time of 0.22 s, an MPA of 85.72%, and an MIoU of 90.32%, and it outperforms Xce-U-Net, Xce-PSPNet, and Xce-DeepLabv3+ models. The system control software was developed as a multi-threaded system to design a system grading strategy, which solves the problem that the identification signal is not synchronized with the grading signal. The system test results show that the average sorting accuracy of the system is 77% and the average false detection rate is 21.97% when the conveyor belt running speed is 1.55 m/s. The separation efficiency for a single-channel system is 200–300 kg/h, which can replace the manual work of three workers. The proposed method meets the requirements of current Panax notoginseng processing enterprises and provides technical support for the intelligent separation of Panax notoginseng taproots.
Funding Information
  • Major Science and Technology Project of Yunnan province (202102AA310048)

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