Intelligent Identification and Sorting of Chinese Herbs Recommend a String-Level Predictive Electromechanical System
Wenyi Zhang1, Gang Wang2, Xiaofei Xu1, Junjie Zhu1, Keping Mao1, Tao Ma1 & Zixuan Li1 Show affiliations
- School of Automation, Beijing Information Science and Technology University, Beijing, China
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
American Journal of Biochemistry and Biotechnology, Volume 20, Issue 2, pp. 159–168 · doi.org/10.3844/ajbbsp.2024.159.168
Abstract
Based on the analysis of a large number of Chinese medicinal materials, a mobile robot visual function research and development experimental domestic chips electromechanical arm-controller, which was constructed using a typical kernel algorithm recommended by Chinese medicinal materials visual recognition, which the cascade Electromechanical Control System was based on iterative learning electromechanical control for multi-joint manipulators. The original and improved YOLOV5 algorithm models were compared to detect and recommend targets in the color recognition and shape recognition vision scene of mobile robots in human-computer interaction. The experimental results show that, on the self-made data set, the improved system can obtain a better average accuracy score and detection speed and meet the requirements of real-time and accuracy, it provides a new reference design scheme for the experimental platform of mobile robot vision recognition
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Zhang, W., Wang, G., Xu, X., Zhu, J., Mao, K., Ma, T. & Li, Z. (2024). Intelligent Identification and Sorting of Chinese Herbs Recommend a String-Level Predictive Electromechanical System. American Journal of Biochemistry and Biotechnology, 20(2), 159–168. https://doi.org/10.3844/ajbbsp.2024.159.168
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