Intelligent Identification and Sorting of Chinese Herbs Recommend a String-Level Predictive Electromechanical System
- 1 School of Automation, Beijing Information Science and Technology University, Beijing, China
- 2 School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
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
DOI: https://doi.org/10.3844/ajbbsp.2024.159.168
Copyright: © 2024 Wenyi Zhang, Gang Wang, Xiaofei Xu, Junjie Zhu, Keping Mao, Tao Ma and Zixuan Li. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Domestic Chips
- Electromechanical Controller
- Mobile Robot Vision
- Target Recognition Recommendation
- YOLOv5
- Distance-IOU
- CSPNet
- FocalLoss