Intelligent Identification and Sorting of Chinese Herbs Recommend a String-Level Predictive Electromechanical System

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