Apple bagging system based on machine vision and multi-factor discrimination

This paper designs an apple bagging system based on machine vision and multi-factor discrimination by combining apple varieties and planting areas and using convolutional neural networks. This article uses a knowledge base-based apple bagging time query system to obtain the best bagging time, uses machine vision and convolutional neural networks to visually locate the bagged apples, uses the path planning method to plan the bagging path, and controls it by sending Command to control the bagging machine to complete bagging. The use of this system can effectively solve the problems of time-consuming, low efficiency, and insufficient labor for apple bagging, and improve the quality and output of apples.