关键词: 迁移学习, 视觉识别, 图像处理, 神经网络, 分类

Abstract: In order to solve the application problems facing traditional industrial robots such as difficulty in identifying complex industrial parts and singleness in recognition, a visual recognition and sorting strategy based on transfer learning is proposed. Firstly, the pictures taken by high-precision industrial camera are processed by Haclon software, such as expansion, corrosion and then imported to Pytorch which has prepared a good neural network model to identify the target classification, and finally the purpose of industrial robot sorting is achieved. In the experiment, two kinds of mushrooms with varied shapes are taken as an example to implement the transfer learning and sorting on the UR5 robot platform. The experimental results illustrate the good accuracy and stability of the proposed algorithm.

Key words: transfer learning, vision recognition, image processing, neural networks, sorting