关键词: 机器视觉, 桌面型机械臂, TensorFlow, OpenCV

Abstract: Compared with the traditional industry robot arm, the desktop robot arm has the characteristics of changeable environment and man-machine cooperation, which makes it more important to increase its visual function. At present, there are many application frameworks to realize machine vision. How to build an appropriate software and hardware platform for visual application according to the working environment and nature of the robot arm, so as to improve the accuracy and efficiency of machine vision recognition is the focus of this paper. Based on TensorFlow’s deep learning framework, the embedded system’s software and hardware design, and the application of OpenCV and other image processing software, this paper constructs a machine vision secondary development framework suitable for desktop robot arm, which provides a foundation for the further development of vision-based robot arm applications. Through simulation test and case application of man-machine cooperation, it is shown that the framework has better adaptability and better efficiency.

Key words: machine vision, desktop robot arm, TensorFlow, OpenCV