Application of Image Recognition in Workpiece Classification
學年 109
學期 2
出版(發表)日期 2021-06-23
作品名稱 Application of Image Recognition in Workpiece Classification
著者 Hsin-Yi Chien; Yu-Chen Wang; Guan-Chen Chen
著錄名稱、卷期、頁數 Advances in Mechanical Engineering 13(6)
摘要 With the rapid development of information technology and widespread use of the Internet of Things, machine intelligence will undoubtedly emerge as a leading research topic in the future. The main purpose of the present research is to incorporate an image recognition system into a robotic arm motion to achieve automatic classification. First, we upload captured images to a PC for classification process and use chess patterns to conduct a sampling test. Next, when the system identifies these patterns as proper chess patterns, the robotic arm grabs the objects and moves them to designated locations. The project is divided into two main sections: image recognition and robotic arm motion. In the image recognition section, we use Keras and the Tensorflow open source learning machine to build a convolutional neural network model. Then, we use a learning model network that is a considerably more compact variant of the VGGNet network in the image recognition system. With this model, we achieve a recognition accuracy of 95%. In the robotic arm section, we use a five-axis robotic arm and an Arduino Uno board as the controller. We design the Denavit–Hartenberg parameters of the arm and calculate the direct (inverse) kinematics parameters to plan its trajectory. Thereafter, we use MATLAB software to simulate prototype processes, such as grabbing, moving, and placing. Finally, we import the program into the controller so that the robotic arm can execute classification based on the chess pattern.
關鍵字 CNN; VGGNet; image recognition; robotic arm; Denavit–Hartenberg
語言 en
ISSN 1687-8140
期刊性質 國外
收錄於 SCI
國別 GBR
出版型式 ,電子版,紙本

機構典藏連結 ( )