An Assembly System Based on Industrial Robot with Binocular Stereo Vision

作者：Tang, Hong^*; Xiao, Nanfeng

来源：7th International Conference on Electronics and Information Engineering (ICEIE), 2016-09-17 To 2016-09-18.

DOI：10.1117/12.2265855

• Assembly system
• Industrial robot
• Binocular stereo vision
• Genetic algorithm
• Deep neural network

This paper proposes an electronic part and component assembly system based on an industrial robot with binocular stereo vision. Firstly, binocular stereo vision with a visual attention mechanism model is used to get quickly the image regions which contain the electronic parts and components. Secondly, a deep neural network is adopted to recognize the features of the electronic parts and components. Thirdly, in order to control the end-effector of the industrial robot to grasp the electronic parts and components, a genetic algorithm (GA) is proposed to compute the transition matrix and the inverse kinematics of the industrial robot (end-effector), which plays a key role in bridging the binocular stereo vision and the industrial robot. Finally, the proposed assembly system is tested in LED component assembly experiments, and the results denote that it has high efficiency and good applicability.

• 出版日期2017
• 单位华南理工大学