An assembly system based on industrial robot with binocular stereo vision
Hong Tang, Nanfeng Xiao
Available Online November 2016.
- https://doi.org/10.2991/aest-16.2016.1How to use a DOI?
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Hong Tang AU - Nanfeng Xiao PY - 2016/11 DA - 2016/11 TI - An assembly system based on industrial robot with binocular stereo vision BT - 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016) PB - Atlantis Press SP - 1 EP - 9 SN - 1951-6851 UR - https://doi.org/10.2991/aest-16.2016.1 DO - https://doi.org/10.2991/aest-16.2016.1 ID - Tang2016/11 ER -