Research on Object Grasping Point Selection Based on Deep Learning
Authors
Bo Yuan, Shukai Qin, Hualiang Zhang, Tao Zhang, Xiaolong Yu
Corresponding Author
Bo Yuan
Available Online March 2018.
- DOI
- 10.2991/icaita-18.2018.16How to use a DOI?
- Keywords
- deep learning; depth image; grasping points
- Abstract
The research on robot grasping involves mechanical, control, computer, artificial intelligence and so on. Robot Grasping is also a good emplementation of minimal research to support other related research. Efforts on flexibility and interactivity of robot grasping can promote many related studies. In this paper, convolutional neural network is used to study the grasp candidates selection of two-finger robot grasp. The experient explained the processes of select candidate points in detail, the results of the convolutional neural network in the grasp candidates selection is verified through experiments.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Bo Yuan AU - Shukai Qin AU - Hualiang Zhang AU - Tao Zhang AU - Xiaolong Yu PY - 2018/03 DA - 2018/03 TI - Research on Object Grasping Point Selection Based on Deep Learning BT - Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018) PB - Atlantis Press SP - 62 EP - 65 SN - 1951-6851 UR - https://doi.org/10.2991/icaita-18.2018.16 DO - 10.2991/icaita-18.2018.16 ID - Yuan2018/03 ER -