Manipulator Grasping Based on Object Detection
Xin Shu, Chang Liu, Tong Li
Available Online December 2018.
- https://doi.org/10.2991/tlicsc-18.2018.9How to use a DOI?
- Grasping; Neural networks; Robot vision systems.
- To make sure that manipulator can perform well on novel environment, a new grasping approach based on object detection is proposed. A pose estimation network is used as usual to predict the grasping pose of the object while an object detection network is added before it as the input information of the pose estimation. This combination of object detection and pose estimation improves the grasping accuracy by 28% and shows grasping robustness to objects which are not seen by manipulator before.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xin Shu AU - Chang Liu AU - Tong Li PY - 2018/12 DA - 2018/12 TI - Manipulator Grasping Based on Object Detection BT - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018) PB - Atlantis Press SP - 57 EP - 60 SN - 1951-6851 UR - https://doi.org/10.2991/tlicsc-18.2018.9 DO - https://doi.org/10.2991/tlicsc-18.2018.9 ID - Shu2018/12 ER -