@inproceedings{40da10a68e4b4fa7a9f870557fec32a0,
title = "A grasping CNN with image segmentation for mobile manipulating robot",
abstract = "This paper presents a grasping convolutional neural network with image segmentation for mobile manipulating robot. The proposed method is cascaded by a feature pyramid network FPN and a grasping network DrGNet. The FPN network combined with point cloud clustering is used to obtain the mask of the target object. Then, the grayscale map and the depth map corresponding to the target object are combined and sent to the DrGNet network for providing multi-scale images. On this basis, depthwise separable convolution is used for encoding. The results of encoders are refined according to the light-weight RefineNet as well as sSE, which can achieve a better grasp detection. The proposed method is verified by the experiments on mobile manipulating robot.",
keywords = "Grasping CNN, Image segmentation, Mobile manipulating robot, Robotic grasping",
author = "Yingying Yu and Zhiqiang Cao and Shuang Liang and Zhicheng Liu and Junzhi Yu and Xuechao Chen",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019 ; Conference date: 06-12-2019 Through 08-12-2019",
year = "2019",
month = dec,
doi = "10.1109/ROBIO49542.2019.8961427",
language = "English",
series = "IEEE International Conference on Robotics and Biomimetics, ROBIO 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1688--1692",
booktitle = "IEEE International Conference on Robotics and Biomimetics, ROBIO 2019",
address = "United States",
}