A grasps-generation-and-selection convolutional neural network for a digital twin of intelligent robotic grasping

Author:

Hu WeifeiORCID,Wang Chuxuan,Liu Feixiang,Peng Xiang,Sun PengwenORCID,Tan Jianrong

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Reference33 articles.

1. Deep learning for detecting robotic grasps;Lenz;Int. J. Rob. Res.,2015

2. Closing the loop for robotic grasping: a real-time, generative grasp synthesis approach;Morrison;Robot. Sci. Syst.,2018

3. On-policy dataset synthesis for learning robot grasping policies using fully convolutional deep networks;Satish;IEEE Robot. Autom. Lett.,2019

4. Grasp2Vec: learning object representations from self-supervised grasping;Jang,2018

5. Dex-Net 2.0: deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics;Mahler;Robot. Sci. Syst.,2017

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