Generative model based robotic grasp pose prediction with limited dataset-Reference-Cited by-同舟云学术

Generative model based robotic grasp pose prediction with limited dataset

Published:2022-01-10 Issue:9 Volume:52 Page:9952-9966
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Shukla Priya^ORCID,Pramanik Nilotpal,Mehta Deepesh,Nandi G. C.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-021-03011-z.pdf

Reference41 articles.

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3. Asif U, Tang J, Harrer S (2018) Ensemblenet: Improving grasp detection using an ensemble of convolutional neural networks. In: BMVC. p 10

4. Asif U, Tang J, Harrer S (2018) Graspnet: An efficient convolutional neural network for real-time grasp detection for low-powered devices. In: IJCAI. vol 7, pp 4875–4882

5. Bicchi A, Kumar V (2000) Robotic grasping and contact: A review. In: Proceedings 2000 ICRA. Millennium conference. IEEE international conference on robotics and automation. symposia proceedings (Cat. No. 00CH37065), vol 1. IEEE, pp 348–353

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