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A review: machine learning on robotic grasping
Author(s): Youhao Li; Qujiang Lei; ChaoPeng Cheng; Gong Zhang; Weijun Wang; Zheng Xu
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Paper Abstract

Machine learning has made breakthroughs in areas such as computer vision and natural language processing. In recent years, more and more research has been done on the application of machine learning on robotic grasping. This article summarizes the research progress of machine learning on robotic grasping, from the aspects of object grasping datasets, two main categories of methods that differ from the criteria for successful grasping with deep learning or reinforcement learning algorithm, discusses what current researches have done and the problems that have not yet been solved, and hopes to inspire new ideas in research of robotic grasping based on machine learning.

Paper Details

Date Published: 15 March 2019
PDF: 9 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110412U (15 March 2019); doi: 10.1117/12.2522945
Show Author Affiliations
Youhao Li, Guangzhou Institute of Advanced Technology (China)
Qujiang Lei, Guangzhou Institute of Advanced Technology (China)
ChaoPeng Cheng, Guangzhou Institute of Advanced Technology (China)
Gong Zhang, Guangzhou Institute of Advanced Technology (China)
Weijun Wang, Guangzhou Institute of Advanced Technology (China)
Zheng Xu, Guangzhou Institute of Advanced Technology (China)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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