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Author:

Xu, Zhe (Xu, Zhe.) | Chen, Muxin (Chen, Muxin.) | Liu, Chunfang (Liu, Chunfang.)

Indexed by:

CPCI-S EI Scopus

Abstract:

Aiming at the problem of lowering the success rate of grasping due to the different characteristics of the grasped object, such as quality, soft and hard, in the process of robotic garbage sorting, this paper proposes an MTV tactile character recognition model based on the attention mechanism. The model is trained using five tactile capture data sets for tactile traits, and the recognition rate of the object's hardness and hardness traits can reach more than 90 degrees. Experimental results show that the model can effectively identify tactile traits with a high recognition rate. Has good generalization ability.

Keyword:

Robot garbage sorting LSTM Tactile time series Object character recognition

Author Community:

  • [ 1 ] [Xu, Zhe]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Chen, Muxin]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Liu, Chunfang]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

Reprint Author's Address:

  • [Xu, Zhe]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

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Source :

2020 CHINESE AUTOMATION CONGRESS (CAC 2020)

ISSN: 2688-092X

Year: 2020

Page: 7095-7100

Language: English

Cited Count:

WoS CC Cited Count: 4

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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