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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.
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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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