DocumentCode :
3587060
Title :
Classification of flexible three-fingered hand grasping pattern based on BP neural network
Author :
Zhen Qian ; Fang Xu ; Guanjun Bao ; Sheng Xu ; Shibo Cai ; Jianchao Zhang ; Qinghua Yang
Author_Institution :
Coll. of Mech. Eng., Zhejiang Univ. of Technol., Hangzhou, China
fYear :
2014
Firstpage :
2209
Lastpage :
2213
Abstract :
In robotic application, flexible actuator is the end terminal parts. Rigid actuators are accurate but have poor security and practicability. This paper designed a new type of pneumatic dexterous hand - flexible three-fingered hand. The flexible three-fingered hand grasping pattern can be divided into griping, grasping and holding. The pattern classification of flexible three-fingered hand is designed based on the BP neural network. The network training results show that the proposed classification can determine the operation pattern of flexible three-fingered hand, according to the characteristics of the specific operating parameter vector of the target.
Keywords :
actuators; backpropagation; dexterous manipulators; flexible manipulators; neurocontrollers; pattern classification; vectors; BP neural network; flexible actuator; flexible three-fingered hand grasping pattern classification; network training; operating parameter vector; pneumatic dexterous hand; rigid actuators; robotic application; Biological neural networks; Grasping; Joints; Thumb; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
Type :
conf
DOI :
10.1109/ROBIO.2014.7090665
Filename :
7090665
Link To Document :
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