Intelligent Fusion Method Based on BP Neural Network for Robot Suit Pressure Sensing Array Data
In order to eliminate the crosstalk influence existed among temperature, voltage fluctuation and sensor signal of robot tactile sensor array unit, the paper presented a sort of information fusion method in large scale sensor array based on BP neural network. By means of learning training with weight...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Bulgarian Academy of Sciences
2017-12-01
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| Series: | International Journal Bioautomation |
| Subjects: | |
| Online Access: | http://www.biomed.bas.bg/bioautomation/2017/vol_21.4/files/21.4_03.pdf |
| Summary: | In order to eliminate the crosstalk influence existed among temperature, voltage fluctuation and sensor signal of robot tactile sensor array unit, the paper presented a sort of information fusion method in large scale sensor array based on BP neural network. By means of learning training with weight for neural network, the method can effectively eliminate the crosstalk influence for output characteristics of pressure sensing array sensor among non-target parameters and large scale sensor signals such as the environment temperature, voltage disturbance and so on, and thereby it improves the stability and reliability of robot tactile sensing suit system. Laboratory tests demonstrated that the error of the suit pressure sensor array data is less than 5%. The experimental results show that the intelligent fusion method presented in this paper can be accepted in engineering application, and the method is be propitious to improve intelligent judgment and information utilization ratio of robot system. |
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| ISSN: | 1314-1902 1314-2321 |