ISSN:
1662-7482
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
The fingertip force sensor is the key for the complex task of the dexterous underwaterhand, in order to safely grasp an unknown object using the dexterous underwater hand andaccurately perceive its position in the fingers, a sensor should be developed, which can detect theforce and position simultaneously. Furthermore, this sensor should be used underwater. It isdifficult to employ the accustomed calibration method for the characteristic of the fingertip forcesensor, and the accustomed method is not able to assure the precision. A calibration method basedon RBF (Radial-Basis Function) neural network is introduced. Furthermore, the calibration systemand program are also designed. The calibration experiment of the sensor is carried out. The resultsshow the nonlinear calibration method based on RBF neural network assure the precision of thesensor, which meets the demand of research on the underwater dexterous hand
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/01/38/transtech_doi~10.4028%252Fwww.scientific.net%252FAMM.10-12.267.pdf
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