Human skin has tactile receptors that have different response characteristics. These characteristics are effective for the tactile texture classification. In this paper, we propose a classification method by using a magnetic tactile sensor. The tactile sensor has two sensing elements that detects slow and fast deformations occurred on the surface of itself. We confirm that the output voltages of the sensing elements include frequency characteristics of tactile texture. In addition, a support vector machine classifies tactile textures based on the output voltages.
DahiyaR.S. and ValleM., System Issues, Requirements and Expectations, Robotic Tactile Sensing, 2013, pp. 43-78.
2.
TognettiA., LorussiF., TesconiM. and De RossiD., Strain sensing fabric characterization, Proc. IEEE Sesnors1 (2004), 527-530.
3.
HoshiT. and ShinodaH., A sensitive skin based on touch-area-evaluating tactile elements, Proc. IEEE Virtual Reality, 2006, pp. 89-94.
4.
NakamotoH., KobayashiF. and KojimaF., Evaluation of circle diameter by distributed tactile information in active tracing, Journal of Sensors, Article ID 658749, 2013, pp. 1-7.
5.
KamiyamaK., KajimotoH., KawakamiN. and TachiS., Evaluation of a vision based tactile sensor, Proc. IEEE Int. Conf. Robot. Autom.2 (2004), 1542-1547.
6.
YamadaY., MaenoT., FujimotoI., MorizonoT. and UmetaniY., Identification of incipient slip phenomena based on the circuit output signals of PVDF film strips embedded in artificial finger ridges, Proc. SICE Annual Conf., 2002, pp. 3272-3277.
7.
GladstoneH., WaldronK.J. and EnedahC., Stiffness and texture perception for teledermatology, Stud. Health Technol. Inform. 111, 2005, pp. 579-585.
8.
LedermanS.J., Skin and Touch, Encyclopedia of Human Biology71991.
9.
ChangC.C. and LinC.J., Libsvm: A library for support vector machines, ACM trans. on Intelligent Systems and Technology, 2011, 2-3.
