Bioinspired tactile sensor for surface roughness discrimination
Tài liệu tham khảo
Tang, 2013, The effect of surface texturing on reducing the friction and wear of steel under lubricated sliding contact, Appl. Surf. Sci., 273, 199, 10.1016/j.apsusc.2013.02.013
Mayol-Cuevas, 1998, A first approach to tactile texture recognition, IEEE Int. Conf. Syst. Man Cybern., 5, 4246
Muhammad, 2011, A capacitive tactile sensor array for surface texture discrimination, Microelectron. Eng., 88, 1811, 10.1016/j.mee.2011.01.045
De Boissieu, 2009, Tactile texture recognition with a 3-axial force MEMS integrated artificial finger, Robot. Sci. Syst., 49
Kroemer, 2011, Learning dynamic tactile sensing with robust vision-based training, IEEE Trans. Robot., 27, 545, 10.1109/TRO.2011.2121130
Oddo, 2011, Roughness encoding for discrimination of surfaces in artificial active-touch, IEEE Trans. Robot., 27, 522, 10.1109/TRO.2011.2116930
Peiner, 2008, Slender tactile sensor for contour and roughness measurements within deep and narrow holes, IEEE Sens. J., 8, 1960, 10.1109/JSEN.2008.2006701
Vorburger, 2007, Comparison of optical and stylus methods for measurement of surface texture, Int. J. Adv. Manuf. Technol., 33, 110, 10.1007/s00170-007-0953-8
Skedung, 2013, Feeling small: exploring the tactile perception limits, Sci. Rep., 3, 10.1038/srep02617
Connor, 1992, Neural coding of tactile texture: comparison of spatial and temporal mechanisms for roughness perception, J. Neurosci., 12, 3414, 10.1523/JNEUROSCI.12-09-03414.1992
Yoshioka, 2001, Neural coding mechanisms underlying perceived roughness of finely textured surfaces, J. Neurosci., 21, 6905, 10.1523/JNEUROSCI.21-17-06905.2001
Libouton, 2012, Tactile roughness discrimination of the finger pad relies primarily on vibration sensitive afferents not necessarily located in the hand, Behav. Brain Res., 229, 273, 10.1016/j.bbr.2012.01.018
Augustine, 2004
Hosoda, 2006, Anthropomorphic robotic soft fingertip with randomly distributed receptors, Rob. Auton. Syst., 54, 104, 10.1016/j.robot.2005.09.019
Jaffe, 1971
Sokhanvar, 2007, A multifunctional PVDF-based tactile sensor for minimally invasive surgery, Smart Mater. Struct., 16, 989, 10.1088/0964-1726/16/4/006
Takashima, 2008, Piezoelectric properties of vinylidene fluoride oligomer for use in medical tactile sensor applications, Sens. Actuators A Phys., 144, 90, 10.1016/j.sna.2008.01.015
Bonakdar, 2010, Determination of tissue properties using microfabricated piezoelectric tactile sensor during minimally invasive surgery, Sens. Rev., 30, 233, 10.1108/02602281011051425
Li, 2008, Flexible dome and bump shape piezoelectric tactile sensors using PVDF-TrFE copolymer, J. Microelectromech. Syst., 17, 334, 10.1109/JMEMS.2007.911375
Howe, 1993, Dynamic tactile sensing: perception of fine surface features with stress rate sensing, IEEE Trans. Robot. Autom., 9, 140, 10.1109/70.238278
Choi, 2005, Development of tactile sensor for detecting contact force and slip, IEEE/RSJ Int Conf. Intell. Robot. Syst., 263, 2638
Kimoto, 2010, A multifunctional tactile sensor based on PVDF films for identification of materials, IEEE Sens. J., 10, 1508, 10.1109/JSEN.2010.2044407
Yi, 2016, Bio-inspired tactile FA-I spiking genertion under sinusoidal stimuli, J. Bionic Eng., 13, 612, 10.1016/S1672-6529(16)60332-3
Najarian, 2009
Xu, 2015, Long term effects of substrate stiffness on the development of hMSC mechanical properties, RSC Adv., 5, 105651, 10.1039/C5RA17233K
Davis, 1980, Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences, IEEE Trans. Acoust. Speech Signal Process., 28, 357, 10.1109/TASSP.1980.1163420
Lowe, 2004, Distinctive image features from scale-invariant keypoints, Int. J. Comput. Vis., 60, 91, 10.1023/B:VISI.0000029664.99615.94
Dallaire, 2014, Autonomous tactile perception: a combined improved sensing and Bayesian nonparametric approach, Rob. Auton. Syst., 62, 422, 10.1016/j.robot.2013.11.011
Salehi, 2011, Artificial skin ridges enhance local tactile shape discrimination, Sens. (Basel)., 11, 8626, 10.3390/s110908626
Englehart, 1999, Classification of the myoelectric signal using time-frequency based representations, Med. Eng. Phys., 21, 431, 10.1016/S1350-4533(99)00066-1
Schaaff, 2009, Towards an EEG-based emotion recognizer for humanoid robots, 792
Gehler, 2009, On feature combination for multiclass object classification, 221
Ngiam, 2011, Multimodal deep learning, 689
Drimus, 2012, Object texture recognition by dynamic tactile sensing using active exploration, 277
Hoelscher, 2015, Evaluation of tactile feature extraction for interactive object recognition, 310
Veiga, 2015, Stabilizing novel objects by learning to predict tactile slip, 5065
Cortes, 1995, Support vector machine, Mach. Learn., 20, 273, 10.1007/BF00994018
Hsu, 2002, A comparison of methods for multiclass support vector machines, Neural Netw. IEEE Trans., 13, 415, 10.1109/72.991427
Chang, 2011, LIBSVM: a library for support vector machines, ACM Trans. Intell. Syst. Technol., 2, 27, 10.1145/1961189.1961199
Edwards, 2008, Extracting textural features from tactile sensors, Bioinspir. Biomim., 3, 35002, 10.1088/1748-3182/3/3/035002
Rakotomamonjy, 2008, J. Mach. Learn. Res., 9, 2491
Gönen, 2013, Localized algorithms for multiple kernel learning, Pattern Recognit., 46, 795, 10.1016/j.patcog.2012.09.002