Dynamic tactile restoration by time domain nonlinear filtering without forward modeling

When we use a tactile sensor, sensing mechanism and restoration of texture from electric sensing signals are important issues. The objectives of this research are to design a new texture sensing system and to develop a new signal processing algorithm which can restore various texture. The new texture sensing system is designed to get texture with high resolution and wide velocity range, which uses a PVDF sensor and has fixing components for several types of objects in precise condition. Next, a new signal processing algorithm is developed to restore texture. In the previous researches, forward model is needed and then it is inverted by using some regularized inversion formula in frequency domain, where there exist problems such as amplification of noise due to ill-posedness, modeling uncertainty due to orientation and position of PVDF films and silicon rubber, and difficulty to add nonlinear terms into model in frequency domain. While, in this paper, we model directly the relation containing transient-state from measured signals to texture by using model structure of multi-input multi-output nonlinear autoregressive moving average and a time domain least squares estimation. The direct modeling can be done by the use of F/T sensor which is not used in the previous researches. Finally the several texture is experimentally reconstructed from sensing signals using the developed signal processing algorithm.