Tactile sensors are basically arrays of force sensors. Most of these force sensors are made of polymers or conductive rubber to lower cost, especially in the case of large area low-medium resolution tactile sensors. The consequence of such a decrease in cost and complexity is a worsening in performance. Hysteresis and drift are two main sources of error. Other tactile sensors do not present such limitations per se, however they are covered by a protective elastic layer in their final location and this covering can also lead to limitations. This paper presents a method to reduce the error caused by hysteresis in tactile sensors. This method is based on the generalized Prandtl-Ishlinskii model that has been applied to characterize hysteresis and saturation nonlinearities in smart actuators. The approximation error depends on several parameters as well as on the envelope functions that are chosen. Different alternatives are explored in the paper.
Moreover, the model can also be inverted. This inverse model allows the force values to be obtained from the tactile sensor output while reducing the errors caused by hysteresis. In this paper the results of such an inversion are compared with other alternatives to register the data that do not compensate hysteresis. The average value of the hysteresis error measured in the experimental curve is 7.20% for an input range of 206kPa, while this error is 1.51% following the compensation procedure. Since the implementation of tactile sensors usually results in the electronics being close to the raw sensor, and this hardware is also commonly based on a microcontroller or even on a FPGA, it is possible to add the algorithms presented in this paper to the set of compensation and calibration procedures to run in the smart sensor.
