Development of a Capacitive-Piezoelectric Tactile Force Sensor for Static and Dynamic Forces Measurement and Neural Network-Based Texture Discrimination

Taking inspiration from human tactile system, a sensitive biomimetic multimodal tactile sensor for discrimination of static and dynamic forces is presented in this paper. The multimodal tactile sensor has a piezoelectric-capacitive tandem for responding to the dynamic and static forces respectively. Sensor can cater to normal direction dynamic force signals with a piezoelectric part operating in the d33 mode and static force with a capacitive part. The capacitive sensing part has a unique configuration with a top electrode and two sets of differential pairs electrodes for the force measurement in x and y shear axis, and one electrode for normal force measurement. The experimental characterization of the sensor was performed for static, quasi-static and dynamic forces. Along with the static forces the sensor was also able to cater to dynamic forces up to 60 Hz. The force sensitivity of the sensor for the normal force is 0.084 pF/N and 0.035 V/N from the capacitive and piezoelectric part respectively for a force range of 10 N. Also, in the shear X and Y direction the sensor exhibited a sensitivity of 0.027 pF/N and 0.029 pF/N respectively in the force range of 1.2 N. Through the vibrotactile data, the sensor showed an ability to discriminate between two texture samples through a neural network classifier. The presented sensor owing to its dimension, performance and capabilities can find its application in minimally invasive robotic surgery, robotics, wearable devices, and prosthetics.