Principal curvature estimation by acoustical tactile sensing system

It is essential for robotic tactile sensors to provide capability of shape discrimination from static touch. For this purpose, the principal curvatures and corresponding principal directions play the important roles which defines the local shape of the object. This paper proposes a novel acoustic tactile sensing system which has an ability to identify the principal curvatures of the object surface by utilizing reflected acoustical wavefronts. Any smooth surface can be locally approximated by a set of independent parameters: the location of the point of contact, the normal vector of the tangent plane, the principal curvatures and the corresponding principal directions. The major difficulty, however, existing in estimating these parameters is that the wavefront reflected by the paraboloidal surface cannot be described in the linear combination of the plane-waves nor the spherical-waves strictly such that the nonlinearity exists between TOF and the parameters defining the surface. Avoiding the difficulty, the proposed sensing system seeks the unique point over the manifold which satisfies the Snell's low. In this paper, several acoustical experiments show the above advantages of the tactile sensor and topographical image reconstruction via geometrical connection of principal curvatures.