Sensing the Frictional State of a Robotic Skin via Subtractive Color Mixing

Abstract

The perception of surface properties such as shape and slipperiness is crucial to ensure that the hand-held object is stable. Without touch, precise manipulation becomes difficult. Some robotic tactile sensors use cameras that observe the elastic deformation of a membrane to detect edges or slippage of the contact. The perception of the contact state drove innovative control strategies. However, previous methods on these lines do not include quantitative means of measuring the three-dimensional (3-D) deformation of the skin or suffer from a lack of spatial resolution. Here, we present a tactile sensor based on a subtractive color mixing process designed to track the 3-D displacement of an array of markers, using the information delivered by the color channel of off-the-shelf cameras. The distributed shear and normal deformation can be assessed from the spectrum of the light reflected and refracted by an array of diffusive and transmissive markers placed on two superimposed layers. The markers show various blends of colors, depending on the displacement at the surface. The color pattern of each marker can be tracked with little computation and remains robust to external lighting. The ability to sense the 3-D deformation field can improve robotic perception of frictional properties that have applications in the fields of robotic control and human-robot interactions.