Tactile Object Recognition and Localization Using Spatially-Varying Appearance

Abstract

In this work, we present a new method for doing object recognition using tactile force sensors that makes use of recent work on “tactile appearance” to describe objects by the spatially-varying appearance characteristics of their surface texture. The method poses recognition as a localization problem with a discrete component of the state representing object identity, allowing the application of sequential state estimation techniques from the mobile robotics literature. Ideas from geometric hashing approaches are incorporated to enable efficient updating of probabilities over object identity and pose. The method’s strong performance is demonstrated experimentally both in simulation and using physical sensors.