Representing Data in Robotic Tactile Perception -- A Review

Abstract

Robotic tactile perception is a complex process involving several computational steps performed at different levels. Tactile information is shaped by the interplay of robot actions, the mechanical properties of its body, and the software that processes the data. In this respect, high-level computation, required to process and extract information, is commonly performed by adapting existing techniques from other domains, such as computer vision, which expects input data to be properly structured. Therefore, it is necessary to transform tactile sensor data to match a specific data structure. This operation directly affects the tactile information encoded and, as a consequence, the task execution. This survey aims to address this specific aspect of the tactile perception pipeline, namely Data Representation. The paper first clearly defines its contributions to the perception pipeline and then reviews how previous studies have dealt with the problem of representing tactile information, investigating the relationships among hardware, representations, and high-level computation methods. The analysis has led to the identification of six structures commonly used in the literature to represent data. The manuscript provides discussions and guidelines for properly selecting a representation depending on operating conditions, including the available hardware, the tactile information required to be encoded, and the task at hand.