TOWARD A COMPUTATIONAL MODEL OF CONSTRAINT-DRIVEN EXPLORATION AND HAPTIC OBJECT IDENTIFICATION

A conceptual model of the human haptic system in relation to object id entification is presented. The model encompasses major architectural e lements including representations of haptically accessible object prop erties and exploratory procedures (EPs)-dedicated movement patterns th at are specialized to extract particular properties. These architectur al units are related in processing-specific ways. Properties are assoc iated with exploratory procedures in keeping with the extent to which a given procedure delivers information about a given property. The EPs are associated with one another in keeping with their compatibility, as determined by parameters of motor execution and interactions with t he object and the workspace. The resulting architecture is treated as a system of constraints which guide the exploration of an object durin g the course of identification. The selection of the next step in a se quence of exploration requires that constraints be optimally satisfied . A network approach to constraint satisfaction is implemented and sho wn to account for a number of previous empirical results concerning th e time course of exploration, object classification speed, and inciden tal learning about object properties. This system has potential applic ations for robotic haptic exploration.