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Dynamic tactile sensing for object identification

Gunther Heidemann, Matthias Schöpfer

Year
2004
Citations
53

Abstract

We propose a neural architecture for the recognition of objects by haptics. We demonstrate its performance for a set of household objects and toys using a low cost 2D pressure sensor of coarse resolution, which is moved by a robot arm guided by contact points. The approach transfers the well known view-based method from computer vision to the domain of tactile sensing. However, in contrast to computer vision, not static frames but entire time series of 2D pressure profiles are evaluated.

Keywords

Tactile sensorComputer visionComputer scienceArtificial intelligenceObject (grammar)RobotCognitive neuroscience of visual object recognitionIdentification (biology)Contrast (vision)Set (abstract data type)

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