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Dynamic tactile sensing for object identification

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.