Helping a bio-inspired tactile sensor system to focus on the essential

Abstract

Insects use their antennae (feelers) as near-range sensors for orientation, object localization and communication. This paper presents further developments for an approach for an active tactile sensor system. This includes a hardware construction as well as a software implementation for interpreting the sensor readings. The discussed tactile sensor is able to detect an obstacle and its location. Furthermore the material properties of the obstacles are classified by application of neural networks. The focus of this paper lies in the development of a method which allows to determine automatically the part of the input data which is actually needed to fulfill the classification task. For that, non-negative matrix factorization is evaluated by quantifying the trade-off between classification accuracy and input (and network) dimension. © 2011 Springer-Verlag.