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Publication Summary and Abstract

Lepora N, Fox C, Evans M, Mitchinson B, Motiwala A, Sullivan J, Pearson M, Welsby J, Pipe T, Gurney K and Prescott T (2011), A general classifier of whisker data using stationary na´ve Bayes: Application to BIOTACT robots, proceedings of Towards Autonomous Robotic Systems (TAROS), Sheffield, Springer LNCS 6856:13-23.

A general problem in robotics is how to best utilize sensors to classify the robot's environment. The BIOTACT project (BIOmimetic Technology for vibrissal Active Touch) is a collaboration between biologists and engineers that has led to many distinctive robots with artificial whisker sensing capabilities. One problem is to construct classifiers that can recognize a wide range of whisker sensations rather than constructing different classifiers for specific features. In this article, we demonstrate that a stationary naive Bayes classifier can perform such a general classification by applying it to various robot experiments. This classifier could be a key component of a robot able to learn autonomously about novel environments, where classifier properties are not known in advance.
Article via Digital Object Identifer (DOI) - article retrieved is probably subject to publisher's copyright