A general classifier of whisker data using stationary naive bayes: Application to BIOTACT robots

7Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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. © 2011 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Lepora, N. F., Fox, C. W., Evans, M., Mitchinson, B., Motiwala, A., Sullivan, J. C., … Prescott, T. J. (2011). A general classifier of whisker data using stationary naive bayes: Application to BIOTACT robots. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6856 LNAI, pp. 13–23). https://doi.org/10.1007/978-3-642-23232-9_2

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free