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.
CITATION STYLE
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
Mendeley helps you to discover research relevant for your work.