Title
A general classifier of whisker data using stationary naive bayes: application to BIOTACT robots
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.
Year
DOI
Venue
2011
10.1007/978-3-642-23232-9_2
TAROS
Keywords
Field
DocType
biotact project,various robot experiment,distinctive robot,general classification,whisker data,stationary naive bayes,artificial whisker,biotact robot,stationary naive bayes classifier,classifier property,different classifier,whisker sensation,general problem,general classifier
Naive Bayes classifier,Computer science,Artificial intelligence,Robot,Classifier (linguistics),Active touch,Machine learning,Robotics,Bayes' theorem
Conference
Citations 
PageRank 
References 
4
0.60
11
Authors
11
Name
Order
Citations
PageRank
Nathan F. Lepora123935.36
Charles W. Fox216214.65
Mat Evans340.60
Ben Mitchinson414517.74
Asma Motiwala550.97
J. Charlie Sullivan681.07
Martin J. Pearson721526.34
Jason Welsby8151.46
Tony Pipe917124.02
Kevin Gurney1040.60
Tony J. Prescott1140.60