Paper Info
Title
Naive Bayes novelty detection for a moving robot with whiskers
Abstract
Novelty detection would be a useful ability for any autonomous robot that seeks to categorize a new environment or notice unexpected changes in its present one. A biomimetic robot (SCRATCHbot) inspired by the rat whisker system was here used to examine the performance of a novelty detection algorithm based on a “naive” implementation of Bayes rule. Naive Bayes algorithms are known to be both efficient and effective, and also have links with proposed neural mechanisms for decision making. To examine novelty detection, the robot first used its whiskers to sense an empty floor, after which it was tested with a textured strip placed in its path. Given only its experience of the familiar situation, the robot was able to distinguish the novel event and localize it in time. Performance increased with the number of whiskers, indicating benefits from integrating over multiple streams of information. Considering the generality of the algorithm, we suggest that such novelty detection could have widespread applicability as a trigger to react to important features in the robot's environment.
Year
DOI
Venue
2010
10.1109/ROBIO.2010.5723315
Robotics and Biomimetics
Keywords
Field
DocType
Bayes methods,biomimetics,decision making,mobile robots,motion control,robot vision,SCRATCHbot,autonomous robot,biomimetic robot,decision making,moving robot,naive Bayes rule,neural mechanism,novelty detection,rat whisker system,textured strip
Novelty detection,Motion control,Naive Bayes classifier,Biomimetics,Artificial intelligence,Engineering,Robot,Autonomous robot,Mobile robot,Machine learning,Bayes' theorem
Conference
ISBN
Citations 
PageRank 
978-1-4244-9319-7
2
0.41
References 
Authors
8
8
Name
Order
Citations
PageRank
Nathan F. Lepora123935.36
Martin J. Pearson221526.34
Benjamin Mitchinson3867.90
Mathew H. Evans47210.13
Charles W. Fox516214.65
Anthony G. Pipe625539.08
Kevin N. Gurney744553.49
Tony J. Prescott816428.77