Lepora, N.F., Pearson, M.J., Mitchinson, B. et al. (5 more authors) (2010) Naive Bayes novelty detection for a moving robot with whiskers. In: Robotics and Biomimetics (ROBIO), 2010 IEEE International Conference on. 2010 IEEE International Conference on Robotics and Biomimetics, 14-18 Dec 2010, Tianjin, China. IEEE , pp. 131-136. ISBN 9781424493173
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. © 2010 IEEE.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2010 IEEE. This is an author produced version of a paper subsequently published in Robotics and Biomimetics (ROBIO), 2010 IEEE International Conference on. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Feb 2017 13:55 |
Last Modified: | 19 Dec 2022 13:34 |
Published Version: | https://doi.org/10.1109/ROBIO.2010.5723315 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ROBIO.2010.5723315 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:108434 |