Abstract
The study of natural olfaction can assist in developing more robust and sensitive artificial chemical sensing systems. Here we present the implementation on an indoor fully autonomous wheeled robot of two insect models for odor classification and localization based on moth behavior and the insect’s olfactory pathway. Using the biologically based signal encoding scheme of the Temporal Population Code (TPC) as a model of the antenna lobe, the robot is able to identify and locate the source of odors using real-time chemosensor signals. The results of the tests performed show a successful classification for ethanol and ammonia under controlled conditions. Moreover, a comparison between the results obtained with and without the localization algorithm, shows an effect of the behavior itself on the performance of the classifier, suggesting that the behavior of insects may be optimized for the specific sensor encoding scheme they deploy in odor discrimination.
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López-Serrano, L.L., Vouloutsi, V., Escudero Chimeno, A., Mathews, Z., Verschure, P.F.M.J. (2012). Insect-Like Odor Classification and Localization on an Autonomous Robot. In: Prescott, T.J., Lepora, N.F., Mura, A., Verschure, P.F.M.J. (eds) Biomimetic and Biohybrid Systems. Living Machines 2012. Lecture Notes in Computer Science(), vol 7375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31525-1_47
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DOI: https://doi.org/10.1007/978-3-642-31525-1_47
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