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An artificial moth: Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search

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Citation

Pyk, P., Badia, S. B. I., Bernardet, U., Knusel, P., Carlsson, M., Gu, J., et al. (2006). An artificial moth: Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search. Autonomous Robots, 20(3), 197-213. doi:10.1007/s10514-006-7101-4.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0014-705F-1
Abstract
Robots have been used to model nature, while nature in turn can
contribute to the real-world artifacts we construct. One particular
domain of interest is chemical search where a number of efforts are
underway to construct mobile chemical search and localization systems.
We report on a project that aims at constructing such a system based on
our understanding of the pheromone communication system of the moth.
Based on an overview of the peripheral processing of chemical cues by
the moth and its role in the organization of behavior we emphasize the
multimodal aspects of chemical search, i.e. optomotor anemotactic
chemical search. We present a model of this behavior that we test in
combination with a novel thin metal oxide sensor and custom build mobile
robots. We show that the sensor is able to detect the odor cue, ethanol,
under varying flow conditions. Subsequently we show that the standard
model of insect chemical search, consisting of a surge and cast phases,
provides for robust search and localization performance. The same holds
when it is augmented with an optomotor collision avoidance model based
on the Lobula Giant Movement Detector (LGMD) neuron of the locust. We
compare our results to others who have used the moth as inspiration for
the construction of odor robots.