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

Pawel Pyk*, Sergi Bermúdez i Badia, Ulysses Bernardet, Philipp Knüsel, Mikael Carlsson, Jing Gu, Eric Chanie, Bill S. Hansson, Tim C. Pearce, Paul F.M.J. Verschure

*Corresponding author for this work

Research output: Contribution to journalReview article

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.

Original languageEnglish
Pages (from-to)197-213
Number of pages17
JournalAutonomous Robots
Volume20
Issue number3
DOIs
Publication statusPublished - 1 Jun 2006

Fingerprint

Robots
Odors
Sensors
Collision avoidance
Mobile robots
Neurons
Communication systems
Ethanol
Detectors
Oxides
Processing
Metals

Keywords

  • Electronic noses
  • Gas distribution mapping
  • Gas source localization
  • Mobile olfaction
  • Odor discrimination

Cite this

Pyk, P., Bermúdez i Badia, S., Bernardet, U., Knüsel, P., Carlsson, M., Gu, J., ... Verschure, P. F. M. J. (2006). An artificial moth: Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search. Autonomous Robots, 20(3), 197-213. https://doi.org/10.1007/s10514-006-7101-4
Pyk, Pawel ; Bermúdez i Badia, Sergi ; Bernardet, Ulysses ; Knüsel, Philipp ; Carlsson, Mikael ; Gu, Jing ; Chanie, Eric ; Hansson, Bill S. ; Pearce, Tim C. ; Verschure, Paul F.M.J. / An artificial moth : Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search. In: Autonomous Robots. 2006 ; Vol. 20, No. 3. pp. 197-213.
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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.",
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Pyk, P, Bermúdez i Badia, S, Bernardet, U, Knüsel, P, Carlsson, M, Gu, J, Chanie, E, Hansson, BS, Pearce, TC & Verschure, PFMJ 2006, 'An artificial moth: Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search', Autonomous Robots, vol. 20, no. 3, pp. 197-213. https://doi.org/10.1007/s10514-006-7101-4

An artificial moth : Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search. / Pyk, Pawel; Bermúdez i Badia, Sergi; Bernardet, Ulysses; Knüsel, Philipp; Carlsson, Mikael; Gu, Jing; Chanie, Eric; Hansson, Bill S.; Pearce, Tim C.; Verschure, Paul F.M.J.

In: Autonomous Robots, Vol. 20, No. 3, 01.06.2006, p. 197-213.

Research output: Contribution to journalReview article

TY - JOUR

T1 - An artificial moth

T2 - Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search

AU - Pyk, Pawel

AU - Bermúdez i Badia, Sergi

AU - Bernardet, Ulysses

AU - Knüsel, Philipp

AU - Carlsson, Mikael

AU - Gu, Jing

AU - Chanie, Eric

AU - Hansson, Bill S.

AU - Pearce, Tim C.

AU - Verschure, Paul F.M.J.

PY - 2006/6/1

Y1 - 2006/6/1

N2 - 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.

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KW - Electronic noses

KW - Gas distribution mapping

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KW - Mobile olfaction

KW - Odor discrimination

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