Chemotactic Search in Complex Environments

Pearce, Tim; Chong, Kwok Ying; Verschure, Paul F. M. J.; Bermudez, i Badia S; Carlsson, Mikael A.; Chanie, Eric; Hansson, Bill S.

doi:10.1007/1-4020-2319-7_13

Cited by 6 publications

(1 citation statement)

References 55 publications

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“…Male moths, for example, locate females by modulating their flight patterns in response to female sex pheromones whilst bumblebees locate nectaring plants and female butterflies locate potential oviposition sites by responding to plant odors (Andersson & Dobson, 2003;Baker & Vickers, 1997;Honda, Omura, & Hayashi, 1998;Proctor, Lack, & Yeo, 1996). Robots have been designed to search for sources of hazardous chemicals or pollutants, unexploded ordinance and undersea wreckage (e.g., Farrell, Pang, & Li, 2005;Li, Farrell, & Cardé, 2001;Pearce et al, 2004;Rutkowski, Edwards, Willis, Quinn, & Causey, 2004;Webb, 2002; and references therein).…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Different Searching Strategies to Locate Sources of Odor in Turbulent Flows

Iacono

2010

Adaptive Behavior

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Four different searching strategies to locate the source of odor in turbulent flows have been computationally tested. These algorithms can be separated into two classes. One is based on the rate of odor patches encountered by the searcher, the other employs the variation of odor concentrations as well as the rate of odor patches experienced by the searcher. The concentration of odor has been simulated by using a stochastic model for the time-evolution of concentrations along the path of a moving observer in an inhomogeneous plume. For each algorithm, we released the searchers at a crosswind location away from the plume centerline; we then calculated the ensemble average position relative to the plume centerline and the distribution of the searchers along the crosswind direction at the source. Compared with strategies using rate of odor patches only, the algorithms that also employ the variation of concentrations are seen to be more effective in locating the source; that is, the average path of all searchers is more biased toward the plume centerline and their crosswind distribution is more skewed toward the source. The findings of this work can be used as guidelines to discriminate successful strategies that can be tested in future experiments

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Section: Introductionmentioning

confidence: 99%

A Comparison of Different Searching Strategies to Locate Sources of Odor in Turbulent Flows

Iacono

2010

Adaptive Behavior

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Insect-Like Odor Classification and Localization on an Autonomous Robot

Lopez-Serrano

Vouloutsi

Chimeno

et al. 2012

Biomimetic and Biohybrid Systems

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

et al. 2006

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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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Chemotactic Search in Complex Environments

Cited by 6 publications

References 55 publications

A Comparison of Different Searching Strategies to Locate Sources of Odor in Turbulent Flows

A Comparison of Different Searching Strategies to Locate Sources of Odor in Turbulent Flows

Insect-Like Odor Classification and Localization on an Autonomous Robot

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

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