Modeling of the Adaptive Chemical Plume Tracing Algorithm of an Insect Using Fuzzy Inference

Front. Comput. Neurosci.

et al. 2021

Self Cite

Insects search for and find odor sources as their basic behaviors, such as when looking for food or a mate. This has motivated research to describe how they achieve such behavior under turbulent odor plumes with a small number of neurons. Among different insects, the silk moth has been studied owing to its clear motor response to olfactory input. In past studies, the “programmed behavior” of the silk moth has been modeled as the average duration of a sequence of maneuvers based on the duration of periods without odor hits. However, this model does not fully represent the fine variations in their behavior. In this study, we used silk moth olfactory search trajectories from an experimental virtual reality device. We achieved an accurate input by using optogenetic silk moths that react to blue light. We then modeled such trajectories as a probabilistic learning agent with a belief of possible source locations. We found that maneuvers mismatching the programmed behavior are related to larger entropy decrease, that is, they are more likely to increase the certainty of the belief. This implies that silkmoths include some stochasticity in their search policy to balance the exploration and exploitation of olfactory information by matching or mismatching the programmed behavior model. We believe that this information-theoretic representation of insect behavior is important for the future implementation of olfactory searches in artificial agents such as robots.

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of Exploration and Exploitation Balance in the Silkmoth Olfactory Search Behavior by Information-Theoretic Modeling

Hernandez-Reyes

Fukushima

Front. Comput. Neurosci.

et al. 2021

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“…However, the output of CPT behaviour, such as movement velocity and timing of switching action phases, varies depending on the environmental situation. Although a CPT model reflecting this adaptability may further improve the CPT performance, the mechanism remains unclear [19]. Therefore, we expect that a data-driven CPT model can reflect the underlying adaptability of the moth, possibly outperforming existing modelbased CPT models.…”

Section: Problem Statementmentioning

confidence: 99%

“…Almost all existing biomimetic methods use model-based strategies [16][17][18] which are based on an organism's characteristic behaviour. Although these strategies may lead a CPT agent to the source of the odour, the adaptability of organisms modulating their behaviour depending on the surrounding environment (such as [19]) may be lost through these strategies. Thus, their performance depends upon environmental conditions and an effective CPT model should take into account an organism's adaptability.…”

Section: Introductionmentioning

confidence: 99%

A novel framework based on a data-driven approach for modelling the behaviour of organisms in chemical plume tracing

Okajima

Suko

et al. 2021

J. R. Soc. Interface.

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We propose a data-driven approach for modelling an organism's behaviour instead of conventional model-based strategies in chemical plume tracing (CPT). CPT models based on this approach show promise in faithfully reproducing organisms’ CPT behaviour. To construct the data-driven CPT model, a training dataset of the odour stimuli input toward the organism is needed, along with an output of the organism’s CPT behaviour. To this end, we constructed a measurement system comprising an array of alcohol sensors for the measurement of the input and a camera for tracking the output in a real scenario. Then, we determined a transfer function describing the input–output relationship as a stochastic process by applying Gaussian process regression, and established the data-driven CPT model based on measurements of the organism’s CPT behaviour. Through CPT experiments in simulations and a real environment, we evaluated the performance of the data-driven CPT model and compared its success rate with those obtained from conventional model-based strategies. As a result, the proposed data-driven CPT model demonstrated a better success rate than those obtained from conventional model-based strategies. Moreover, we considered that the data-driven CPT model could reflect the aspect of an organism’s adaptability that modulated its behaviour with respect to the surrounding environment. However, these useful results came from the CPT experiments conducted in simple settings of simulations and a real environment. If making the condition of the CPT experiments more complex, we confirmed that the data-driven CPT model would be less effective for locating an odour source. In this way, this paper not only poses major contributions toward the development of a novel framework based on a data-driven approach for modelling an organism’s CPT behaviour, but also displays a research limitation of a data-driven approach at this stage.

“…This unique behavior in combination with three different walking patterns (zigzag, surge, and loop) triggered by pheromone stimulation is thought to contribute to their effective odor search mechanisms [ 34 ]. It is also known that odor source search behavior is regulated by the frequency of the odor-receptive stimulation [ 34 , 35 ]. It is quite possible for the frequency of the flapping to change depending on the frequency of the odor reception because walking has a high correlation with flapping [ 36 , 37 ].…”

Section: Analysis Of Flapping Changes With Behaviormentioning

confidence: 99%

Wearable Vibration Sensor for Measuring the Wing Flapping of Insects

Yanagisawa

Yasui

et al. 2021

Sensors

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In this study, we fabricated a novel wearable vibration sensor for insects and measured their wing flapping. An analysis of insect wing deformation in relation to changes in the environment plays an important role in understanding the underlying mechanism enabling insects to dynamically interact with their surrounding environment. It is common to use a high-speed camera to measure the wing flapping; however, it is difficult to analyze the feedback mechanism caused by the environmental changes caused by the flapping because this method applies an indirect measurement. Therefore, we propose the fabrication of a novel film sensor that is capable of measuring the changes in the wingbeat frequency of an insect. This novel sensor is composed of flat silver particles admixed with a silicone polymer, which changes the value of the resistor when a bending deformation occurs. As a result of attaching this sensor to the wings of a moth and a dragonfly and measuring the flapping of the wings, we were able to measure the frequency of the flapping with high accuracy. In addition, as a result of simultaneously measuring the relationship between the behavior of a moth during its search for an odor source and its wing flapping, it became clear that the frequency of the flapping changed depending on the frequency of the odor reception. From this result, a wearable film sensor for an insect that can measure the displacement of the body during a particular behavior was fabricated.