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Estimation of Stimuli Timing to Evaluate Chemical Plume Tracing Behavior of the Silk Moth

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Robot Intelligence Technology and Applications 2

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 274))

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Abstract

Insects serve as ideal models for replicating the adaptability of biological systems in Chemical Plume Tracing (CPT) because they perform efficient olfactory tracking. In this paper, we propose to evaluate the CPT behavior of the silk moth (Bombyx Mori) from the perspective of machine learning. We use a classification approach consisting of the Gaussian Mixture Model with Expectation Maximization (GMMEM) and the Echo State Networks (ESN) to identify the initial motion phases upon stimulation. The former method classifies the locomotion observation consisting of the linear and angular velocity into Gaussian density components which represent different elemental motions. Then, these motions are used as training data for the ESN to estimate the initial motion phases upon stimulation which represents the stimuli timing. The same procedure is implemented on different moths and cross-evaluation is done among the moths in the sample to evaluate their behavior singularity. This method achieves decent estimation accuracy and serves as a feasible approach to complement the conventional neurophysiology analysis of insects’ behavior. The results also suggest the presence of CPT behavior singularity for silk moths.

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Authors and Affiliations

  1. Dept. of Mechanical and Control Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan

    Jouh Yeong Chew, Kotaro Kishi, Yohei Kinowaki & Daisuke Kurabayashi

Authors
  1. Jouh Yeong Chew
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  2. Kotaro Kishi
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  3. Yohei Kinowaki
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  4. Daisuke Kurabayashi
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Corresponding author

Correspondence to Jouh Yeong Chew .

Editor information

Editors and Affiliations

  1. Electrical Engineering, KAIST, Daejeon, Korea, Republic of (South Korea)

    Jong-Hwan Kim

  2. Computer and Information Technology, Purdue University, West Lafayette, Indiana, USA

    Eric T . Matson

  3. Civil and Environmental Engg., KAIST, Daejeon, Korea, Republic of (South Korea)

    Hyun Myung

  4. Department of Mechanical Engineering, Auckland University, Auckland, New Zealand

    Peter Xu

  5. University of Waterloo, Waterloo, Ontario, Canada

    Fakhri Karray

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Chew, J.Y., Kishi, K., Kinowaki, Y., Kurabayashi, D. (2014). Estimation of Stimuli Timing to Evaluate Chemical Plume Tracing Behavior of the Silk Moth. In: Kim, JH., Matson, E., Myung, H., Xu, P., Karray, F. (eds) Robot Intelligence Technology and Applications 2. Advances in Intelligent Systems and Computing, vol 274. Springer, Cham. https://doi.org/10.1007/978-3-319-05582-4_53

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  • DOI: https://doi.org/10.1007/978-3-319-05582-4_53

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05581-7

  • Online ISBN: 978-3-319-05582-4

  • eBook Packages: EngineeringEngineering (R0)

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