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Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework.

Yiftach Golov1,2, Noam Benelli3, Roi Gurka4

  • 1Porter School of Environment and Earth Sciences, Tel Aviv University, Israel.

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|January 10, 2022
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This study introduces Mothpy, an open-source simulator for comparing moth-inspired olfactory navigation strategies. It provides a framework for statistically analyzing and improving autonomous systems in complex environments.

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Area of Science:

  • Robotics
  • Computational Biology
  • Bio-inspired Navigation

Background:

  • Olfactory navigation, crucial for organisms like moths, involves detecting airborne chemical cues for source localization.
  • Existing moth-inspired algorithms lack a standardized framework for performance comparison in controlled environments.
  • Comparing diverse bio-inspired strategies is challenging due to the absence of componential analysis tools.

Purpose of the Study:

  • To develop and present an open-source simulation framework, Mothpy, for benchmarking olfactory navigation strategies.
  • To facilitate statistical comparison of different moth-inspired navigation algorithms.
  • To aid in understanding evolutionary efficient strategies and advancing autonomous systems.

Main Methods:

  • Developed Mothpy, an open-source simulation framework for moth-like navigators.
  • Implemented two distinct moth-inspired navigation strategies with modifications, creating four navigation models.
  • Tested navigator performance in a virtual turbulent environment with varied wind and odor parameters.
  • Utilized bio-statistical tests for comprehensive performance analysis.

Main Results:

  • Mothpy enables simulation of moth-like navigators with adjustable flow conditions and navigation strategies.
  • The framework facilitates benchmarking by comparing multiple navigators across diverse environments and strategies.
  • Performance analysis revealed insights into the effectiveness of different navigation models.

Conclusions:

  • Mothpy serves as a valuable, benchmark-ready tool for both biological and engineering research.
  • The framework supports the deduction of evolutionarily efficient navigation strategies.
  • Mothpy can contribute to the improvement of self-propelled autonomous systems in complex, odor-driven environments.