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Olfaction

Olfaction

The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
The olfactory receptors are embedded in the cilia of the...

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Updated: Jul 24, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

A Comparison of Multiple Odor Source Localization Algorithms.

Marshall Staples^1,2, Chris Hugenholtz¹, Alex Serrano-Ramirez²

¹Centre for Smart Emissions Sensing Technologies, Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada.

Sensors (Basel, Switzerland)

|July 11, 2023

Summary

The Independent Posteriors (IP) algorithm is superior for multiple odor source localization in turbulent flow compared to Dempster-Shafer theory. IP minimizes false positives, accurately identifying odor sources.

Keywords:

gas source localization mobile robot olfaction remote gas sensing

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Area of Science:

Robotics
Artificial Intelligence
Fluid Dynamics

Background:

Autonomous multiple odor source localization (MOSL) is crucial for identifying emission sources.
Turbulent fluid flow presents significant challenges for accurate odor source detection.

Purpose of the Study:

To evaluate and compare the performance of Independent Posteriors (IP) and Dempster-Shafer (DS) theory algorithms for MOSL.
To understand the limitations and effectiveness of these algorithms under varying environmental and search conditions.

Main Methods:

Implemented occupancy grid mapping for source probability assessment.
Tested both IP and DS algorithms under diverse environmental and odor search parameters.
Quantified localization performance using the earth mover's distance metric.

Main Results:

The IP algorithm demonstrated superior performance by reducing false positive source attributions.
IP correctly identified actual odor source locations.
The DS theory algorithm, while identifying sources, incorrectly attributed emissions to numerous non-source locations.

Conclusions:

The IP algorithm is a more suitable approach for multiple odor source localization in turbulent fluid flow environments.
Further understanding of algorithm performance is necessary for practical applications.