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A Comparison of Multiple Odor Source Localization Algorithms.
Marshall Staples1,2, 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.
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.
