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gmrf_gas_mapping package from gmrf_gas_mapping repo

gmrf_gas_mapping

Package Summary

Tags No category tags.
Version 0.0.0
License GPLv3
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/mapirlab/gmrf_gas_mapping.git
VCS Type git
VCS Version ros2
Last Updated 2023-03-04
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Implementation of the Time-Variant gas distribution mapping using Gaussian Markov Random Fields See: http://mapir.isa.uma.es/jgmonroy/papers/2015_GDM_TimeVariant_Obstacles_AutonomousRobots.pdf

Additional Links

No additional links.

Maintainers

  • Javier Monroy

Authors

  • Javier Monroy

gmrf_gas_mapping

Implementation of the Time-Variant Gas Distribution Mapping technique based on Gaussian Markov Random Fields (http://mapir.isa.uma.es/jgmonroy/papers/2015_GDM_TimeVariant_Obstacles_AutonomousRobots.pdf).

This algorithm contributes an effective solution to two important problems that have been disregarded so far in the mapping of gases: First, obstacles in the environment (walls, furniture, …) do affect the gas spatial distribution. Second, when combining odor measurements taken at different instants of time, their ‘ages’ must be taken into account to model the ephemeral nature of gas distributions. In order to incorporate these two characteristics into the mapping process we propose modeling the spatial distribution of gases as a Gaussian Markov random field (GMRF). This mathematical framework allows us to consider both: (i) the vanishing information of gas readings by means of a time-increasing uncertainty in sensor measurements, and (ii) the influence of objects in the environment by means of correlations among the different areas.

Dependencies

  • olfaction_msgs: a dedicated pkg that defines specific msgs for gas and wind measurements

  • Eigen: Due to the sparse nature of samples, we accelerate the computation by relying on Eigen::SparseMatriX. sudo apt install libeigen3-dev

CHANGELOG
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Wiki Tutorials

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Dependant Packages

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Launch files

Messages

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Services

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Plugins

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