Three-dimensional statistical gas distribution mapping in an uncontrolled indoor environment

Matteo Reggente, Achim J. Lilienthal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

In this paper we present a statistical method to build three-dimensional gas distribution maps (3D-DM). The proposed mapping technique uses kernel extrapolation with a tri-variate Gaussian kernel that models the likelihood that a reading represents the concentration distribution at a distant location in the three dimensions. The method is evaluated using a mobile robot equipped with three "e-noses" mounted at different heights. Initial experiments in an uncontrolled indoor environment are presented and evaluated with respect to the ability of the 3D map, computed from the lower and upper nose, to predict the map from the middle nose.

Original languageEnglish
Title of host publicationOlfaction and Electronic Nose - Proceedings of the 13th International Symposium on Olfaction and Electronic Nose, ISOEN
Pages109-112
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event13th International Symposium on Olfaction and Electronic Nose, ISOEN - Brescia, Italy
Duration: 15 Apr 200917 Apr 2009

Publication series

NameAIP Conference Proceedings
Volume1137
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference13th International Symposium on Olfaction and Electronic Nose, ISOEN
Country/TerritoryItaly
CityBrescia
Period15/04/0917/04/09

Keywords

  • 3D-gas distribution
  • E-nose
  • Gas sensing
  • Kernel density estimation
  • Mobile robots
  • Model evaluation

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