Achim J. Lilienthal, Marco Trincavelli and Erik Schaffernicht
It's always smelly around here! Modeling the Spatial Distribution of Gas Detection Events with BASED Grid Maps
Proceedings of the 15th International Symposium on Olfaction and Electronic Nose (ISOEN 2013), July 2-5, 2013, Daegu, South Korea.
Abstract: In this paper we introduce a novel gas distribution mapping algorithm, Bayesian Spatial Event Distribution (BASED), that, instead of modeling the spatial distribution of the gas concentration, models the spatial distribution of events of detection and non-detection of a target gas. The proposed algorithm is based on the Bayesian inference framework and models the likelihood of events at a certain location with a Bernoulli distribution. In order to avoid overfitting a Bayesian approach is used with a beta distribution prior for the parameter u that governs the Bernoulli distribution. In this way, the posterior distribution maintains the same form of the prior, i.e. will be a beta distribution, enabling a simple approach for sequential learning. To learn a field of beta distributions, we discretize the inspection area into a grid map and extrapolate from local measurements using Gaussian kernels. We demonstrate the proposed algorithm for different sensors mounted on a mobile robot and show how qualitatively similar maps are obtained from very different gas sensors.
Keywords: Gas Distribution Mapping, Bayesian Statistical Modeling, Beta Distribution
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@INPROCEEDINGS{Lilienthal_etal:ISOEN:2013,
  AUTHOR = {Lilienthal, Achim and Trincavelli, Marco and Schaffernicht, Erik}
  TITLE = {It's always smelly around here! Modeling the Spatial Distribution of Gas Detection Events with BASED Grid Maps},
  BOOKTITLE = {Proceedings of the 15th International Symposium on Olfaction and Electronic Nose (ISOEN 2013)},
  VOLUME = {},
  YEAR = {2013},
  DATE = {July 2--5},
  ADRESS = {Daegu, South Korea},
  PAGES = {}
  DOI = {}
}