Gas distribution mapping and source localization using a 3D grid of metal oxide semiconductor sensors

Javier Burgués, Victor Hernández, Achim J. Lilienthal, Santiago Marco

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


The difficulty to obtain ground truth (i.e. empirical evidence) about how a gas disperses in an environment is one of the major hurdles in the field of mobile robotic olfaction (MRO), impairing our ability to develop efficient gas source localization strategies and to validate gas distribution maps produced by autonomous mobile robots. Previous ground truth measurements of gas dispersion have been mostly based on expensive tracer optical methods or 2D chemical sensor grids deployed only at ground level. With the ever-increasing trend towards gas-sensitive aerial robots, 3D measurements of gas dispersion become necessary to characterize the environment these platforms can explore. This paper presents ten different experiments performed with a 3D grid of 27 metal oxide semiconductor (MOX) sensors to visualize the temporal evolution of gas distribution produced by an evaporating ethanol source placed at different locations in an office room, including variations in height, release rate and air flow. We also studied which features of the MOX sensor signals are optimal for predicting the source location, considering different lengths of the measurement window. We found strongly time-varying and counter-intuitive gas distribution patterns that disprove some assumptions commonly held in the MRO field, such as that heavy gases disperse along ground level. Correspondingly, ground-level gas distributions were rarely useful for localizing the gas source and elevated measurements were much more informative. We make the dataset and the code publicly available to enable the community to develop, validate, and compare new approaches related to gas sensing in complex environments.

Original languageEnglish
Article number127309
JournalSensors and Actuators, B: Chemical
StatePublished - 1 Feb 2020
Externally publishedYes


  • Gas distribution mapping
  • Gas source localization
  • Metal oxide gas sensors
  • Mobile robotic olfaction
  • Sensor networks
  • Signal processing


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