Autonomous Robots

, Volume 30, Issue 3, pp 281–292 | Cite as

Odor source localization using a mobile robot in outdoor airflow environments with a particle filter algorithm

  • Ji-Gong Li
  • Qing-Hao Meng
  • Yang Wang
  • Ming Zeng


This paper discusses odor source localization (OSL) using a mobile robot in an outdoor time-variant airflow environment. A novel OSL algorithm based on particle filters (PF) is proposed. When the odor plume clue is found, the robot performs an exploratory behavior, such as a plume-tracing strategy, to collect more information about the previously unknown odor source. In parallel, the information collected by the robot is exploited by the PF-based OSL algorithm to estimate the location of the odor source in real time. The process of the OSL is terminated if the estimated source locations converge within a given small area. The Bayesian-inference-based method is also performed for comparison. Experimental results indicate that the proposed PF-based OSL algorithm performs better than the Bayesian-inference-based OSL method.


Odor source localization Olfaction Mobile robot Particle filter 


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Supplementary material

10514_2011_9219_MOESM1_ESM.doc (36 kb)
Explanation to the three Videos (DOC 35,5 KB)

Exploration for OSL (WMV 4,08 MB)

10514_2011_9219_MOESM3_ESM.wmv (1.8 mb)
Reconstructed Bayesian (WMV 1,83 MB)
10514_2011_9219_MOESM4_ESM.wmv (1.9 mb)
Reconstructed PF (WMV 1,87 MB)


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Ji-Gong Li
    • 1
  • Qing-Hao Meng
    • 1
  • Yang Wang
    • 1
  • Ming Zeng
    • 1
  1. 1.School of Electrical Engineering and AutomationTianjin UniversityTianjinChina

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