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.
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Li, J., Meng, Q., Wang, Y. et al. Odor source localization using a mobile robot in outdoor airflow environments with a particle filter algorithm. Auton Robot 30, 281–292 (2011). https://doi.org/10.1007/s10514-011-9219-2
- Odor source localization
- Mobile robot
- Particle filter