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

Authors:
Ji-Gong Li;Qing-Hao Meng;Yang Wang;Ming Zeng
Affiliations:
School of Electrical Engineering and Automation, Tianjin University, Tianjin, China 300072;School of Electrical Engineering and Automation, Tianjin University, Tianjin, China 300072;School of Electrical Engineering and Automation, Tianjin University, Tianjin, China 300072;School of Electrical Engineering and Automation, Tianjin University, Tianjin, China 300072
Venue:
Autonomous Robots
Year:
2011

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Abstract

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.