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Odor source localization using a mobile robot in outdoor airflow environments with a particle filter algorithm.
- Source :
- Autonomous Robots; Apr2011, Vol. 30 Issue 3, p281-292, 12p
- Publication Year :
- 2011
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- MOBILE robots
ALGORITHMS
OLFACTORY receptors
ROBOTICS
MACHINE theory
Subjects
Details
- Language :
- English
- ISSN :
- 09295593
- Volume :
- 30
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Autonomous Robots
- Publication Type :
- Academic Journal
- Accession number :
- 58627953
- Full Text :
- https://doi.org/10.1007/s10514-011-9219-2