Robot Odor Localization: A Taxonomy and Survey

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  • Gideon Kowadlo
    Intelligent Robotics Research Centre, Electronics and Computer Systems Engineering, Monash University, Victoria 3800, Australia,
  • R. Andrew Russell
    Intelligent Robotics Research Centre, Electronics and Computer Systems Engineering, Monash University, Victoria 3800, Australia

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<jats:p> Robotic odor localization has become a prominent research area in recent years. It promises many valuable practical applications, and contributes to the knowledge of biological odor localization, which has in many cases been the source of inspiration. There have been a diversity of approaches, implemented in both simulated and practical experiments, with a wide variety of platforms, and in a number of environments. This article presents a survey of the existing methods, which have been organized into taxonomic classifications. This provides a framework in which to evaluate the methods, view how they relate to each other, and make qualitative comparisons. The methods are grouped at the highest level by environmental conditions, and then by the localization method which in most cases is closely associated with the type of sensors used. </jats:p>

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