Odor Plume Tracking Algorithm Inspired on Evolution

Smell sensors in mobile robotics for odor source localization are getting the attention for researches around the world. To solve the problem, it must be considered the environmental model and odor behavior, the perception system and the algorithm for tracking the odors plume. Current algorithms try to emulate the behavior of the animals known by its capability to follow odors. Nevertheless, the odor perception systems are still in its infancy and far to be compared with the biological smell sense. This is why, an algorithm that considers the perception system capabilities and drawbacks, the environmental model and the odor behavior is presented on this work. Besides, an artificial intelligent technique (Genetic Programming) is used as a platform to develop odor source localization algorithms. It is prepared for different environment conditions and perception systems. A comparison between this improved algorithm and a pair of basic techiques for odor source localization is presented in terms of repeatability.

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