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Odor Plume Tracking Algorithm Inspired on Evolution

机译:气味羽毛跟踪算法启发了演进

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摘要

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.
机译:气味源定位的移动机器人中的嗅觉传感器正在引起世界各地的研究。为了解决问题,必须考虑追踪气味羽流的环境模型和气味行为,感知系统和算法。目前的算法尝试模拟其能力所知的动物的行为跟踪气味。尽管如此,气味感知系统仍处于婴儿期,远远与生物嗅觉感相比。这就是为什么这项工作提出了一种考虑感知系统能力和缺点的算法,环境模型和气味行为。此外,人工智能技术(基因编程)用作开发气味源定位算法的平台。它是为不同的环境条件和感知系统做好准备。在重复性方面呈现了这种改进的算法与一对基本技术的比较,以重复性呈现。

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