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Odor Plume Tracking Algorithm Inspired on Evolution

机译:进化启发的气味羽流跟踪算法

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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:用于气味源定位的移动机器人中的气味传感器正在引起全球研究的关注。为了解决该问题,必须考虑环境模型和气味行为,感知系统以及用于追踪气味羽流的算法。当前的算法试图模仿动物的行为,这种行为以其追踪气味的能力而著称。然而,气味感知系统仍处于起步阶段,与生物气味感知相比尚远。这就是为什么在这项工作中提出了一种考虑感知系统功能和缺点,环境模型和气味行为的算法。此外,人工智能技术(遗传编程)被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准备的。在可重复性方面,提出了此改进算法与用于气味源定位的一对基本技术之间的比较。

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