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Tracking Odor Plumes in a Laminar Wind Field with Bio-inspired Algorithms

机译:利用生物启发算法跟踪层流风场中的气味羽

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摘要

We introduce a novel bio-inspired odor source localization algorithm (surge-cast) for environments with a main wind flow and compare it to two well-known algorithms. With all three algorithms, systematic experiments with real robots are carried out in a wind tunnel under laminar flow conditions. The algorithms are compared in terms of distance overhead when tracking the plume up to the source, but a variety of other experimentally measured results are provided as well. We conclude that the surge-cast algorithm yields significantly better performance than the casting algorithm, and slightly better performance than the surge-spiral algorithm.
机译:我们介绍了一种针对具有主要风流的环境的新型生物启发性气味源定位算法(浪涌铸造),并将其与两种众所周知的算法进行了比较。使用这三种算法,在层流条件下的风洞中进行了真实机器人的系统实验。在跟踪直到源的羽流时,在距离开销方面对算法进行了比较,但是还提供了其他各种实验测量的结果。我们得出的结论是,喘振铸造算法的性能要比浇铸算法好得多,而性能要比喘振螺旋算法好一些。

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