We report on real-robot odor source localization experiments carried out in an environment with obstacles in the odor plume. The robot was equipped with an ethanol sensor and a wind direction sensor, and the experiments were carried out in a wind tunnel, i.e. in a controlled environment. An enhanced version of the surge-spiral algorithm was used, which was augmented with a dedicate behavior to manage obstacles (avoid them, or follow their contour). We compare the results in terms of distance overhead and success rate, and discuss the impact of obstacles on plume traversal.
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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 experimental results and some theoretical considerations 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.