Abstract
Robots play a fundamental role in the exploration of environments that are harmful to humans or animals: robotic probes can reach deep into the earth’s crust, explore our oceans, traverse high radiation areas, navigate in outer space, etc. The harsh conditions and large amounts of uncertainty of these environments can complicate the use of global positioning systems, and in some cases robots have to depend exclusively in local information as external position landmarks are not available. Lévy walks are increasingly studied as effective solutions in these exploratory contexts. The superdiffusive (dispersive) properties of these forms of random walks are often exploited by many animal species, in particular when tackling search problems that have uncertainty. Based on experimentation with low-cost mobile robots, this work has characterized how long-term motion drift (which is inherent to search contexts that lack global positioning systems) can have an effect in the overall characteristics of Lévy trajectories. The results show that Lévy-based searches can be robust and maintain superdiffusive properties for some ranges of motion drift parameters that are closely related to the scale of the search problem. Locomotive drift seems to act effectively as a long-term truncation parameter that could be corrected or even incorporated during the design of a search task.
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Acknowledgements
We acknowledge support from MINECO/FEDER DPI2015-65833-P, TIN2014-54580-R (http://www.mineco.gob.es/).
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Garcia-Saura, C., Serrano, E., Rodriguez, F.B., Varona, P. (2017). Effects of Locomotive Drift in Scale-Invariant Robotic Search Strategies. In: Mangan, M., Cutkosky, M., Mura, A., Verschure, P., Prescott, T., Lepora, N. (eds) Biomimetic and Biohybrid Systems. Living Machines 2017. Lecture Notes in Computer Science(), vol 10384. Springer, Cham. https://doi.org/10.1007/978-3-319-63537-8_14
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