Effects of Locomotive Drift in Scale-Invariant Robotic Search Strategies

  • Carlos Garcia-SauraEmail author
  • Eduardo Serrano
  • Francisco B. Rodriguez
  • Pablo Varona
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10384)


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.


Lévy flight Bio-inspired random walks Exploration Mobile robots Scale invariance Motion drift Odor sensor 



We acknowledge support from MINECO/FEDER DPI2015-65833-P, TIN2014-54580-R (


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Carlos Garcia-Saura
    • 1
    Email author
  • Eduardo Serrano
    • 1
  • Francisco B. Rodriguez
    • 1
  • Pablo Varona
    • 1
  1. 1.Grupo de Neurocomputación Biológica, Escuela Politécnica SuperiorUniversidad Autónoma de MadridMadridSpain

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