Abstract
In this paper, we describe a novel swarming framework that guides autonomous mobile sensors into a flexible arrangement to interpolate values of a field in an unknown region. The algorithm is devised so that the sensor distribution will behave like a Chebyshev distribution, which can be optimal for certain ideal geometries. The framework is designed to dynamically adjust to changes in the region of interest, and operates well with very little a priori knowledge of the given region.
For comparison, we interpolate a variety of nontrivial fields using a standard swarming algorithm that produces a uniform distribution and our new algorithm. We find that our new algorithm interpolates fields with greater accuracy.
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Kirby, J., de Oca, M.A.M., Senger, S., Rossi, L.F., Shen, CC. (2012). Swarm Interpolation Using an Approximate Chebyshev Distribution. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2012. Lecture Notes in Computer Science, vol 7461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32650-9_34
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DOI: https://doi.org/10.1007/978-3-642-32650-9_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32649-3
Online ISBN: 978-3-642-32650-9
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