Abstract
Spiders are able to extract crucial information, such as the location prey, predators, mates, and even broken threads from propagating web vibrations. The complex structure of the web suggests that the morphology itself might provide computational support in form of a mechanical signal processing system - often referred to as morphological computation. We present preliminary results on identifying these computational aspects in naturally spun webs. A recently presented definition for physical computational systems, consisting of three main elements: (i) a mathematical part, (ii) a computational setup with a theoretical and real part, and (iii) an interpretation, is employed for the first time, to characterize these morphological computation properties. Signal transmission properties of a real spider orb web, as the real part of a morphological computation setup, is investigated in response to step transverse inputs. The parameters of a lumped system model, as the theoretical part of a morphological computation setup, are identified empirically and with the help of an earlier FEM model for the same web. As the possible elements of a computational framework, the web transverse signal filtering, attenuation, delay, memory effect, and deformation modes are briefly discussed based on experimental data and numerical simulations.
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Acknowledgment
This work is supported by the Leverhulme Trust Research Project, “Computing with spiders’ web”, number RPG-2016-345, granted to H.H. and F.V.; and the Royal Academy of Engineering (research fellowship RF1516/15/11), granted to L.R. With special thanks to Dr. Helmut Hauser, Dr. Ludovic Renson, Dr. Beth Mortimer, Prof. Fritz Vollrth, Dr. S. Elnaz Naghibi and Alan Quille who contribute to this research by helpful discussions, exchanging ideas, proofreading the draft and providing helpful comments.
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Sadati, S.M.H., Williams, T. (2018). Toward Computing with Spider Webs: Computational Setup Realization. In: Vouloutsi , V., et al. Biomimetic and Biohybrid Systems. Living Machines 2018. Lecture Notes in Computer Science(), vol 10928. Springer, Cham. https://doi.org/10.1007/978-3-319-95972-6_43
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