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Information-based centralization of locomotion in animals and robots

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  • Izaak D. Neveln

    (Georgia Institute of Technology)

  • Amoolya Tirumalai

    (Georgia Institute of Technology)

  • Simon Sponberg

    (Georgia Institute of Technology
    Georgia Institute of Technology)

Abstract

The centralization of locomotor control from weak and local coupling to strong and global is hard to assess outside of particular modeling frameworks. We developed an empirical, model-free measure of centralization that compares information between control signals and both global and local states. A second measure, co-information, quantifies the net redundancy in global and local control. We first validate that our measures predict centralization in simulations of phase-coupled oscillators. We then test how centralization changes with speed in freely running cockroaches. Surprisingly, across all speeds centralization is constant and muscle activity is more informative of the global kinematic state (the averages of all legs) than the local state of that muscle’s leg. Finally we use a legged robot to show that mechanical coupling alone can change the centralization of legged locomotion. The results of these systems span a design space of centralization and co-information for biological and robotic systems.

Suggested Citation

  • Izaak D. Neveln & Amoolya Tirumalai & Simon Sponberg, 2019. "Information-based centralization of locomotion in animals and robots," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11613-y
    DOI: 10.1038/s41467-019-11613-y
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