Guided by direct experiments on many-legged animals, mathematical models
and physical models (robots), we postulate a hierarchical family of
control loops that necessarily include constraints of the body's
mechanics. At the lowest end of this neuromechanical hierarchy, we
hypothesize the primacy of mechanical feedback - neural clocks exciting
tuned muscles acting through chosen skeletal postures. Control
algorithms appear embedded in the form and skeleton of the animal
itself. The control potential of muscles must be realized through
complex, viscoelastic bodies. Bodies can absorb and redirect energy for
transitions. Tails can be used as inertial control devices. On top of
this physical layer reside sensory feedback driven reflexes that
increase an animal's stability further and, at the highest level,
environmental sensing that operates on a stride-to-stride timescale to
direct the animal's body. Most importantly, locomotion requires an
effective interaction with the environment. Understanding control requires understanding the coupling to
environment. Amazing feet permit creatures such as geckos to climb up
walls at over meter per second without using claws, glue or suction -
just molecular forces using hairy toes. Fundamental principles of animal
locomotion have inspired the design of self-clearing dry adhesives and
autonomous legged robots such as the Ariel, Mecho-gecko, Sprawl, RHex,
RiSE and Stickybot that can aid in search and rescue, inspection,
detection and exploration.
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