Abstract
Abstract Embodiment has led to a revolution in
robotics by not thinking of the robot body and its
controller as two separate units, but taking into
account the interaction of the body with its
environment. By investigating the effect of the body on
the overall control computation, it has been suggested
that the body is effectively performing computations,
leading to the term morphological computation. Recent
work has linked this to the field of reservoir
computing, allowing one to endow morphologies with a
theory of universal computation. In this work, we study
a family of highly dynamic body structures, called
tensegrity structures, controlled by one of the
simplest kinds of ?brains.? These structures can be
used to model biomechanical systems at different
scales. By analyzing this extreme instantiation of
compliant structures, we demonstrate the existence of a
spectrum of choices of how to implement control in the
body-brain composite. We show that tensegrity
structures can maintain complex gaits with linear
feedback control and that external feedback can
intrinsically be integrated in the control loop. The
various linear learning rules we consider differ in
biological plausibility, and no specific assumptions
are made on how to implement the feedback in a physical
system.
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