We present self-organizing control principles for simulated
robots actuated by synthetic muscles. Muscles correspond to linear mo-
tors exerting force only when contracting, but not when expanding, with
joints being actuated by pairs of antagonistic muscles. Individually, mus-
cles are connected to a controller composed of a single neuron with a
dynamical threshold that generates target positions for the respective
muscle. A stable limit cycle is generated when the embodied feedback
loop is closed, giving rise to regular locomotive patterns. In the absence
of direct couplings between neurons, we show that force-mediated intra-
and inter-leg couplings between muscles suffice to generate stable gaits.