  We examine the hypothesis, that short-term synaptic plasticity (STSP) may
generate self-organized motor patterns. We simulated sphere-shaped autonomous
robots, within the LPZRobots simulation package, containing three weights
moving along orthogonal internal rods. The position of a weight is controlled
by a single neuron receiving excitatory input from the sensor, measuring its
actual position, and inhibitory inputs from the other two neurons. The
inhibitory connections are transiently plastic, following physiologically
inspired STSP-rules. We find that a wide palette of motion patterns are
generated through the interaction of STSP, robot, and environment (closed-loop
configuration), including various forward meandering and circular motions,
together with chaotic trajectories. The observed locomotion is robust with
respect to additional interactions with obstacles. In the chaotic phase the
robot is seemingly engaged in actively exploring its environment. We believe
that our results constitute a concept of proof that transient synaptic
plasticity, as described by STSP, may potentially be important for the
generation of motor commands and for the emergence of complex locomotion
patterns, adapting seamlessly also to unexpected environmental feedback. We
observe spontaneous and collision induced mode switchings, finding in addition,
that locomotion may follow transiently limit cycles which are otherwise
unstable. Regular locomotion corresponds to stable limit cycles in the
sensorimotor loop, which may be characterized in turn by arbitrary angles of
propagation. This degeneracy is, in our analysis, one of the drivings for the
chaotic wandering observed for selected parameter settings, which is induced by
the smooth diffusion of the angle of propagation.
