  Controlling sensori-motor systems in higher animals or complex robots is a
challenging combinatorial problem, because many sensory signals need to be
simultaneously coordinated into a broad behavioural spectrum. To rapidly
interact with the environment, this control needs to be fast and adaptive.
Current robotic solutions operate with limited autonomy and are mostly
restricted to few behavioural patterns. Here we introduce chaos control as a
new strategy to generate complex behaviour of an autonomous robot. In the
presented system, 18 sensors drive 18 motors via a simple neural control
circuit, thereby generating 11 basic behavioural patterns (e.g., orienting,
taxis, self-protection, various gaits) and their combinations. The control
signal quickly and reversibly adapts to new situations and additionally enables
learning and synaptic long-term storage of behaviourally useful motor
responses. Thus, such neural control provides a powerful yet simple way to
self-organize versatile behaviours in autonomous agents with many degrees of
freedom.

Disordered Systems and Neural Networks;Artificial Intelligence;Robotics;Chaotic Dynamics;Neurons and Cognition