School of Cognitive and Computing Sciences,
University of
Sussex,
Brighton BN1 9QH,
England.
E-mail: adrianth@sussex.ac.uk
Adrian Thompson
Artificial evolution can operate upon reconfigurable electronic circuits to
produce efficient and powerful control systems for autonomous mobile robots.
Evolving physical hardware instead of control systems simulated in software
results in more than just a raw speed increase: it is possible to exploit the
physical properties of the implementation (such as the semiconductor physics
of integrated circuits) to obtain control circuits of unprecedented power. The
space of these evolvable circuits is far larger than the space of solutions in
which a human designer works, because to make design tractable, a more
abstract view than that of detailed physics must be adopted. To allow circuits
to be designed at this abstract level, constraints are applied to the design
that limit how the natural dynamical behaviour of the components is reflected
in the overall behaviour of the system. This paper reasons that these
constraints can be removed when using artificial evolution, releasing huge
potential even from small circuits. Experimental evidence is given for this
argument, including the first reported evolution of a real hardware control
system for a real robot.
Keywords: Evolvable Hardware, Evolutionary Robotics, Physics of
Computation.