  Robotic hardware designs are becoming more complex as the variety and number
of on-board sensors increase and as greater computational power is provided in
ever-smaller packages on-board robots. These advances in hardware, however, do
not automatically translate into better software for controlling complex
robots. Evolutionary techniques hold the potential to solve many difficult
problems in robotics which defy simple conventional approaches, but present
many challenges as well. Numerous disciplines including artificial life,
cognitive science and neural networks, rule-based systems, behavior-based
control, genetic algorithms and other forms of evolutionary computation have
contributed to shaping the current state of evolutionary robotics. This paper
provides an overview of developments in the emerging field of evolutionary
robotics, and discusses some of the opportunities and challenges which
currently face practitioners in the field.
