Challenges and Opportunities of Evolutionary Robotics

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. Evolu- tionary techniques hold the potential to solve many diffi- cult problems in robotics which defy simple conventional approaches, but present many challenges as well. Nu- merous disciplines including artificial life, cognitive sci- ence and neural networks, rule-based systems, behavior- based control, genetic algorithms and other forms of evo- lutionary computation have contributed to shaping the current state of evolutionary robotics. This paper pro- vides an overview of developments in the emerging field of evolutionary robotics, and discusses some of the opportu- nities and challenges which currently face practitioners in the field.