An on-line method to evolve behavior and to control a miniature robot in real time with genetic programming

We present a novel evolutionary approach to robotic control of a real robot based on genetic programming (GP). Our approach uses GP techniques that manipulate machine code to evolve control programs for robots. This variant of GP has several advantages over a conventional GP system, such as higher speed, lower memory requirements, and better real-time properties. Previous attempts to apply GP in robotics use simulations to evaluate control programs and have difficulties with learning tasks involving a real robot We present an on-line control method that is evaluated in two different physical environments and applied to two tasks-obstacle avoidance and object following-using the Khepera robot platform. The results show fast learning and good generalization.