Evolution of Robot Controller Using Cartesian Genetic Programming

Abstract. Cartesian Genetic Programming is a graph based representation that has many benefits over traditional tree based methods, including bloat free evolution and faster evolution through neutral search. Here, an integer based version of the representation is applied to a traditional problem in the field: evolving an obstacle avoiding robot controller. The technique is used to rapidly evolve controllers that work in a complex environment and with a challenging robot design. The generalisation of the robot controllers in different environments is also demonstrated. A novel fitness function based on chemical gradients is presented as a means of improving evolvability in such tasks.

• Type: Conference
• Year: 2005
• Where: EUROGP
• Authors: Simon Harding, Julian F. Miller
• Keywords: EUROGP 2005, Graph Based Representation, Obstacle Avoiding Robot, Robot Controllers