Evolutionary Design of Morphology and Intelligence in Robotic System Using Genetic Programming

This paper deals with the evolutionary design of morphology and intelligence in robotic systems and the characteristics of emerged robot behaviors. A robot performs a given task in a realistic virtual world including physical conditions such as gravity, collision and friction, and is assigned fitness according to its performance. Fitness is improved by genetic programming operations, and therein the robot evolves to a reasonably optimal morphology and control architecture. The behaviors of the robot undertaking threc kinds of tasks differing in the number of objects to be picked up and task limit time are investigated. We find various morphologies and interesting intelligence emerged according to the differences in the tasks and environmental conditions. We examine the relation between robot morphology and behavior, and demonstrate the capability and flexibility of these evolutionary robotic systems.