Evolving neuro-modules and their interfaces to control autonomous robots

An evolutionary algorithm for the creation of recurrent network structures is presented. The aim is to develop neural networks controlling the behaviour of miniature robots. Two neuro-modules are created separately using this evolutionary approach. The first neuromodule gives the agents the ability to move within an environment without colliding with obstacles. The second neuro-module provides the agents with a phototropic behaviour. The interaction of the neuromodules is then investigated evolving the necessary interface to provide the agents with a coherent obstacle avoidance and phototropic behaviour. The evolution process is carried out in a simulated environment and individuals with high performance are also tested on a physical environment with the use of Khepera robots.