Structure and function of evolved neuro-controllers for autonomous robots

The Artificial Life approach to Evolutionary Robotics is used as a fundamental framework for the development of a modular neural control of autonomous mobile robots. The applied evolutionary technique is especially designed to grow different neural structures with complex dynamical properties. This is due to a modular neurodynamics approach to cognitive systems, stating that cognitive processes are the result of interacting dynamical neuro-modules. The evolutionary algorithm is described, and a few examples for the versatility of the procedures are given. Besides solutions for standard tasks like exploration, obstacle avoidance, and tropism, as well as the sequential evolution of morphology and control of a biped is demonstrated. A further example describes the co-evolution of different neuro-controllers cooperating to keep a gravitationally driven art-robot in constant rotation.

• Type: Journal
• Year: 2004
• Where: CONNECTION
• Authors: Martin Hülse, Steffen Wischmann, Frank Pasemann
• Keywords: Applied Evolutionary Technique, CONNECTION 2004, Evolutionary, Modular Neural Control